This document discusses a vector precoding scheme for multi-user MIMO systems. It proposes using vector precoding to circumvent the channel inversion required for zero forcing precoding. The scheme develops a joint transmitter-receiver design where the transmitter precoder lies in the null space of other users' channels to eliminate multi-user interference. Simulation results show the proposed approach improves bit error rate performance by an order of magnitude compared to zero forcing, and increases MIMO broadcast channel capacity with lower complexity than inversion-based techniques.
A New Transmission Scheme for MIMO – OFDMijsrd.com
This contribution introduces a new transmission scheme for multiple-input multiple-output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems. The new scheme is efficient and suitable especially for symmetric channels such as the link between two base stations or between two antennas on radio beam transmission. This survey Paper presents the performance analysis of V-BLAST based multiple inputs multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system with respect to bit error rate per signal to noise ratio (BER/SNR) for various detection techniques. A 2X2 MIMO-OFDM system is used for the performance evaluation. The simulation results shows that the performance of V-BLAST based detection techniques is much better than the conventional methods. Alamouti Space Time Block Code (STBC) scheme is used with orthogonal designs over multiple antennas which showed simulated results are identical to expected theoretical results. With this technique both Bit Error Rate (BER) and maximum diversity gain are achieved by increasing number of antennas on either side. This scheme is efficient in all the applications where system capacity is limited by multipath fading.
Pilot Decontamination over Time Frequency and Space Domains in Multi-Cell Ma...IJECEIAES
In this article, we show that Pilot contamination problem can be seen as a source separation problem using time, frequency, and space domains. Our method capitalizes on a nonunitary joint diagonalization of spatial quadratic time-frequency (STFD) signal representation to identify the desired and interfering users. We first compute the noise subspace from the STFD matrices selected appropriately. Secondly, we use the noise subspace obtained to estimate the Elevation (El) and the Azimuth (Az) angles for which the MUSIC cost function is maximized. Numerical simulations are provided to illustrate the effectiveness and the behavior of the proposed approach.
Investigating the Effect of Mutual Coupling on SVD Based Beam-forming over MI...CSCJournals
This paper investigates the effect of mutual coupling on the performance of SVD based beam-forming technique over a Rician MIMO channel. SVD based beam-forming technique were proposed as a baseband signal processing algorithm to combat NLOS issues. However, most of the researches done in regards to SVD based beam-forming technique are based on the assumption of “ideal array antennas” in which lots of practical issues including the transmitter and receiver array geometry, the number of antenna elements, the inter-element spacing and orientation are not considered. Particularly, the effect of mutual coupling due to finite element spacing is neglected. In real array antennas, Mutual Coupling (MC) is always present and its effects cannot be neglected, especially for tightly spaced arrays. Although the presence of mutual coupling leads to the “cross talk” problems for the SVD based beam-forming techniques. However, it does not adversely affect the system capacity. For some particular range of SNR, inter-element spacing, mutual coupling can in fact increase the capacity and in fact be beneficial in terms of decreasing SER
Combining SFBC_OFDM Systems with SVD Assisted Multiuser Transmitter and Multi...IOSR Journals
Abstract: In this work, we exploit the SVD assisted multiuser transmitter (MUT) and multiuser detector (MUD) technique, using downlink (DL) preprocessing transmitter and DL postprocessing receiver matrice .In combination with space frequency block coding (SFBC). And also propose the precoded DL transmission scheme, were the both proposed schemes take advantage of the channel state information (CSI) of all users at the base station (BS), but only of the mobile station (MS)’s own CSI, to decompose the MU MIMO channels into parallel single input single output (SISO), these two proposed schemes are compared to the vertical layered space time (V_BLAST) combined with SFBC (SFBC_VBLAST). Our Simulation results show that the performance of the proposed scheme with DL Zero Forcing (ZF) transmitter for interference canceller outperforms the SFBC_VBLAST and the precoded DL schemes with ZF receiver in frequency selective fading channels. Keywords – Post processing, Preprocessing,, SFBC, SVD, ZF.
Using the Channel State Information (CSI) at the transmitter is fundamental for the precoder
design in Multi-user Multiple Input Single Output (MU-MISO-OFDM) systems. In Frequency
Division Duplex (FDD) systems, CSI can be just available at the transmitter through a limited
feedback channel [1], where we assume that each user quantizes its channel direction with a
finite number of quantization bits. In this paper, we consider a scalar quantization (SQ) scheme
of the Channel Direction Information (CDI). Although vector quantization (VQ) schemes [2],
[3] still outperform this scalar scheme in terms of quantization error and Sum rate, the former
scheme suffers from an exponential search complexity and high storage requirements at the
receiver for high number of feedback bits.
Effect of Channel Variations on the Spectral Efficiency of Multiuser Diversit...IDES Editor
The high spectral efficiency or high user data rates
from multiuser diversity scheme using MIMO systems with
antenna selection and MRC reception is very important
development for modern cellular communications. Usually in
a service area of such system, the channel type is assumed to
remain constant, and in a Rayleigh fading environment such
systems are found to provide the highest data rate to a scheduled
user. In a service area using multiuser diversity MIMO
technology, the users at different locations may not experience
the same channel type and hence practically observed data
rates differ from the assumed values. We present in this report
how the scheduled user data rate suffers if the channel type
deviates from Rayleigh to Nakagami-m fading in the cellular
service area, both for absolute or dedicated SNR scheduling
scheme and proportional or normalized SNR scheduling
scheme. We explore the loss of user data rates in different
received SNR regime 0 dB, 10 dB, and 20 dB, and for different
m values with different MIMO configurations. We find that at
0 dB per antenna received SNR the loss of user data rates are
the highest.
A New Transmission Scheme for MIMO – OFDMijsrd.com
This contribution introduces a new transmission scheme for multiple-input multiple-output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems. The new scheme is efficient and suitable especially for symmetric channels such as the link between two base stations or between two antennas on radio beam transmission. This survey Paper presents the performance analysis of V-BLAST based multiple inputs multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system with respect to bit error rate per signal to noise ratio (BER/SNR) for various detection techniques. A 2X2 MIMO-OFDM system is used for the performance evaluation. The simulation results shows that the performance of V-BLAST based detection techniques is much better than the conventional methods. Alamouti Space Time Block Code (STBC) scheme is used with orthogonal designs over multiple antennas which showed simulated results are identical to expected theoretical results. With this technique both Bit Error Rate (BER) and maximum diversity gain are achieved by increasing number of antennas on either side. This scheme is efficient in all the applications where system capacity is limited by multipath fading.
