Low Complexity User Scheduling, Ordering and Transmit Covariance Matrix Optimization Algorithms for Successive Zero-Forcing Precoding

2013 ◽  
Vol 75 (4) ◽  
pp. 2467-2484 ◽  
Author(s):  
Shreeram Sigdel ◽  
Witold A. Krzymień
Keyword(s):  
Covariance Matrix ◽  
Optimization Algorithms ◽  
Low Complexity ◽  
User Scheduling ◽  
Zero Forcing ◽  
Matrix Optimization

scholarly journals Precoding With Received-Interference Power Control for Multibeam Satellite Communication Systems

2021 ◽  
Vol 2 ◽  
Author(s):  
Eva Lagunas ◽  
Ana Pérez-Neira ◽  
Marc Martínez ◽  
Miguel Angel Lagunas ◽  
Miguel Angel Vázquez ◽  
...  
Keyword(s):  
Communication Systems ◽  
Satellite Communication ◽  
Satellite Communications ◽  
Low Complexity ◽  
Limiting Factors ◽  
Practical Implementation ◽  
Interference Power ◽  
User Scheduling ◽  
Zero Forcing ◽  
The Matrix

Zero-Forcing (ZF) and Regularized Zero-Forcing (RZF) precoding are low-complexity sub-optimal solutions widely accepted in the satellite communications community to mitigate the resulting co-channel interference caused by aggressive frequency reuse. However, both are sensitive to the conditioning of the channel matrix, which can greatly reduce the achievable gains. This paper brings the attention to the benefits of a design that allows some residual received interference power at the co-channel users. The motivation behind this approach is to relax the dependence on the matrix inversion procedure involved in conventional precoding schemes. In particular, the proposed scheme aims to be less sensitive to the user scheduling, which is one of the key limiting factors for the practical implementation of precoding. Furthermore, the proposed technique can also cope with more users than satellite beams. In fact, the proposed precoder can be tuned to control the interference towards the co-channel beams, which is a desirable feature that is not met by the existing RZF solutions. The design is formulated as a non-convex optimization and we study various algorithms in order to obtain a practical solution. Supporting results based on numerical simulations show that the proposed precoding implementations are able to outperform the conventional ZF and RZF schemes.

Performance Analysis of Low Complexity Multiuser Scheduling Algorithms in MIMO System

2013 ◽  
Vol 392 ◽  
pp. 867-871
Author(s):  
Ming Xia Lv ◽  
Yan Kun Lai ◽  
Dong Tang
Keyword(s):  
Mimo System ◽  
Scheduling Algorithm ◽  
Low Complexity ◽  
Base Station ◽  
User Scheduling ◽  
Sum Capacity ◽  
Multiuser Scheduling ◽  
The Common ◽  
The Cost ◽  
Selection Algorithms

The total throughput of the communication system can be maximized by allocating the common radio resource to the user or the user group having the best channel quality at a given time and the multiuser diversity gain can be obtained when multiple users share the same channel at one time. The object to select the users is to select the users with the maximum sum capacity. As for a scheduling algorithm, exhaustive algorithm can get the largest capability of the system by multi-user scheduling. However, this algorithm is quite complex hence the cost of operation to a base station has substantial increased. We compare the multiuser performance of two fast user selection algorithms with low complexity in MIMO-MRC systems with co-channel interferences. From the simulation results, these two algorithms not only decrease the computational complexity of the scheduling algorithm but also retain large capability of the MIMO system.

scholarly journals Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3368
Author(s):  
Rui Hu ◽  
Jun Tong ◽  
Jiangtao Xi ◽  
Qinghua Guo ◽  
Yanguang Yu
Keyword(s):  
Covariance Matrix ◽  
Communication Systems ◽  
Low Complexity ◽  
Low Rank ◽  
Covariance Matrix Estimation ◽  
Hardware Complexity ◽  
Matrix Estimation ◽  
Planar Arrays ◽  
Rank Matrix ◽  
Low Rank Matrix

Hybrid massive MIMO structures with lower hardware complexity and power consumption have been considered as potential candidates for millimeter wave (mmWave) communications. Channel covariance information can be used for designing transmitter precoders, receiver combiners, channel estimators, etc. However, hybrid structures allow only a lower-dimensional signal to be observed, which adds difficulties for channel covariance matrix estimation. In this paper, we formulate the channel covariance estimation as a structured low-rank matrix sensing problem via Kronecker product expansion and use a low-complexity algorithm to solve this problem. Numerical results with uniform linear arrays (ULA) and uniform squared planar arrays (USPA) are provided to demonstrate the effectiveness of our proposed method.

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