scholarly journals Energy Efficiency-Oriented Resource Allocation for Massive MIMO Systems with Separated Channel Estimation and Feedback

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 582
Author(s):  
Feng Hu ◽  
Kaiyue Wang ◽  
Shufeng Li ◽  
Libiao Jin

This paper proposes a dynamic resource allocation scheme to maximize the energy efficiency (EE) for Massive MIMO Systems. The imperfect channel estimation (CE) and feedback are explicitly considered in the EE maximization problem, which aim to optimize the power allocation, the antenna subset selection for transmission, and the pilot assignment. Assuming CE error to be bounded for the complex-constrained Cramer–Rao Bound (CRB), theoretical results show that the lower bound is directly proportional to its number of unconstrained parameters. Utilizing this perspective, a separated and bi-directional estimation is developed to achieve both low CRB and low complexity by exploiting channel and noise spatial separation. Exploiting global optimization procedure, the optimal resource allocation can be transformed into a standard convex optimization problem. This allows us to derive an efficient iterative algorithm for obtaining the optimal solution. Numerical results are provided to demonstrate that the outperformance of the proposed algorithms are superior to existing schemes.

2019 ◽  
Vol 8 (4) ◽  
pp. 1103-1107 ◽  
Author(s):  
Xianda Wu ◽  
Guanghua Yang ◽  
Fen Hou ◽  
Shaodan Ma

Electronics ◽  
2018 ◽  
Vol 7 (10) ◽  
pp. 218 ◽  
Author(s):  
Kifayatullah Bangash ◽  
Imran Khan ◽  
Jaime Lloret ◽  
Antonio Leon

Traditional Minimum Mean Square Error (MMSE) detection is widely used in wireless communications, however, it introduces matrix inversion and has a higher computational complexity. For massive Multiple-input Multiple-output (MIMO) systems, this detection complexity is very high due to its huge channel matrix dimension. Therefore, low-complexity detection technology has become a hot topic in the industry. Aiming at the problem of high computational complexity of the massive MIMO channel estimation, this paper presents a low-complexity algorithm for efficient channel estimation. The proposed algorithm is based on joint Singular Value Decomposition (SVD) and Iterative Least Square with Projection (SVD-ILSP) which overcomes the drawback of finite sample data assumption of the covariance matrix in the existing SVD-based semi-blind channel estimation scheme. Simulation results show that the proposed scheme can effectively reduce the deviation, improve the channel estimation accuracy, mitigate the impact of pilot contamination and obtain accurate CSI with low overhead and computational complexity.


Sign in / Sign up

Export Citation Format

Share Document