Pilot Decontamination over Time Frequency and Space Domains in Multi-Cell Ma...IJECEIAES
In this article, we show that Pilot contamination problem can be seen as a source separation problem using time, frequency, and space domains. Our method capitalizes on a nonunitary joint diagonalization of spatial quadratic time-frequency (STFD) signal representation to identify the desired and interfering users. We first compute the noise subspace from the STFD matrices selected appropriately. Secondly, we use the noise subspace obtained to estimate the Elevation (El) and the Azimuth (Az) angles for which the MUSIC cost function is maximized. Numerical simulations are provided to illustrate the effectiveness and the behavior of the proposed approach.
Investigating the Effect of Mutual Coupling on SVD Based Beam-forming over MI...CSCJournals
This paper investigates the effect of mutual coupling on the performance of SVD based beam-forming technique over a Rician MIMO channel. SVD based beam-forming technique were proposed as a baseband signal processing algorithm to combat NLOS issues. However, most of the researches done in regards to SVD based beam-forming technique are based on the assumption of “ideal array antennas” in which lots of practical issues including the transmitter and receiver array geometry, the number of antenna elements, the inter-element spacing and orientation are not considered. Particularly, the effect of mutual coupling due to finite element spacing is neglected. In real array antennas, Mutual Coupling (MC) is always present and its effects cannot be neglected, especially for tightly spaced arrays. Although the presence of mutual coupling leads to the “cross talk” problems for the SVD based beam-forming techniques. However, it does not adversely affect the system capacity. For some particular range of SNR, inter-element spacing, mutual coupling can in fact increase the capacity and in fact be beneficial in terms of decreasing SER
Combining SFBC_OFDM Systems with SVD Assisted Multiuser Transmitter and Multi...IOSR Journals
Abstract: In this work, we exploit the SVD assisted multiuser transmitter (MUT) and multiuser detector (MUD) technique, using downlink (DL) preprocessing transmitter and DL postprocessing receiver matrice .In combination with space frequency block coding (SFBC). And also propose the precoded DL transmission scheme, were the both proposed schemes take advantage of the channel state information (CSI) of all users at the base station (BS), but only of the mobile station (MS)’s own CSI, to decompose the MU MIMO channels into parallel single input single output (SISO), these two proposed schemes are compared to the vertical layered space time (V_BLAST) combined with SFBC (SFBC_VBLAST). Our Simulation results show that the performance of the proposed scheme with DL Zero Forcing (ZF) transmitter for interference canceller outperforms the SFBC_VBLAST and the precoded DL schemes with ZF receiver in frequency selective fading channels. Keywords – Post processing, Preprocessing,, SFBC, SVD, ZF.
Using the Channel State Information (CSI) at the transmitter is fundamental for the precoder
design in Multi-user Multiple Input Single Output (MU-MISO-OFDM) systems. In Frequency
Division Duplex (FDD) systems, CSI can be just available at the transmitter through a limited
feedback channel [1], where we assume that each user quantizes its channel direction with a
finite number of quantization bits. In this paper, we consider a scalar quantization (SQ) scheme
of the Channel Direction Information (CDI). Although vector quantization (VQ) schemes [2],
[3] still outperform this scalar scheme in terms of quantization error and Sum rate, the former
scheme suffers from an exponential search complexity and high storage requirements at the
receiver for high number of feedback bits.
Effect of Channel Variations on the Spectral Efficiency of Multiuser Diversit...IDES Editor
The high spectral efficiency or high user data rates
from multiuser diversity scheme using MIMO systems with
antenna selection and MRC reception is very important
development for modern cellular communications. Usually in
a service area of such system, the channel type is assumed to
remain constant, and in a Rayleigh fading environment such
systems are found to provide the highest data rate to a scheduled
user. In a service area using multiuser diversity MIMO
technology, the users at different locations may not experience
the same channel type and hence practically observed data
rates differ from the assumed values. We present in this report
how the scheduled user data rate suffers if the channel type
deviates from Rayleigh to Nakagami-m fading in the cellular
service area, both for absolute or dedicated SNR scheduling
scheme and proportional or normalized SNR scheduling
scheme. We explore the loss of user data rates in different
received SNR regime 0 dB, 10 dB, and 20 dB, and for different
m values with different MIMO configurations. We find that at
0 dB per antenna received SNR the loss of user data rates are
the highest.
A Potent MIMO–OFDM System Designed for Optimum BER and its Performance Anal...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Overview about MIMO
Contents:
Diversity Definition
Why Diversity
Types of Diversity
Types of combining
MIMO Definition
Why MIMO ?
MIMO Advantages and disadvantages
Applications of MIMO
Computationally Efficient Multi-Antenna Techniques for Multi-User Two-Way Wire...IJECEIAES
In this work, we are interested in implementing, developing and evaluating multi-antenna techniques used for multi-user two-way wireless relay networks that provide a good tradeoff between the computational complexity and performance in terms of symbol error rate and achievable data rate. In particular, a variety of newly multi-antenna techniques is proposed and studied. Some techniques based on orthogonal projection enjoy low computational complexity. However, the performance penalty associated with them is high. Other techniques based on maximum likelihood strategy enjoy high performance, however, they suffer from very high computational complexity. The Other techniques based on randomization strategy provide a good trade-off between the computational complexity and performance where they enjoy low computational complexity with almost the same performance as compared to the techniques based on maximum likelihood strategy.
Performance Analysis of Massive MIMO Downlink System with Imperfect Channel S...IJRES Journal
We investigate the ergodic sum rate and required transmit power of a single-cell massive
multiple-input multiple-output (MIMO) downlink system. The system considered in this paper is based on two
linear beamforming schemes, that is, maximum ratio transmission (MRT) beamforming and zero-forcing (ZF)
beamforming. What’s more, we use minimum mean square error (MMSE) channel estimation to get imperfect
channel state information (CSI). Compared with the perfect CSI case, both theoretical analysis and simulation
results show that the system performance is different when the imperfect CSI is taken into account.
Performance Analysis of Various Symbol Detection Techniques in Wireless MIMO ...IOSR Journals
Wireless communication is one of the most effective areas of technology development of our time.
Wireless communications today covers a very wide array of applications. In this paper, we study the
performance of general MIMO system, the performance of Zero Forcing (ZF), Linear Least Square Estimator
(LLSE), V-BLAST/ZF, V-BLAST/LLSE of 4x4, 4x6 & 4x8 with 4-QAM & 16-QAM modulation in i i d Rayleigh
fading channel. We seen that SER performance of 4x8 antennas and 4-QAM modulation scheme outperforms
others. Result shows that for higher modulation schemes SER performance degrades as well as SER
performance increases for higher no of receiver antennas
3D METALLIC PLATE LENS ANTENNA BASED BEAMSPACE CHANNEL ESTIMATION TECHNIQUE F...ijwmn
Beamspace channel estimation mechanism for massive MIMO (multiple input multiple output) antenna
system presents a major process to compensate the 5G spectrum challenges caused by the proliferation of
information from mobile devices. However, this estimation is required to ensure the perfect channel state
information (CSI) for lower amount of Radio Frequency (RF) chains for each beam. In addition, phase
shifter (PS) components used in this estimation need high power to select the beam in the desired direction.
