Weighted Sum Rate Optimization for Downlink Multiuser MIMO Systems with per Antenna Power Constraint: Downlink-Uplink Duality Approach
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This document proposes a downlink-uplink duality approach to solve the weighted sum rate maximization problem for multiuser MIMO systems with per antenna power constraints. The duality is established by modifying the input covariance matrix of the dual uplink problem and formulating the noise covariance matrix as a fixed point function. Simulation results show that the proposed duality-based solution utilizes less total base station power than existing algorithms.
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![Weighted Sum Rate Optimization for Downlink Multiuser
MIMO Systems with per Antenna Power Constraint:
Downlink-Uplink Duality Approach
Tadilo Endeshaw Bogale, Luc Vandendorpe
ICTEAM Institute, Place du Levant, 2, 1348 Louvain-la-Neuve
{tadilo.bogale, luc.vandendorpe}@uclouvain.be
ABSTRACT
This work proposes downlink-uplink duality approach to solve weighted sum rate
maximization problem for multiuser MIMO systems. The duality is established by
modifying the input covariance matrix of the dual uplink problem, and formulating
the noise covariance matrix of the uplink channel as a fixed point function. In our
simulation results, we have observed that the proposed duality based solution
utilizes less total BS power than that of existing algorithms.
PROBLEM FORMULATION
PROPSED SOLUTION CONTINUED
In this work we propose new duality based iterative solution to solve per antenna power constrained WSR
maximization problem. For our simulation setup, we have observed that the proposed duality based solution
requires less total BS power compared to the existing approach.
TWO STEP PROPOSED DUALITY SOLUTION
Difficult to ensure Per ant power const
The per antenna power constraint issue of Algorithm I at step 4 can be resolved as follows
SYSTEM MODEL
CONCLUSIONS
REFERENCES
[1] T. E. Bogale and L.Vandendorpe,”Weighted sum rate optimization for downlink multiuser MIMO
coordinated base station systems: Centralized and distributed algorithms,” IEEE Tran. Sig. Proc., Dec. 2011.
[2] S.Shi, M. Schubert and H. Boche, “Per antenna power constrained rate optimization for multiyser MIMO
systems,” ITG WSA, Berlin, Germany, 26 – 27 Feb., 2008, pp 270 -- 277
SIMULATION RESULTS
IMPROVING THE CONVERGENCE SPEED OF ALGORITHM I](https://image.slidesharecdn.com/120137poster-140612100020-phpapp01/85/Weighted-Sum-Rate-Optimization-for-Downlink-Multiuser-MIMO-Systems-with-per-Antenna-Power-Constraint-Downlink-Uplink-Duality-Approach-1-320.jpg)
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This document presents a novel approach to designing a broadband full wave rectenna for wireless energy transfer at 2.45 GHz. The rectenna consists of a center shorted dual edge feed microstrip patch antenna and a two diode full wave rectifier. Simulation and experimental results show that the proposed rectenna provides higher RF to DC conversion efficiency than a similar design using a half wave rectifier. A dual feed antenna is used to provide differential voltages at its two feed points, which the full wave rectifier utilizes with its two diodes to convert both half cycles of the incoming AC signal into DC power. The optimized rectenna design is tested and shown to agree with theoretical simulations.
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This document outlines a presentation on MSE duality under imperfect channel state information. It establishes three types of MSE duality - sum MSE duality, user-wise MSE duality, and symbol-wise MSE duality. As an application example, it examines a robust sum MSE minimization problem. An alternating optimization technique is proposed to solve this problem by decomposing precoders and decoders and formulating the power allocation as a geometric program at each step. Simulation results show the proposed robust design outperforms a non-robust design and that increased antenna correlation worsens sum AMSE.
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This document announces a call for papers for the IEEE PIMRC 2015 conference in Hong Kong from August 30 to September 2, 2015. It will include technical sessions, tutorials, workshops, and panels on wireless communications, networks, services, and applications. The deadline for paper submissions is April 30, 2015. It also provides details on one of the tutorials that will be presented on advanced air interface techniques for 5G networks. The tutorial will discuss key 5G technologies including distributed antenna systems, massive MIMO, millimeter wave communications, and small cell networks. It will analyze the technical aspects and challenges of 5G and present emerging research opportunities in this area. The tutorial presenters and their brief biographies are also included.
