scholarly journals Sum Rate Analysis for Massive MIMO Downlink With MRC Beamforming and User Selection

2021 ◽  
Vol 2113 (1) ◽  
pp. 012025
Author(s):  
Yiyang Wu ◽  
Chang Chang ◽  
Fei Xie ◽  
Dacheng Ju ◽  
Yilun Pan
Keyword(s):  
Channel Model ◽  
Base Station ◽  
Transmission Model ◽  
User Selection ◽  
Selection Algorithm ◽  
User Scheduling ◽  
Downlink System ◽  
Sum Rate ◽  
Simulation Results ◽  
Mimo Downlink

Abstract Average allocation of data rate to each user is inefficient since the resource a base station can allocate is limited. Thus, user selection and user scheduling need to be applied into multi-user massive multiple-input multiple-output (MIMO) downlink system. In this paper, we mainly focus on the methods of user selection. First, we establish a downlink system model including transmission model and channel model. Then, two user-rate based user selection algorithms via the signal-to-interference-plus-noise-ratio (SINR) are proposed, where the SINR is generated by MRC beamforming. Finally, simulation results are provided to compare the performance of two proposed algorithms and their fairness towards selected users. In the simulation results, location-based selection algorithm and random selection algorithm are jointly compared. The second proposed algorithm possesses the highest total sum-rate and is the optimal algorithms among the four algorithms.

A User Selection Algorithm Based on the Combination of Block Diagonalization and SLNR Maximization

2013 ◽  
Vol 347-350 ◽  
pp. 2474-2478
Author(s):  
Wei Hong Fu ◽  
Cheng Wang ◽  
Nai An Liu ◽  
Qing Liang Kong ◽  
Wei Xin Tian
Keyword(s):  
User Selection ◽  
Rate Performance ◽  
Block Diagonalization ◽  
Selection Algorithm ◽  
Signal Noise ◽  
Performance Loss ◽  
Single Antenna ◽  
Sum Rate ◽  
Simulation Results ◽  
Noise Ratio

In this paper, a new precoding scheme is proposed based on the combination of Block Diagonalization (BD) and SLNR (Signal Leakage Noise Ratio) maximization. Then a new user selection algorithm is proposed based on the joint precoding scheme. BD precoding will cause performance loss in the single antenna terminals when the number of terminal antenna is inconsistent. The algorithm we proposed can overcome the drawback by using the maximum SLNR for single-antenna users and BD precoding for multi-antenna users respectively. Simulation results show that the proposed algorithm will enhance the system sum-rate performance significantly when SNR (Signal Noise Ratio) over 5dB. The performance improves by 30% when SNR reaches 20dB.

scholarly journals Sum Rate Analysis of MU-MIMO with a 3D MIMO Base Station Exploiting Elevation Features

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Xingwang Li ◽  
Lihua Li ◽  
Fupeng Wen ◽  
Junfeng Wang ◽  
Chao Deng
Keyword(s):  
Channel Model ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Three Dimensional ◽  
Base Station ◽  
Rate Performance ◽  
High Rise ◽  
Rate Analysis ◽  
Input Multiple Output ◽  
Sum Rate

Although the three-dimensional (3D) channel model considering the elevation factor has been used to analyze the performance of multiuser multiple-input multiple-output (MU-MIMO) systems, less attention is paid to the effect of the elevation variation. In this paper, we elaborate the sum rate of MU-MIMO systems with a 3D base station (BS) exploiting different elevations. To illustrate clearly, we consider a high-rise building scenario. Due to the floor height, each floor corresponds to an elevation. Therefore, we can analyze the sum rate performance for each floor and discuss its effect on the performance of the whole building. This work can be seen as the first attempt to analyze the sum rate performance for high-rise buildings in modern city and used as a reference for infrastructure.

Sum-Rate Analysis for Massive MIMO Downlink With Joint Statistical Beamforming and User Scheduling

2017 ◽  
Vol 16 (4) ◽  
pp. 2181-2194 ◽  
Author(s):  
Cheng Zhang ◽  
Yongming Huang ◽  
Yindi Jing ◽  
Shi Jin ◽  
Luxi Yang
Keyword(s):  
Massive Mimo ◽  
User Scheduling ◽  
Rate Analysis ◽  
Sum Rate ◽  
Mimo Downlink

scholarly journals Low-Complexity User Scheduling with Switched Tilting for 3D Cellular Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Haijing Liu ◽  
Hui Gao ◽  
Tiejun Lv
Keyword(s):  
Large Scale ◽  
Matrix Theory ◽  
Low Complexity ◽  
Base Station ◽  
Optimal Number ◽  
Cellular Systems ◽  
Rate Performance ◽  
User Scheduling ◽  
Sum Rate ◽  
Computational Resources