To overcome these limitations, in this work, we propose Regular Scanning Support Detection (RSSD)
based channel estimation mechanism. Moreover, we utilise a 3D lens antenna array having metallic plate
and a switch in our model which compensates the limitation of phase shifters. Simulation results show that
the proposed RSSD based channel estimation surpasses traditional technique and SD based channel
estimation even in lower SNR area which is highly desirable in the millimeter wave (mmWave) massive
MIMO systems.
LARGE-SCALE MULTI-USER MIMO APPROACH FOR WIRELESS BACKHAUL BASED HETNETScsandit
In this paper, we consider the optimization of wireless capacity-limited backhaul links in future heterogeneous networks (HetNets). We assume that the HetNet is formed with one macro-cell base station (MBS), which is associated with multiple small-cell base stations (SBSs). It is also assumed both the MBS and the SBSs are equipped with massive arrays, while all mobiles users (macro-cell and small-cell users) have single antenna. For the backhaul links, we propose to use a capacity-aware beamforming scheme at the SBSs and MRC at the MBS. Using particle swarm optimization (PSO), each SBS seeks the optimal transmit weight vectors that maximize the backhaul uplink capacity and the access uplinks signal-to-interference plus noise ratio (SINR). The performance evaluation in terms of the symbol error rate (SER) and the ergodic system capacity shows that the proposed capacity-aware backhaul link scheme achieves similar or better performance than traditional wireless backhaul links and requires considerably less computational complexity.
Spectrum sharing paradigm (SSP) has recently emerged as an attractive solution to provide capital expenditure (CapEx) and operating expenditure (OpEx) savings and to enhance spectrum utilization (SU). However, practical issues concerning the implementation of such paradigm are rarely addressed (e.g., mutual interference, fairness, and mmWave base station density). Therefore, in this paper, we proposed ultra-reliable and proportionally fair hybrid spectrum sharing access strategy that aims to address the aforementioned aspects as a function of coverage probability (CP), average rate distributions (ARD), and the number of mmWave base stations (mBSs). In this strategy, the spectrum is sliced into three parts (exclusive, semi-pooled, and fully pooled). A typical user that belongs to certain operator has the right to occupy a part of the spectrum available in the high and low frequencies (28 and 73 GHz) based on an adaptive multi-state mmWave cell selection scheme (AMMC-S) which associates the user with the tagged mBS that offers a highest SINR to maintain more reliable connection and enrich the user experience. Numerical results show that significant improvement in terms of ARD, CP, fairness among operators, and maintain an acceptable level of mBSs density.
Performance Comparison of Multi-Carrier CDMA Using QPSK and BPSK ModulationIOSR Journals
Abstract: MC-CDMA (Multi Carrier Code Division Multiple Access) plays an important role in modern wireless communications. Modern communication required an efficient spectrum usage and capacity and throughput.MC-CDMA provided the solution of these problems. MIMO refers to links with multiple antennas at the transmitter and receiver side. CDMA systems combined with multiple antennas is a promising technique, beyond 3G and 4G wireless communications. MIMO provides spatial diversity, which mitigates the fading. The usage of multiple antennas can significantly improve the performance of wireless communication system. This work also derives simulation through MATLAB of average bit error rate verses bit energy to noise ratio of multicarrier code division multiple access over Rayleigh channel using QPSK and BPSK modulation additive white Gaussian noise. Keywords: AWGN,BER,MC-CDMA, QPSK Modulation, Rayleigh Channel.
A Potent MIMO–OFDM System Designed for Optimum BER and its Performance Anal...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Overview about MIMO
Contents:
Diversity Definition
Why Diversity
Types of Diversity
Types of combining
MIMO Definition
Why MIMO ?
MIMO Advantages and disadvantages
Applications of MIMO
Computationally Efficient Multi-Antenna Techniques for Multi-User Two-Way Wire...IJECEIAES
In this work, we are interested in implementing, developing and evaluating multi-antenna techniques used for multi-user two-way wireless relay networks that provide a good tradeoff between the computational complexity and performance in terms of symbol error rate and achievable data rate. In particular, a variety of newly multi-antenna techniques is proposed and studied. Some techniques based on orthogonal projection enjoy low computational complexity. However, the performance penalty associated with them is high. Other techniques based on maximum likelihood strategy enjoy high performance, however, they suffer from very high computational complexity. The Other techniques based on randomization strategy provide a good trade-off between the computational complexity and performance where they enjoy low computational complexity with almost the same performance as compared to the techniques based on maximum likelihood strategy.
Performance Analysis of Massive MIMO Downlink System with Imperfect Channel S...IJRES Journal
We investigate the ergodic sum rate and required transmit power of a single-cell massive
multiple-input multiple-output (MIMO) downlink system. The system considered in this paper is based on two
linear beamforming schemes, that is, maximum ratio transmission (MRT) beamforming and zero-forcing (ZF)
beamforming. What’s more, we use minimum mean square error (MMSE) channel estimation to get imperfect
channel state information (CSI). Compared with the perfect CSI case, both theoretical analysis and simulation
results show that the system performance is different when the imperfect CSI is taken into account.
Performance Analysis of Various Symbol Detection Techniques in Wireless MIMO ...IOSR Journals
Wireless communication is one of the most effective areas of technology development of our time.
Wireless communications today covers a very wide array of applications. In this paper, we study the
performance of general MIMO system, the performance of Zero Forcing (ZF), Linear Least Square Estimator
(LLSE), V-BLAST/ZF, V-BLAST/LLSE of 4x4, 4x6 & 4x8 with 4-QAM & 16-QAM modulation in i i d Rayleigh
fading channel. We seen that SER performance of 4x8 antennas and 4-QAM modulation scheme outperforms
others. Result shows that for higher modulation schemes SER performance degrades as well as SER
performance increases for higher no of receiver antennas
3D METALLIC PLATE LENS ANTENNA BASED BEAMSPACE CHANNEL ESTIMATION TECHNIQUE F...ijwmn
Beamspace channel estimation mechanism for massive MIMO (multiple input multiple output) antenna
system presents a major process to compensate the 5G spectrum challenges caused by the proliferation of
information from mobile devices. However, this estimation is required to ensure the perfect channel state
information (CSI) for lower amount of Radio Frequency (RF) chains for each beam. In addition, phase
shifter (PS) components used in this estimation need high power to select the beam in the desired direction.