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The document compares digital and hybrid analog-digital beamforming for multiuser massive MIMO systems. It describes the system model and problem formulation. Digital beamforming requires many RF chains and ADCs which is expensive for massive MIMO. Hybrid beamforming uses limited RF chains by employing analog beamforming at the transmitter with phase shifters. The document proposes a hybrid beamforming algorithm that minimizes the mean square error between the estimated signals of digital and hybrid beamforming. Simulation results show the proposed hybrid approach achieves similar performance as digital beamforming using fewer RF chains and phase shifters. It concludes hybrid beamforming provides significant savings in hardware complexity over digital beamforming for multiuser massive MIMO systems.
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Presentation style iswcs2014
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It802 d mobilecommunicationspart3
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A DISTRIBUTED FAULT-TOLERANT TOPOLOGY CONTROL ALGORITHM FOR HETEROGENEOUS WIR...
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
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2013 ictc toha_slide
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International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Pimrc2008 Presentation
This is the ppt file that I used to give my talk at PIMRC 2008, that was held in Cannes on September 2008
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Security of wireless networks with rechargeable energy harvesting transmitters
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International Conference on IEEE ICT Convergence 2013
This paper proposes a cooperative power allocation algorithm called CoopWF for small cell networks. CoopWF uses block diagonalization precoding to cancel interference between users. The algorithm is designed for small cell networks like femtocells, metrocells, and picocells. Simulation results show CoopWF provides better average capacity compared to existing algorithms, improving capacity by up to 0.4 Mbps for networks with 3 cooperative small cells in low SNR conditions.
Java a resource allocation scheme for scalable video multicast in wi max rel...
This paper proposes a resource allocation scheme to support scalable video multicast for WiMAX relay networks. It presents a greedy weighted algorithm (GWA) that intelligently allocates bandwidth to maximize network throughput or number of satisfied users. To improve GWA, the paper extends it to a bounded greedy weighted algorithm (BGWA) that guarantees performance is at least 1/ρ times optimal, where ρ is a finite value greater than 1. Simulations show BGWA effectively achieves different performance objectives based on parameter settings.
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A Distributed Approach to Maximum Power Point Tracking for Photovoltaic Sub-M...
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IEEE 2014 MATLAB EEE PROJECT LIST
This document provides information about Vision Solutions, an engineering consulting firm with offices in Hyderabad, Vijayawada, and Guntur, India. It lists 13 IEEE papers on topics related to power electronics, including abstracts. Vision Solutions provides services aligned with IEEE standards and can be contacted by phone, email, or through their website for engineering consulting.
A hybrid artificial neural network-genetic algorithm for load shedding
This paper proposes the method of applying Artificial Neural Network (ANN) with Back Propagation (BP) algorithm in combination or hybrid with Genetic Algorithm (GA) to propose load shedding strategies in the power system. The Genetic Algorithm is used to support the training of Back Propagation Neural Networks (BPNN) to improve regression ability, minimize errors and reduce the training time. Besides, the Relief algorithm is used to reduce the number of input variables of the neural network. The minimum load shedding with consideration of the primary and secondary control is calculated to restore the frequency of the electrical system. The distribution of power load shedding at each load bus of the system based on the phase electrical distance between the outage generator and the load buses. The simulation results have been verified through using MATLAB and PowerWorld software systems. The results show that the Hybrid Gen-Bayesian algorithm (GA-Trainbr) has a remarkable superiority in accuracy as well as training time. The effectiveness of the proposed method is tested on the IEEE 37 bus 9 generators standard system diagram showing the effectiveness of the proposed method.
Linear approximation
This document discusses using linear approximation techniques to solve a nonlinear optimization problem for renewable sensor networks with wireless energy transfer. It presents a case study where the objective is to maximize the vacation time of a wireless charging vehicle over each cycle time by determining its optimal traveling path, charging schedule at each sensor node, and multi-hop data routing. The nonlinear problem is approximated using piecewise linear functions and solved to provide a near-optimal solution within a specified performance gap. Numerical results demonstrate the approach for a 50-node and 100-node network.
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This document presents a method for dominant CIR tap index identification in wideband channels. It proposes formulating the problem to maximize a lower bound on SNR by identifying the optimal number of CIR taps (L) to include. A two-step approach is used: 1) estimate noise variances from past OFDM symbols to determine tap powers, and 2) calculate sorted SNR values to find L via bisection search. Simulation results show over 50% SE improvement compared to not accounting for dominant taps, especially at high SNR. The method provides a simple, efficient way to identify important multipath for channel estimation.