We propose a low-complexity user scheduling scheme to enhance the sum rate performance for a multicell downlink system, in which the base station (BS) is equipped with a large-scale active antenna array. First, we divide each cell intoNregions according to the vertical beamwidth of the BS antennas. Next, candidate user equipment (UE) items are assigned to corresponding groups to their locations. Each scheduling slot is also divided intoNequal-time subslots. Then, at each subslot, we focus on one UE group, select the optimal number,K*, of UEs for simultaneous data transmission in the manner of round-robin scheduling, and adjust the BS antenna tilting to the optimal angleθtilt*. In particular,K*andθtilt*for each UE group are both obtained by means of large-system asymptotic analysis. Benefiting from the random matrix theory tools, the asymptotic analytical results are independent of instantaneous channel state information of UE, which make it possible to solveK*andθtilt*offline, therefore saving the online computational resources significantly. Numerical results verify that the proposed scheme achieves good sum rate performance with extremely low computational complexity.

Capacity Limits of Base Station Cooperation in Cellular Networks

2010 ◽  
pp. 102-132
Author(s):  
Symeon Chatzinotas ◽  
Muhammad Ali Imran ◽  
Reza Hoshyar
Keyword(s):  
Channel Model ◽  
High Capacity ◽  
Path Loss ◽  
Base Station ◽  
Cellular Systems ◽  
Current Channel ◽  
Capacity Limits ◽  
Base Station Cooperation ◽  
Rate Capacity ◽  
Sum Rate

In the information-theoretic literature, it has been widely shown that multicell processing is able to provide high capacity gains in the context of cellular systems. What is more, it has been proved that the per-cell sum-rate capacity of multicell processing systems grows linearly with the number of base station (BS) receive antennas. However, the majority of results in this area have been produced assuming that the fading coefficients of the MIMO subchannels are completely uncorrelated. In this direction, this chapter investigates the ergodic per-cell sum-rate capacity of the Gaussian MIMO cellular channel under correlated fading and BS cooperation (multicell processing). More specifically, the current channel model considers Rayleigh fading, uniformly distributed user terminals (UTs) over a planar cellular system, and power-law path loss. Furthermore, both BSs and UTs are equipped with correlated multiple antennas, which are modelled according to the Kronecker product correlation model. The per-cell sum-rate capacity is evaluated while varying the cell density of the system, as well as the level of receive and transmit correlation. In this context, it is shown that the capacity performance is compromised by correlation at the BS-side, whereas correlation at the UT-side has a negligible effect on the system’s capacity.

A User Selection Algorithm Providing Maximum Sum-Rate for Multiuser MIMO Systems

2010 ◽  
Vol E93-B (5) ◽  
pp. 1302-1305 ◽  
Author(s):  
Taeyoul OH ◽  
Seungheon HYEON ◽  
Hyunsung GO ◽  
Seungwon CHOI
Keyword(s):  
Mimo Systems ◽  
User Selection ◽  
Selection Algorithm ◽  
Multiuser Mimo ◽  
Sum Rate ◽  
Multiuser Mimo Systems

scholarly journals Low Power Allocation Based Error Improvements in wireless 5G

2019 ◽  
Vol 8 (4) ◽  
pp. 11049-11052
Keyword(s):  
Multiple Access ◽  
Antenna Selection ◽  
Base Station ◽  
Time Varying ◽  
Transmit Antenna Selection ◽  
User Experiences ◽  
Common Technique ◽  
Sum Rate ◽  
Simulation Results ◽  
Time Varying Channel

Transmit antenna selection is very common technique to reduce system complexity and power consumption at transmitter side while maintaining nearly the same performance of multiple antennas. In this paper, we introduce a transmit antenna selection (TAS) scheme for non orthogonal multiple access (NOMA) to improve the performance in terms of total sum rate. Therefore different antenna elements added at the base station experiences different fading conditions (A channel is a time varying channel).Experiences different SNR values adding more number of antennas at the base station. Increases the complaxicity as well as the performance with respect to the sum rate Non linear the user experiences the Bit error rate at the receiver simulation results shows that the BER is verified for different antenna error consideration (MIMO).

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