To overcome these limitations, in this work, we propose Regular Scanning Support Detection (RSSD)
based channel estimation mechanism. Moreover, we utilise a 3D lens antenna array having metallic plate
and a switch in our model which compensates the limitation of phase shifters. Simulation results show that
the proposed RSSD based channel estimation surpasses traditional technique and SD based channel
estimation even in lower SNR area which is highly desirable in the millimeter wave (mmWave) massive
MIMO systems.
LARGE-SCALE MULTI-USER MIMO APPROACH FOR WIRELESS BACKHAUL BASED HETNETScsandit
In this paper, we consider the optimization of wireless capacity-limited backhaul links in future heterogeneous networks (HetNets). We assume that the HetNet is formed with one macro-cell base station (MBS), which is associated with multiple small-cell base stations (SBSs). It is also assumed both the MBS and the SBSs are equipped with massive arrays, while all mobiles users (macro-cell and small-cell users) have single antenna. For the backhaul links, we propose to use a capacity-aware beamforming scheme at the SBSs and MRC at the MBS. Using particle swarm optimization (PSO), each SBS seeks the optimal transmit weight vectors that maximize the backhaul uplink capacity and the access uplinks signal-to-interference plus noise ratio (SINR). The performance evaluation in terms of the symbol error rate (SER) and the ergodic system capacity shows that the proposed capacity-aware backhaul link scheme achieves similar or better performance than traditional wireless backhaul links and requires considerably less computational complexity.
Spectrum sharing paradigm (SSP) has recently emerged as an attractive solution to provide capital expenditure (CapEx) and operating expenditure (OpEx) savings and to enhance spectrum utilization (SU). However, practical issues concerning the implementation of such paradigm are rarely addressed (e.g., mutual interference, fairness, and mmWave base station density). Therefore, in this paper, we proposed ultra-reliable and proportionally fair hybrid spectrum sharing access strategy that aims to address the aforementioned aspects as a function of coverage probability (CP), average rate distributions (ARD), and the number of mmWave base stations (mBSs). In this strategy, the spectrum is sliced into three parts (exclusive, semi-pooled, and fully pooled). A typical user that belongs to certain operator has the right to occupy a part of the spectrum available in the high and low frequencies (28 and 73 GHz) based on an adaptive multi-state mmWave cell selection scheme (AMMC-S) which associates the user with the tagged mBS that offers a highest SINR to maintain more reliable connection and enrich the user experience. Numerical results show that significant improvement in terms of ARD, CP, fairness among operators, and maintain an acceptable level of mBSs density.
Performance Comparison of Multi-Carrier CDMA Using QPSK and BPSK ModulationIOSR Journals
Abstract: MC-CDMA (Multi Carrier Code Division Multiple Access) plays an important role in modern wireless communications. Modern communication required an efficient spectrum usage and capacity and throughput.MC-CDMA provided the solution of these problems. MIMO refers to links with multiple antennas at the transmitter and receiver side. CDMA systems combined with multiple antennas is a promising technique, beyond 3G and 4G wireless communications. MIMO provides spatial diversity, which mitigates the fading. The usage of multiple antennas can significantly improve the performance of wireless communication system. This work also derives simulation through MATLAB of average bit error rate verses bit energy to noise ratio of multicarrier code division multiple access over Rayleigh channel using QPSK and BPSK modulation additive white Gaussian noise. Keywords: AWGN,BER,MC-CDMA, QPSK Modulation, Rayleigh Channel.
Error Rate Analysis of MIMO System Using V Blast Detection Technique in Fadin...IJERA Editor
Wireless communication system with multi- antenna arrays has been a field of intensive analysis on the last years. The appliance of multiple sending antennas and Receiving Antennas either side will considerably enhance the data rate and rate. The review of the performance limitations of MIMO system becomes vital since it will provide lot ideas in understanding and planning the important life MIMO systems. Vertical Bell Laboratories layered space Time (V-BLAST). The thought behind Multiple Input and Multiple Output system is that the signals on the transmitter antennas at one finish and also the receiver antennas at the opposite finish are correlative in such how that the performance (Bit Error Rate or BER) or the info rate (bits/sec) of the wireless communication system for every MIMO subscriber are improved. During this paper we tend to are proposing a technique that evaluates the performance of V-BLAST MIMO system in several thought of Rayleigh attenuation surroundings to urge higher performance of the system. In V- BLAST MIMO system a number of linear detection techniques will be used for interference cancellation. At this point we are using MMSE-IC for the same. Our expected system provide higher error rate performance with the used of matched filter at receiver aspect .The projected system compared within the presence of AWGN. Now matched filter applied on V- BLAST MIMO with MMSE-IC system in fading diversity surroundings.
Bit Error Rate Performance of MIMO Spatial Multiplexing with MPSK Modulation ...ijsrd.com
Wireless communication is one of the most effective areas of technology development of our time. Wireless communications today covers a very wide array of applications. In this, we study the performance of general MIMO system, the general V-BLAST architecture with MPSK Modulation in Rayleigh fading channels. Based on bit error rate, we show the performance of the 2x2 schemes with MPSK Modulation in noisy environment. We also show the bit error rate performance of 2x2, 3x3, 4x4 systems with BPSK modulation. We see that the bit error rate performance of 2x2 systems with QPSK modulation gives us the best performance among other schemes analysed here.
Design and analysis of mimo system for uwb communicationijwmn
Multiple transmit and receive antennas are used MIMO system. The system creates parallel MIMO
subchannels to transmit independent streams of data under the appropriate channel conditions. Similarly,
Ultrawideband (UWB) communication has attracted great interest for various applications in recent days.
Spatially multiplexed (SM) multiple-input multiple-output (MIMO) systems gains the spectral efficiency as
well as high data rates without consuming additional power, bandwidth or time slots. In this paper, we
extend the concept of MIMO to UWB systems. The correlated channel for such purpose is considered and
the performance has been analyzed for spatial multiplexing SM-UWB-MIMO system which is required for
estimation. The system performance substantially degrades in the presence of high values of spatial
correlation. To avoid the degradation of such system, it has been designed for virtual UWB-MIMO Time
Reversal (TR) system, so that it is not affected by the transmit correlation. Another novel method to reduce
the effect of correlation has been chosen by taking the Eigen value of the channel matrix for the
computation of the system performance. The result shows its performance.
Massive multiple-input multiple-output (MIMO) systems are considered a promising solution to minimize multiuser interference (MUI) based on simple precoding techniques with a massive antenna array at a base station (BS). This paper presents a novel approach of beam division multiple access (BDMA) which BS transmit signals to multiusers at the same time via different beams based on hybrid beamforming and user-beam schedule. With the selection of users whose steering vectors are orthogonal to each other, interference between users is significantly improved. While, the efficiency spectrum of proposed scheme reaches to the performance of fully digital solutions, the multiuser interference is considerably reduced.
