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หน่วยที่ 3 รูปร่างเครือข่าย
หน่วยที่ 3 รูปร่างเครือข่าย
natnathapong
Kowit
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Kowit Yodmongkol
What is Mimo,Why MIMO,Diversity and multiplexing,need of mimo,reliability ,capacity of mimo all this aspect we will see here
MIMO Antenna and Technology installation
MIMO Antenna and Technology installation
DILSHAD AHMAD
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.
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Performance Analysis of Massive MIMO Downlink System with Imperfect Channel S...
IJRES Journal
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TitanMIMO is the only testbed capable of enabling true 5G Massive MIMO research without compromise. - Remote or local radio head location - Validate various waveform propagation schemes - Optimize network deployment by balancing cost VS performance - Validate interoperability scenarios - HetNet, MU-MIMO, and CRAN testbed ready - Validate, optimize & develop analytic channel models - Optimize TDD and RF calibration techniques - Full TDD & FDD support
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หน่วยที่ 3 รูปร่างเครือข่าย
หน่วยที่ 3 รูปร่างเครือข่าย
natnathapong
Kowit
Kowit
Kowit Yodmongkol
What is Mimo,Why MIMO,Diversity and multiplexing,need of mimo,reliability ,capacity of mimo all this aspect we will see here
MIMO Antenna and Technology installation
MIMO Antenna and Technology installation
DILSHAD AHMAD
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 Massive MIMO Downlink System with Imperfect Channel S...
Performance Analysis of Massive MIMO Downlink System with Imperfect Channel S...
IJRES Journal
Mimo Calculation
MIMO Calculation
MIMO Calculation
Abhijeet Kumar
TitanMIMO is the only testbed capable of enabling true 5G Massive MIMO research without compromise. - Remote or local radio head location - Validate various waveform propagation schemes - Optimize network deployment by balancing cost VS performance - Validate interoperability scenarios - HetNet, MU-MIMO, and CRAN testbed ready - Validate, optimize & develop analytic channel models - Optimize TDD and RF calibration techniques - Full TDD & FDD support
Nutaq's TitanMIMO Massive MIMO Testbeds
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Nutaq
Vblast
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Amal Shekar
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In the present thesis, the concept for beyond 3G mobile radio systems is described. A service area concept is introduced in order to combat the performance limiting interferences present in the cellular mobile communication systems, with each service area consisting of a various simultaneously active mobile terminals, a number of fixed access points and a central unit per- forming signal processing. About uplink transmission, the main characteristic of this service area system is that with the aid of joint detection of the transmit signals from the mobile ter- minals performed at uplink transmission, all interferences between the simultaneously active mobile terminals using the same bandwidth is drastically reduced. Moreover the use of OFDM subcarrierwise in the described service area based system allows for intersymbol interference free communication and for simple equalization in the frequency domain. Through this subcarrierwise equalization the service area based system is equivalent with a number of smaller parallel systems, a fact that affects in a reduced computational complexity in the case of optimum multiuser operating with the maximum likehood principle and subop- timum linear detector zero-forcing. In this thesis the parallel interference cancellation detector is introduced, according to which the multi access interference is iteratively reconstructed and subtracted from the received signal. Parallel interference cancellation detector is compared in terms of performance with suboptimum linear detector, due to the reduced computational com- plexity. Using standardized COST 207 channel models, the performance of parallel interference can- cellation detector compared with suboptimum linear detector has been investigated for a frozen channel, with the same snapshot using the same parameters of the channel, as well as for a number of system loads. A fact that can be observed in simulations results is that parallel in- terference cancellation detectors could achieve the same performance with a reduction of the complexity as suboptimum linear detector zero-forcing in the case of no estimate refinement and with estimate refinement by hard quantization depending on the load system. With esti- mate refinement by soft quantization the performance of the parallel interference cancellation detector is improved, having better performance than zero-forcing detector in cases with nor- mal load. Moreover with the improvement raised in this thesis, in this normal system load, the performance is more improved. On the other hand in the case of full load system, the PIC detector can not substract all the multi access interference producing error flow, this thing is not too important taking in account that the fully loaded system case should not be never present.
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Globecom 2015: Citywide MU vs SU MIMO (Siming Zhang)
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In the present thesis, the concept for beyond 3G mobile radio systems is described. A service area concept is introduced in order to combat the performance limiting interferences present in the cellular mobile communication systems, with each service area consisting of a various simultaneously active mobile terminals, a number of fixed access points and a central unit per- forming signal processing. About uplink transmission, the main characteristic of this service area system is that with the aid of joint detection of the transmit signals from the mobile ter- minals performed at uplink transmission, all interferences between the simultaneously active mobile terminals using the same bandwidth is drastically reduced. Moreover the use of OFDM subcarrierwise in the described service area based system allows for intersymbol interference free communication and for simple equalization in the frequency domain. Through this subcarrierwise equalization the service area based system is equivalent with a number of smaller parallel systems, a fact that affects in a reduced computational complexity in the case of optimum multiuser operating with the maximum likehood principle and subop- timum linear detector zero-forcing. In this thesis the parallel interference cancellation detector is introduced, according to which the multi access interference is iteratively reconstructed and subtracted from the received signal. Parallel interference cancellation detector is compared in terms of performance with suboptimum linear detector, due to the reduced computational com- plexity. Using standardized COST 207 channel models, the performance of parallel interference can- cellation detector compared with suboptimum linear detector has been investigated for a frozen channel, with the same snapshot using the same parameters of the channel, as well as for a number of system loads. A fact that can be observed in simulations results is that parallel in- terference cancellation detectors could achieve the same performance with a reduction of the complexity as suboptimum linear detector zero-forcing in the case of no estimate refinement and with estimate refinement by hard quantization depending on the load system. With esti- mate refinement by soft quantization the performance of the parallel interference cancellation detector is improved, having better performance than zero-forcing detector in cases with nor- mal load. Moreover with the improvement raised in this thesis, in this normal system load, the performance is more improved. On the other hand in the case of full load system, the PIC detector can not substract all the multi access interference producing error flow, this thing is not too important taking in account that the fully loaded system case should not be never present.
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3 Network Topology) 1.
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Star-Topology HUB) Bus hub switch Bus Hub
Switch **** **** Transmission Media) Hardware) Software)
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