scholarly journals Enhanced Transmit-Antenna Selection Schemes for Multiuser Massive MIMO Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Byung-Jin Lee ◽  
Sang-Lim Ju ◽  
Nam-il Kim ◽  
Kyung-Seok Kim
Keyword(s):  
Computational Complexity ◽  
Radio Frequency ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Base Station ◽  
Base Stations ◽  
Transmit Antenna Selection ◽  
Selection Scheme

Massive multiple-input multiple-output (MIMO) systems are a core technology designed to achieve the performance objectives defined for 5G wireless communications. They achieve high spectral efficiency, reliability, and diversity gain. However, the many radio frequency chains required in base stations equipped with a high number of transmit antennas imply high hardware costs and computational complexity. Therefore, in this paper, we investigate the use of a transmit-antenna selection scheme, with which the number of required radio frequency chains in the base station can be reduced. This paper proposes two efficient transmit-antenna selection (TAS) schemes designed to consider a trade-off between performance and computational complexity in massive MIMO systems. The spectral efficiency and computational complexity of the proposed schemes are analyzed and compared with existing TAS schemes, showing that the proposed algorithms increase the TAS performance and can be used in practical systems. Additionally, the obtained results enable a better understanding of how TAS affects massive MIMO systems.

scholarly journals A Novel Transmit Antenna Selection Algorithms to Improve Energy and Spectral Efficiency

2019 ◽  
Vol 9 (2S3) ◽  
pp. 298-301
Keyword(s):  
Spectral Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Transmit Antenna Selection ◽  
Noise Interference ◽  
Efficiency Performance ◽  
Selection Algorithms ◽  
Mimo Technology ◽  
Selection Of

In massive MIMO systems, the selection of optimal transmits antennas remains as a major constraint. As the number of antennas is increased, the power or energy consumption also increases. Selection of optimal transmit antennas is considered as a multi objective problem, where the energy has to be minimizedand the spectral efficiency (bandwidth) has to be increased. In fact, for attaining higher bandwidth, more transmit antennas have to be selected, which leads to increase in power consumption, In this proposal various papers are reviewed for Energy and Spectral Efficiency performance in Massive MIMO Technology through different algorithms and parameter comparisons are made to identify the better algorithms in terms of EE and SE to achieve the higher data transmission rates, BER, mitigating the inter Noise interference.

scholarly journals A Novel Iterative Discrete Estimation Algorithm for Low-Complexity Signal Detection in Uplink Massive MIMO Systems

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 980 ◽  
Author(s):  
Hui Feng ◽  
Xiaoqing Zhao ◽  
Zhengquan Li ◽  
Song Xing
Keyword(s):  
Computational Complexity ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Estimation Algorithm ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Base Station ◽  
Damping Factor ◽  
Mimo Detection ◽  
Discrete Estimation

In this paper, a novel iterative discrete estimation (IDE) algorithm, which is called the modified IDE (MIDE), is proposed to reduce the computational complexity in MIMO detection in uplink massive MIMO systems. MIDE is a revision of the alternating direction method of multipliers (ADMM)-based algorithm, in which a self-updating method is designed with the damping factor estimated and updated at each iteration based on the Euclidean distance between the iterative solutions of the IDE-based algorithm in order to accelerate the algorithm’s convergence. Compared to the existing ADMM-based detection algorithm, the overall computational complexity of the proposed MIDE algorithm is reduced from O N t 3 + O N r N t 2 to O N t 2 + O N r N t in terms of the number of complex-valued multiplications, where Ntand Nr are the number of users and the number of receiving antennas at the base station (BS), respectively. Simulation results show that the proposed MIDE algorithm performs better in terms of the bit error rate (BER) than some recently-proposed approximation algorithms in MIMO detection of uplink massive MIMO systems.

A Novel Transmit Diversity Technique for MIMO System

2012 ◽  
Vol 468-471 ◽  
pp. 355-359
Author(s):  
You Yan Zhang ◽  
Shu Yue Hong
Keyword(s):  
Likelihood Ratio ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Signal To Noise Ratio ◽  
Gray Code ◽  
Transmit Antenna Selection ◽  
Selection Scheme ◽  
Log Likelihood ◽  
Log Likelihood Ratio

The antenna diversity based on log-likelihood ratio (LLR) is better than that based on signal-to-noise ratio (SNR) in bit error rate performance for MIMO systems. Thus in this paper, we present a novel transmit antenna selection scheme based on bit log-likelihood ratio when the Alamouti code is employed .Then the BER expressions of application based on Bit-LLR (BLLR) for MPSK and MQAM modulation with Gray code are derived. The simulation results show that the new scheme based on BLLR is superior to SNR. With the increase of the transmit antennas, the performance of system is improved significantly. Furthermore, the diversity order is the same as that of the full complexity systems.

scholarly journals Transmit Antenna Optimization in Massive MIMO Technology with EE, SE Trade off

2019 ◽  
Vol 9 (1) ◽  
pp. 1926-1929
Keyword(s):  
Data Transmission ◽  
Massive Mimo ◽  
Search Algorithm ◽  
Antenna Selection ◽  
Gravitational Search Algorithm ◽  
Base Station ◽  
Transmit Antenna Selection ◽  
Transmission Rates ◽  
High Data ◽  
Mimo Technology

Massive MIMO Technology showed its unique characteristics and capabilities for future wireless communications where high data transmission rates are desired for fast growing 5G applications. High data transmission rates need more number of antennas at base station which comprised of increased system complexity and hardware cost. A proven method for reducing number of RF (radio frequency) chains at base station is Transmit Antenna Selection algorithm. In this paper an effective approach for TAS and optimizing the number of antennas at base station for desired data rates have been proposed and a Tradeoff between SE (Spectral Efficiency), EE (energy Efficiency) are discussed. MVGSA (modified velocity Gravitational Search algorithm) discussed for optimization of Transmit Antennas along with Improved SE and EE other effective algorithms are compared with multi objectives and data transmission rates. MVGSA proved with Improved SE and EE with Effective TAS.

scholarly journals Efficient Capacity-Based Joint Quantized Precoding and Transmit Antenna Selection Using Cross-Entropy Method for Multiuser MIMO Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Jung-Chieh Chen ◽  
Min-Han Chiu ◽  
Yi-Syun Yang ◽  
Kuan-Yuen Liao ◽  
Chih-Peng Li
Keyword(s):  
Computational Complexity ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Random Search ◽  
Multiple Input Multiple Output ◽  
Entropy Method ◽  
Cross Entropy ◽  
Transmit Antenna Selection ◽  
Cross Entropy Method ◽  
Optimum Solution

The current paper considers the joint precoding and transmit antenna selection to reduce hardware cost, such as radio-frequency chains, associated with antennas in the downlink of multiuser multiple-input multiple-output systems with limited feedback. The joint precoding and transmit antenna selection algorithm requires an exhaustive search of all possible combinations and permutations to find the optimum solution at the transmitter, thus resulting in extremely high computational complexity. To reduce the computational load while still maximizing channel capacity, the cross-entropy (CE) method is adopted to determine the suboptimum solution. Compared with the conventional genetic algorithm and random search method, the CE method provides better performance under the same computational complexity, as shown by the simulation results.

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