MIMO Channel Estimation Using the LS and MMSE AlgorithmIOSRJECE
Wireless Communication Technology has developed over the past few yearsfor other objectives.The Multiple InputMultiple Output (MIMO) is one of techniques that is used to enhancethe data rates, in which multiple antennas are employed both the transmitter and receiver. Multiple signals are transmitted from different antennas at the transmitter using the same frequency and separated space. Various channel estimation techniques are employed in order to judge the physical effects of the medium present. In this paper, we analyze and implementvarious estimation techniques for MIMO Systems such as Least Squares (LS), Minimum Mean Square Error (MMSE),these techniques are therefore compared to effectively estimate the channel in MIMO System. The results demonstrate that SNR required to support different values of bit error rate varies depending on different low correlation between the transmitting and the receiving antennas .In addition, it is illustrated that when the number of transmitter and receiver antennas increases, the performance of TBCE schemes significantly improves. The Same behavior isalso observed for MIMO system. Performance of both MMSE and LSestimation are the same for allkinds of modulation at small value of SNR but the more we increase the SNR value the more performance gap goes on increasing.
Multiuser MIMO Gaussian Channels: Capacity Region and DualityShristi Pradhan
In this paper, I present the MIMO channel for single user case, discuss the decomposition of MIMO into parallel independent channels, and estimate the MIMO channel capacity. Then, I discuss on computation of capacity region for multiuser MIMO broadcast and multiple access channel and plot capacity regions for two users case. I conclude by showing the duality relationship between the multiple access and broadcast channel and show its significance for numerical standpoint.
An approach to control inter cellular interference using load matrix in multi...eSAT Journals
Abstract
This paper deals with reduction of inter cellular interference in Multi-carrier communication systems. In the past, Load Matrix(LM) is proposed to allocate power to different users in a network based upon Signal to noise plus interference ratio (SNIR) so as to reduce inter cellular interference and is observed for single carrier systems. In Multi carrier systems the SNIR is affected distinctly in each carrier thus a single SNIR for power allocation is not optimal. In this paper, to obtain the optimization of power allocation in Multi-Carrier system, Load Matrix coding with bifurcated SNIR (LM-BFSNIR) is proposed. Using this approach it is observed that inter cellular interference is reduced better when compared to a single carrier system evaluated over a 3GPP-LTE standard.
Keywords−Power allocation, Inter cellular interference, Multi-Carrier mobile Communication system.
Ber analysis of 2x2 mimo spatial multiplexing under awgn and rician channels ...ijwmn
Multiple-input–multiple-output (MIMO) wireless systems use multiple antennas at transmitting and
receiving end to offer improved capacity and data rate over single antenna systems in multipath channels.
In this paper we have investigated the Spatial Multiplexing technique of MIMO systems. Here different
fading channels like AWGN and Rician are used for analysis purpose. Moreover we analyzed the technique
using high level modulations (i.e. M-PSK for different values of M). Detection algorithms used are Zero-
Forcing and Minimum mean square estimator. Performance is analyzed in terms of BER (bit error rate) vs.
SNR (signal to noise ratio).
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
BER Performance of MU-MIMO System using Dirty Paper CodingIJEEE
In this paper Dirty Paper Coding for communication system is implemented. MIMO application that involves devices such as cell phones, pocket PCs require closely spaced antenna, which suffers from mutual coupling among antennas and high spatial correlation for signals. DPC is used for compensating the degradation due to correlation and mutual coupling.
In this paper, three beamforming design are considered for multi user MIMO system. First, transmit
beamformers are fixed and the receive (RX) beamformers are calculated. Transmit beamformer (TX-BF)is
projectedas a null space of appropriate channels. It reduces the interference for each user. Then the receiver
beamformer is determined which maximize the SNR. This beamforming design provides less computation time.
The second case is joint TX and RX beamformer for SNR maximization. In this transmitter and receiver
beamformer are calculated using extended alternating optimization (EAO) algorithm. The third one is joint
transmitter and receiver beamforming for SNR and SINR maximization using EAO algorithm. This algorithm
provides better error performance and sum rate performance. All the design cases are simulated by using
standard multipath channel model. Our simulation results illustrate that compared to the least square design and
zero forcing design, the joint TX and RX beamforming design using EAO algorithm provides faster
beamforming and improved error performance and sum rate.
Application of multi antenna technologies in cellular mobile communications
paperVTCFall2009
1. Vector Precoding Scheme
for Multi-user MIMO Systems
Yogesh Nijsure, Charan Litchfield, Yifan Chen and Predrag B. Rapajic
Medway School of Engineering,
the University of Greenwich, UK,
Email: {y.nijsure, c.litchfield, y.chen, p.rapajic}@gre.ac.uk
Abstract— In this paper, the performance of Vector Precoding
in multiple input multiple output broadcast channels(MIMO BC)
is investigated and compared with other channel decomposition
techniques utilized for implementing zero forcing (ZF) precod-
ing. It is a known result that ZF precoding requires pseudo
inversion of the channel matrix, where this operation is only
optimum when the transmitter power is unconstrained. The
problem when the transmitter is subject to average or maximum
power constraints is well known, where results published have
indicated that ZF precoding approaches the maximum capacity
bound if the dimensionality of the system is greater than the
number of transmitter antennas. A vector precoding technique
for MIMO BC channels is investigated in this paper where
pseudo inversion is circumvented by employing joint co-operation
between transmitter and receiver for all users. This technique
adopts a time scheduling approach to service the users which
facilitates decentralized multi-user detection at the receiver. This
approach yeilds an improvement to the bit error rate probability
by approximately an order of magnitude as compared to the ZF
approach utilizing other channel decomposition techniques. The
scheme also enables an increase in the capacity of the MIMO BC,
with less computational complexity as compared to the techniques
employing Moore-Penrose pseudo inverse.
I. INTRODUCTION
Precoding uses the same idea as frequency equalization,
except that the fading is inverted at the transmitter instead of
at the receiver. The technique requires the transmitter to have
knowledge of the sub-channel flat fading gains, which must be
obtained through estimation. When the receiver has multiple
antennas, the transmit beamforming cannot simultaneously
maximize the signal level at all of the receive antenna and pre-
coding is used. Note that precoding requires knowledge of the
channel state information (CSI) at the transmitter. Precoding
is quite common on wireline multi-carrier systems like high
bit rate digital subscriber lines.There are two main problems
with precoding in the wireless setting. First, precoding is
basically channel inversion, and we know that inversion is
not power efficient in fading channels. In particular an infinite
amount of power is needed for channel inversion on a Rayleigh
fading channel. The other problem with precoding is the need
for accurate channel estimates at the transmitter, which are
difficult to obtain in a rapidly fading channel.