Joint CSI Estimation, Beamforming and Scheduling Design for Wideband Massive ...
The document presents a new design for joint channel estimation, beamforming, and scheduling for wideband massive MIMO systems. It proposes using non-orthogonal pilots for channel estimation and a two-phase scheduling approach. Simulation results show the proposed design achieves higher total rates than conventional OFDM and performs better in dense multipath environments, especially with larger bandwidths and antenna arrays. An open issue discussed is comparing the proposed non-orthogonal pilot scheme to non-orthogonal multiple access techniques.
Hybrid Analog-Digital Architecture for Massive MIMO: An Introduction
The document describes the components of wireless transmitters and receivers. It discusses low-noise amplifiers (LNA), digital-to-analog converters (DAC), analog-to-digital converters (ADC), and other components. It also compares the design of antenna switch phase shifters for sub-6GHz systems like LTE versus mmWave systems operating at 60GHz, noting that the latter requires more antennas and RF chains.
Adaptive Channel Prediction, Beamforming and Scheduling Design for 5G V2I Net...
The document proposes and evaluates an adaptive channel prediction, beamforming, and scheduling design for 5G vehicle-to-infrastructure networks. It presents an RLS-based algorithm to predict time-varying channel impulse responses and jointly optimizes beamforming vectors and vehicle scheduling to maximize throughput. Simulation results show the proposed design outperforms alternatives when scheduling a single vehicle, but performance degrades with increasing numbers of scheduled vehicles due to accumulated prediction errors.
5G WIRELESS TECHNOLOGIES FOR V2X COMMUNICATIONS
The document discusses the potential applications of 5G networks for connected vehicles and vehicle-to-everything (V2X) communication systems. It outlines how vehicles will increasingly be connected to the internet and each other using wireless technologies. Standardization activities are underway to support these use cases, including work by the 5G Automotive Association to address connectivity needs for autonomous driving and integration with smart cities. Future 5G systems using microwave and millimeter wave technologies could enable 1000x greater capacity than current networks and make cost-effective V2X systems possible. The session will bring together researchers to discuss opportunities and challenges for 5G enabling connected vehicles.
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5G Communication (Full Video: https://www.youtube.com/watch?v=ICE2BGbQ_14)
This document discusses potential technologies for 5G communication networks, including:
1. Network densification through ultra dense heterogeneous networks using small cells and multi-hop relaying to improve coverage and capacity.
2. Utilization of new spectrum bands, including millimeter wave frequencies above 6 GHz and visible light communication, to provide additional bandwidth for 5G.
3. Implementation of massive MIMO technology using large antenna arrays to focus transmissions and improve spectral efficiency.
Pilot Contamination Mitigation for Wideband Massive MIMO: Number of Cells Vs ...
The document presents a pilot contamination mitigation technique for wideband massive MIMO systems. It proposes a three-step approach: 1) Allowing pilot transmission in the time domain, 2) Expressing sub-carrier channel estimates as linear combinations of received signals, and 3) Optimizing the number of cells, pilots, and linear combination terms to ensure unbounded signal-to-interference-plus-noise ratio (SINR). The main results show that the number of cells can be increased to L, where L is the number of multipath taps, allowing cancellation of pilot contamination. Simulation results demonstrate that the proposed approach achieves rates close to perfect channel state information.
Slide11 icc2015
The document presents a system model and problem formulation for user scheduling in massive MIMO OFDMA systems with hybrid analog-digital beamforming. The system considers a base station with N antennas but only Na < N RF chains serving multiple single-antenna mobile stations. The objective is to maximize the overall data rate by scheduling Kt mobile stations across subcarriers, subject to a per-subcarrier power constraint. For a single subcarrier, the problem is formulated as maximizing the sum rate of K scheduled users under a total power constraint, assuming Na = K RF chains. Two approaches are discussed: directly constraining the analog beamforming matrix or exploiting the solution from a digital scheduler using a clever decomposition method.
Call for papers: CROWNCOM Cognitive Radio Workshop
Crowncom 2015 will be held from April 21-23, 2015 in Doha, Qatar to mark the 10th anniversary of the conference. It will feature seven technical tracks on topics related to cognitive radio technology, as well as tutorials, panels, and keynote speakers. The goal is to bring together researchers to discuss recent developments and future trends in cognitive radio and its integration with 5G networks. Authors are invited to submit papers on topics such as dynamic spectrum access, networking protocols, modeling and theory, and emerging applications. The deadline for submissions is December 15, 2014.