In multiuser communication scenario, diversity can be ex-
ploited through making appropriate choice among users with
independently faded channels [2]. In the literature, multiuser
scheduling has been considered in the context of channel
allocation for a space division multiple access/time division
multiple access network e.g.,[1],[3],[11] but mainly with the
downlink and the assumptions that users are equipped with
only one antenna or transmit only one data stream. As in-
dicated in [15] this approach raises two potential concerns.
First, a globally optimal allocation requires a thorough search
of all possible choices, and suboptimal or heuristic alternatives
induce complexity versus performance tradeoffs. Second, the
physical layer details are largely neglected: either the compati-
bility metric depends solely on the channel and is independent
of the underlying transceiver structures; or a conservative view
is taken that treats multiuser interference(MUI) as background
noise.
In this paper we adopt the vector precoding scheme for
multi-user multiple input multiple output (MU-MIMO) system
and adopt a time scheduling approach to service the users. The
key contributions of this paper are:
1) Developing a joint-transmitter receiver design for imple-
menting vector precoding for MU-MIMO systems.
2) Evaluation of multi-user channel capacity and Bit-error
rate performance.
The proposed research aims at addressing the issue of channel
inversion required for pre-coding and mitigation of multi-user
interference in MIMO systems. In this first section of this
paper we provide an introduction to the concept of vector
precoding for MIMO systems. In section II we describe the
proposed system model used in this paper. In section III we
analyze how vector precoding is used for our system. In
section IV we develop a multi-user MIMO system. In section
V we provide discussion on results. At the end of this paper
we provide a set of conclusions in section VI.
II. PROBLEM FORMULATION
This proposed scheme for precoding will adopt a joint effort
at both the transmitter and a receiver. This will use a Zero
forcing (ZF) like approach in order to mitigate multiuser inter-
ference. Let Hj be the jth
user subchannel and Xibe the user
i transmit vector. The fundamental idea of ZF solution[7],[13]
is that interference is removed by forcing Hj · Xi = 0 for i
not equal to j, which means that all the other users besides
the user of interest will be forced to have a zero contribution
by adopting this scheme, results in a constraint that the total
number of transmit antennas must always be greater than
number of receiver antennas. as in [16]. The transmitter matrix
for user j will not interfere with the signal at the output of the
2. Fig. 1. vector precoding
receivers for other users if it lies in the null space of the above
given channel vector. Let UjΣVj
H
represent the singular value
decomposition of the channel under consideration. where U
and V represent the left and right singular vectors respectively
and Σ represents the matrix of the singular values of the
decomposed channel. Let the received vector be represented
by Y , the channel matrix by H , the transmitted vector by
˜X. and ϑ represent the additive white gaussian noise and (.)H
represents the Hermitian transpose.
As indicated in Fig.1, the classical method utilizing the
channel decomposition approach can be described as follows.
The received signal can be represented as
Y = HX + ϑ.
Forming the singular value decomposition of the channel
Y = UΣV H
X + ϑ
By utilizing the the matrix of right singular vectors V of the
channel,pre-processing of the signal is achieved and matrix of
transmit vectors is formed
Let X = V ˜X
Y = UΣV H
V ˜X + ϑ
The received signal is partially whitened and post processing
at the receiver end is achieved by utilizing the matrix of left
singular vectors U.
UH
Y = UH
UΣ ˜X + UH
ϑ
Thus the received signal after post- processing can be repre-
sented as:
˜Y = Σ−1
Σ ˜X + Σ−1
UH
ϑ
˜Y = ˜X + υ
Extending the same concept to multi-user MIMO case:
Hj
˜V
(0)
j = [U
(1)
j U
(0)
j ]Σ[V
(0)
j V
(1)
j ] (1)
The transmitted signal X is subject to additive white
Gaussian noise (AWGN) n, and multipath propagation AWGN
channel H. The MU-MIMO system consists of nt transmitting
and nr receiving antennas. The channel matrix H is a (nr ×nt)
complex matrix, the received vector y is a nr dimensional
complex BPSK signal vector, the transmitted signal x is a nt
dimensional vector and n is the nt dimensional noise vector.
A BPSK modulation scheme is used in order to eliminate
modulation gain and simply show the performance advantage
of MU-MIMO. More advanced modulation scheme is expected
to offer extra gain in data rates but at the same time an
increased complexity.
III. MULTI-USER PRECODING
Multi user multiple-input multiple-output (MIMO) systems
provide high capacity with the benefits of space division
multiple access. The channel state information at the base
station (BS) or access point (AP) is very important since
it allows joint processing of all users signals which results
in a significant performance improvement and increased data
rates [1]. If the channel state information is available at the
BS/AP, it can be used to efficiently eliminate or suppress multi-
user interference (MUI) by beamforming or by using dirty-
paper codes. The precoding also allows us to perform most
of the complex processing at the BS/AP which results in a
simplification of users terminals. Linear precoding techniques
have an advantage in terms of computational complexity. [4]
Non-linear techniques have a higher computational complexity
and require some signaling overhead but can provide a better
performance than linear techniques.
The basic idea behind this solution is to utilize the right
singular vectors of the channel matrix in order to form the
precoding matrix.
Thus an optimal precoding matrix can be formed such that
all MUI is zero by choosing a precoding matrix Fi that lies
in the null space of the other users channel matrices. Thereby,
a MU MIMO downlink channel is decomposed into multiple
parallel independent single user MIMO channels [16]. Thus
we can define the zero MUI constraint forces Fi to lie in
the null space of Hi. From the singular value decomposition
(SVD) of Hi whose rank is Li. The proposed system chooses
the last right singular vectors Nt − Li where Nt is number of
transmitter antennas.
Thus the equivalent channel of user i after eliminating the
multi-user interference is identified. Each of these equivalent
single user MIMO channels has the same properties as a
conventional single user MIMO channel. As mentioned before,
by applying block diagonalization on the combined channel
matrix of all users the MU MIMO channel can be transformed
into a set of parallel single-user MIMO channels. However,
there is a capacity loss due to the nulling of overlapping
subspaces of different users. In [13], the authors propose a
successive precoding algorithm in order to define a simplified
solution of the power control problem. By allowing a certain
amount of interference, this algorithm reduces the capacity
loss due to the subspace nulling. In short, first calculate the
maximum capacity that an individual user can achieve. The
basic ideology behind this solution is to utilize the right
singular vectors of the channel matrix in order to form the
precoding matrix.
F = [F1F2F3....FK] ⊆ CNT ×R
(2)
3. Thus an optimal precoding matrix can be formed such that all
MUI is zero by choosing a precoding matrix Fi that lies in
the null space of the other users channel matrices. Thereby,
a MU MIMO downlink channel is decomposed into multiple
parallel independent single user MIMO channels [14], [12].
˜Hi = [HT
1 ....HT
i−1HT
i+1....HT
K]T
(3)
the zero MUI constraint forces Fi to lie in the null space of Hi.
From the singular value decomposition (SVD) of Hi whose
rank is Li. The proposed system chooses the last right singular
vectors MtLi where Mt is number of transmitter antennas.
Hi
˜V
(0)
i = UiΣ[V
(1)
i V
(0)
i ]H
(4)
IV. MULTI-USER MIMO
The proposed solution aims at identifying the user with
the smallest difference between its maximum capacity and its
capacity and generate its precoding matrix such that it lies
in the null space of the remaining users channel matrices.
Thereafter the new combined channel matrix without this users
channel matrix is formed. The proposed system repeats these
steps until the combined channel matrix is empty. The order
of the users in which they are precoded using zero forcing
precoding is the reverse of the order in which their precoding
matrices are generated. The capacity of a MIMO closed-loop
system, that is, perfect CSI at the transmitter, with worst-
case noise under a trace constraint (or worst-case interference)
equals the capacity of a MIMO open-loop system, that is,
no CSI at the transmitter, with white noise, that is, without
interference. The structure of the equivalent system is a single-
user MIMO system with uncorrelated noise and without CSI at
the transmitter [3]. The worst-case noise directions correspond
with the left eigenvectors of the channel matrix H. The optimal
transmit directions correspond with the right eigenvectors of
the channel matrix H. Both are independent of each other. The
power allocation is then the well-known waterfilling solution.
At the receiver each user utilizes the left singular matrix rows
or matrix U to decode the data that was transmitted. Thus the
signal processing at the user end has to be decentralized to
facilitate the successful operation of the proposed solution. It
is evident that a particular user has no idea about the channel
characteristics of different users in the network and a co-
operative scheme between the users cannot be implemented
for conveying the information about the left singular matrices
in between the users for decoding purposes. This is the issue
with the proposed system [6]. The computational complexity
involved in this SVD type of approach is O(nk2
) as compared
to the ZF approach involving Moore-Penrose pseudo inverse
has a greater computational complexity of O(n3
).
A. Performance analysis
The capacity of MU - MIMO downlinks is intimately
connected with a result as indicated in [6] called ”writing on
dirty paper” [6], which is briefly summarized here suppose X
represents a transmitted signal,W and Z are additive white
noise terms, so that the received signal is Y = X + W + Z.It
is shown in [6] that if W is known deterministically to the
transmitter , then the capacity of the communication channel
is same as a channel with only the second interference term:
Y = X + Z. Regardless of whether or not the receiver knows
W and independent of the statistics of W. When the users are
known at the transmitter , SDMA can be employed to increase
capacity [3]. In particular, the capacity of the channel for user
j is indicated as in [15]
Cj = maxXj log2 |I + (σ2
nI + Hj
˜Xj
˜Xj
∗
H∗
j )−1
HjXjX∗
j H∗
j |
(5)
where Rnj
is the covariance of the noise vector. The capacity
is thus the function of not only what modulation matrix
is chosen for the particular user of interest, but also those
chosen for all other co-channel users as well [9]. Viewing the
problem entirely form the perspective of receiver j , capacity
is maximised when, Hj
˜Xj = 0 Or in other words , when the
transmit matrix ˜Xj for all other then j lies in null space of
Hj. If this is done , then the capacity of user j is equal to the
waterfilling capacity of the channel matrix Hj [10]. note that
nt ≥ nr is necessary condition for achieving a requirement
not imposed in the blind transmitter case.
For the purpose of simulations the comparison was made
between the proposed vector precoding scheme and the zero
forcing approach. The systems considered for the simulation
were full rank systems. As seen from the simulations results
the proposed vector precoding scheme outperforms the zero
forcing precoding method even at significantly lower values
of SNR. The main reason for this can be due to the fact that
in traditional zero forcing approach the channel needs to be
inverted at the receiver and under such circumstances spectral
nulls are introduced in the process of reception. In the vector
precoding approach the channel doesnt need to be inverted
under the assumption that the transmitter has complete channel
state information. The vector precoding approach exploits the
orthogonal nature of the right singular matrix. In the case of a
multi-user MIMO system the proposed method adopts a time
division multiple access scheme in which each user is serviced
at a time. In this way the decentralization of users is achieved.
The proposed system is compared with different configurations
in MIMO adopting a zero forcing like approach. The problem
with sum capacity maximization in a multi-user channel is
that such an approach may result in one or two ”strong”
users large taking a dominant share of the available power,
potentially leaving weak users with little or no throughput
[7],[4]. Consequently, in practice, the dual problem is often of
more interest: i.e., minimize power output at the transmitter
subject to achieving a desired arbitrary rate for each user[4].
Assume Hj = AjBJ , where Aj is nR × Lj, Bj is Lj × nT ,
and Lj ≤ nRj
. Here , the condition HiXj = 0,i = j,
necessary to make the system block-diagonal, is equivalent
to BiMj = 0;i = j. Thus , we define the matrix ˜Bj
˜Bj = [BT
1 ...BT
j−1BT
j+1...BT
K]T
(6)
Let the SVD of
˜Bj = ˜UBj
˜ΣBj
[ ˜VBj
(1)
˜VBj
(0)
]∗
(7)
4. Fig. 2. error rate
, where ˜VBj
(0)
, corresponds to the right null space of ˜Bj.
The optimal modulation matrix for user j, subject to the
constraint that the inter-user interference is zero , is now
of the form ˜VBj
(0)
Xj,for some choice of transmit vectorsXj.
Substituting (6) and (7) in (5),the system capacity of the
approach in this case is thus of the form:
C = maxXj
,j=1,K
K
j=1
log2|I+1/σ2
nAjBj
˜VBj
XjX ∗
j
˜VBj
B∗
j A∗
j |
(8)
B. Algorithm
1) For j = 1,....K:
2) Compute ˜Vj
0
, the right null space of ˜HJ . Information
of the active users at the receiver side
3) Compute SVD
Hj
˜
V
(0)
j = Uj ·
Σ 0
0 0
· [V
(1)
j V
(0)
j ]∗
(9)
4) Use water filling on the diagonal elements of Σ to
determine the optimal power loading matrix Λ under
a total power constraint P
5) Xs = [ ˜V
(0)
1
˜V
(1)
1
˜V
(0)
2
˜V
(1)
2 ...... ˜V
(0)
k
˜V
(1)
k ]Λ1/2
6) Evaluate the received vector for the for the current sub-
channel conditions.
7) Post Processing: premultiply by the left matrix of left
singular vectors as obtained from SVD decomposition
of the current channel estimate.