Pilot Optimization and Channel Estimation for Multiuser Massive MIMO Systems
Slide for
Pilot Optimization and Channel Estimation for
Multiuser Massive MIMO Systems
Full paper is published in CISS 2014 conference
Sensing Throughput Tradeoff for Cognitive Radio Networks with Noise Variance ...
This document presents a method for sensing sub-bands in cognitive radio networks with uncertain noise variance. It proposes a new edge detector to detect the number of sub-bands in a wideband spectrum. It then identifies a reference white sub-band using average energy comparison. A test statistic is developed to sense the other sub-bands and optimize the sensing time. Simulation results show the detection probability of the proposed method and how it trades off sensing time with throughput. The method allows cognitive radios to maximize throughput while protecting primary users under uncertainty in noise variance.
More from T. E. BOGALE (12)
Dominant CIR Tap Index Identification for Wideband Channels
Dominant CIR Tap Index Identification for Wideband Channels
Joint CSI Estimation, Beamforming and Scheduling Design for Wideband Massive ...
Joint CSI Estimation, Beamforming and Scheduling Design for Wideband Massive ...
Hybrid Analog-Digital Architecture for Massive MIMO: An Introduction
Hybrid Analog-Digital Architecture for Massive MIMO: An Introduction
Adaptive Channel Prediction, Beamforming and Scheduling Design for 5G V2I Net...
Adaptive Channel Prediction, Beamforming and Scheduling Design for 5G V2I Net...
Orthogonal Faster than Nyquist Transmission for SIMO Wireless Systems
Orthogonal Faster than Nyquist Transmission for SIMO Wireless Systems
5G Communication (Full Video: https://www.youtube.com/watch?v=ICE2BGbQ_14)
5G Communication (Full Video: https://www.youtube.com/watch?v=ICE2BGbQ_14)
Pilot Contamination Mitigation for Wideband Massive MIMO: Number of Cells Vs ...
Pilot Contamination Mitigation for Wideband Massive MIMO: Number of Cells Vs ...
Call for papers: CROWNCOM Cognitive Radio Workshop
Call for papers: CROWNCOM Cognitive Radio Workshop
Pilot Optimization and Channel Estimation for Multiuser Massive MIMO Systems
Pilot Optimization and Channel Estimation for Multiuser Massive MIMO Systems
Sensing Throughput Tradeoff for Cognitive Radio Networks with Noise Variance ...
Sensing Throughput Tradeoff for Cognitive Radio Networks with Noise Variance ...
Weighted Sum Rate Optimization for Downlink Multiuser MIMO Systems with per Antenna Power Constraint: Downlink-Uplink Duality Approach
- 1. Weighted Sum Rate Optimization for Downlink Multiuser MIMO Systems with per Antenna Power Constraint: Downlink-Uplink Duality Approach Tadilo Endeshaw Bogale, Luc Vandendorpe ICTEAM Institute, Place du Levant, 2, 1348 Louvain-la-Neuve {tadilo.bogale, luc.vandendorpe}@uclouvain.be ABSTRACT This work proposes downlink-uplink duality approach to solve weighted sum rate maximization problem for multiuser MIMO systems. The duality is established by modifying the input covariance matrix of the dual uplink problem, and formulating the noise covariance matrix of the uplink channel as a fixed point function. In our simulation results, we have observed that the proposed duality based solution utilizes less total BS power than that of existing algorithms. PROBLEM FORMULATION PROPSED SOLUTION CONTINUED In this work we propose new duality based iterative solution to solve per antenna power constrained WSR maximization problem. For our simulation setup, we have observed that the proposed duality based solution requires less total BS power compared to the existing approach. TWO STEP PROPOSED DUALITY SOLUTION Difficult to ensure Per ant power const The per antenna power constraint issue of Algorithm I at step 4 can be resolved as follows SYSTEM MODEL CONCLUSIONS REFERENCES [1] T. E. Bogale and L.Vandendorpe,”Weighted sum rate optimization for downlink multiuser MIMO coordinated base station systems: Centralized and distributed algorithms,” IEEE Tran. Sig. Proc., Dec. 2011. [2] S.Shi, M. Schubert and H. Boche, “Per antenna power constrained rate optimization for multiyser MIMO systems,” ITG WSA, Berlin, Germany, 26 – 27 Feb., 2008, pp 270 -- 277 SIMULATION RESULTS IMPROVING THE CONVERGENCE SPEED OF ALGORITHM I