8) Evaluate the bit error rate for the user of interest.
9) Repeat the process for each user and each user time slot.
10) End of algorithm.
At higher SNRs, the relatively small gap between channels
with and without channel information at the transmitter is suf-
ficiently small. However, this assumes that the channel is full
rank. When the channel is rank deficient, the gaps are larger,
and having complete, or even only partial channel information
Fig. 3. ergodic capacity
available can be advantageous. Multi-user capacity can be
taken to have different meanings. [8]It is possible to consider
the capacity of one particular user in the context of a system,
or to consider the sum capacity of all users in the system.
Under a single power constraint, it is possible to achieve a
variety of different combinations of rates for different users
by allocating resources differently to different users.
V. DISCUSSION ON RESULTS
Figure 2 indicates BER of a simple MU-MIMO system with
BPSK modulation over a channel,by adopting zero-forcing
precoding and geometric mean decomposition methods is
presented along with the comparison with our vector precoding
approach. Figure 3 shows the capacity of a MIMO system
is presented with a comparison of the ergodic capacity for
the transmitter with uniform power allocation ,transmitter
with CSI and the multiuser MIMO case with the proposed
approach. The joint transmitter and receiver scheme for im-
plementing the Multi-user downlink vector precoding scheme
was demonstrated in this paper. The simulation results indicate
a capacity improvement as well as the improvement in the
bit error rate performance compared with the zero forcing
approach. In the vector precoding approach the channel doesnt
need to be inverted under the assumption that the transmitter
has complete channel state information. Results show that
designing the precoders based on the standard pseudo-inverse
is optimal under the assumption of a total power constraint.
However, when more complex power constraints are involved,
e.g., individual total per antenna power constraints, the pseudo-
inverse is no longer sufficient and vector precoding provides
better performance. In general, finding the optimal inverse is
a difficult optimization problem which is highly dependent
on the specific design criterion. Such constraints may be
important in modern systems where multiple base stations,
each with multiple antennae, cooperatively transmit data to
the same users.
5. VI. CONCLUSION
In this paper we demonstrated the joint transmitter-receiver
design for multi-user precoding scenario. The BER perfor-
mance for such a system was evaluated and simulation results
suggest an improvement in BER performance of the system as
compared to the transmitter side precoding alone. This can be
mainly attributed to the fact that the proposed solution avoids
channel inversion usually required in the precoding process.
The capacity results also indicate a better mitigation of MUI in
the case of MIMO system. Thus, precoding with generalized
power constraints is an important problem in modern com-
munication systems and there are still many open questions.
More advanced linear precoding schemes should be addressed.
For example, it is well known that in low SNR conditions,
and under channel uncertainty, regularizing the pseudo-inverse
can considerably improve the performance. It is interesting to
examine this property in the context of generalized inverses.
Future work should also address the implications of the results
on non-linear schemes such as ZF DPC precoding. Another
extension of this work is to consider the well known duality
between receive and transmit processing. ZF decoding using
the pseudo-inverse (the decorrelator) is probably the most
common decoding algorithm. The results suggest that vector
precoding may outperform it under uncertainty conditions.
REFERENCES
[1] E. Telatar, ”Capacity of Multi-antenna Gaussian Channels”, European
Trans. Telecomm. ETT, vol. 10, pp. 585–596, Nov/Dec 1999.
[2] G. J. Foschini. ”Layered space-time architecture for wireless communi-
cation in fading environments when using multielement antennas.” Bell
Labs Techn. J., pages 4159, Autumn 1996.
[3] H. Harashima, H. Miyakawa. ”Matched-transmission technique for chan-
nels with intersymbol interference”, IEEE Trans. Comm., pp. 774780,
Aug. 1972.
[4] M. Tomlinson.”New automatic equaliser employing modulo arithmetic”,
Electronics Letters, pp. 138139, March 1971.
[5] S.Boyd S. Vishwanath and A. J. Goldsmith. ”On the worst-case capacity
of multi-antenna channels”. 2002. Submitted to Int. Conf. Commun.
[6] M. H. M. Costa, ”Writing on dirty paper,” IEEE Trans. Inform. Theory,
vol. 29, no. 3, pp. 439441, May 1983.
[7] G. Caire and S. Shamai, ”On the achievable throughput of a multiantenna
Gaussian broadcast channel”, IEEE Trans. Inform. Theory, vol. 49, no.
7, pp. 16911706, Jul. 2003
[8] H. Weingarten, Y. Steinberg, and S. Shamai, ”The capacity region of the
Gaussian multiple-input multiple-output broadcast channel,” IEEE Trans.
Inform. Theory, vol. 52, no. 9, pp. 39363964, Sep. 2006.
[9] S. Vishwanath, N. Jindal, and A. Goldsmith, ”Duality, achievable rates,
and sum-rate capacity of Gaussian MIMO broadcast‘channels,” IEEE
Trans. Inform. Theory, vol. 49, no. 10, pp. 26582668, Oct. 2003.
[10] P. Viswanath and D. N. C. Tse, ”Sum capacity of the vector Gaussian
broadcast channel and uplink-downlink duality,” IEEE Trans. Inform.
Theory, vol. 49, no. 8, pp. 19121921, Aug. 2003.
[11] W. Yu and J. M. Cioffi, ”Sum capacity of Gaussian vector broadcast
channels,” IEEE Trans. Inform. Theory, vol. 50, no. 9, pp. 18751892,
Sep. 2004.
[12] G. Caire and S. Shamai, ”On the Achievable Throughput of a Multi-
Antenna Gaussian Broadcast Channel,” IEEE Transactions on Information
Theory, vol. 49, no. 7, pp. 16911706, July 2003.
[13] H. Viswanathan, S. Venkatesan, and H. Huang, ”Downlink Capacity
Evaluation of Cellular Networks with Known-Interference Cancellation,”
IEEE Journal on Selected Areas in Communications, vol. 21, no. 5, pp.
802811, June 2003.
[14] L. U. Choi and R. D. Murch, ”A transmit preprocessing technique
for multiuser MIMO systems using a decomposition approach,” IEEE
Transactions on Wireless Communications, vol. 3, no. 1, pp. 2024,
January 2004.
[15] Q. H. Spencer, A. L. Swindlehurst, and M. Haardt, ”Zeroforcing methods
for downlink spatial multiplexing in Multiuser MIMO channels,”.IEEE
Transactions on Signal Processing, vol. 52, no. 2, pp. 461471, February
2004.
[16] Feng Liu, L.Jiang,Chean He, ”MMSE vector precoding with precoding
with joint transmitter andreceiver design for MIMO systems” IEEE
Transactions on Signal Processing, 2823-2833,7 June 2007.