A Novel Antenna Selection Algorithm Based on Port Selection in Distributed MIMO Systems

2014 ◽  
Vol 687-691 ◽  
pp. 3956-3962
Author(s):  
Nae Zheng ◽  
Xiu Kun Ren ◽  
Peng Dong ◽  
Shi Lei Zhu
Keyword(s):  
Mimo Systems ◽  
Optimal Algorithm ◽  
Selection Process ◽  
Antenna Selection ◽  
Mimo System ◽  
Structural Characteristics ◽  
Base Station ◽  
System Capacity ◽  
Selection Algorithm ◽  
Port Selection

The antenna number in distributed MIMO system is much larger than that in distributed antenna system (DAS) and traditional centralized MIMO system. Therefore adopting the existing antenna selection algorithms with excellent performance will make it difficult to realize the system due to the complexity of the algorithms. In order to solve the problem, a novel antenna selection algorithm performed at the base station (BS) is proposed according to the structural characteristics of the system. In the proposed algorithm, the antenna search scope is narrowed down by port selection based on the trace of the sub-channel matrices, and antennas with little contributions to the system capacity are removed gradually by iteratively updating the optimization parameter, which further reduces the complexity. When this algorithm is treated as the transmit antenna selection algorithm, its port selection process is performed by the user equipment, which can reduce the feedback overhead. Simulation results show that the proposed algorithm possesses the similar system capacity with the optimal algorithm.

scholarly journals On the Capacity and Transmission Techniques of Massive MIMO Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Mohamed Abdul Haleem
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Transmission Rate ◽  
Mimo System ◽  
Coupling Factor ◽  
Base Station ◽  
Power Sharing ◽  
System Capacity ◽  
Bit Rate ◽  
Channel Coupling

A massive MIMO wireless system is a multiuser MISO system where base stations consist of a large number of antennas with respect to number of user devices, each equipped with a single antenna. Massive MIMO is seen as the way forward in enhancing the transmission rate and user capacity in 5G wireless. The potential of massive MIMO system lies in the ability to almost always realize multiuser channels with near zero mutual coupling. Coupling factor reduces by 1/2 for each doubling of transmit antennas. In a high bit rate massive MIMO system with m base station antennas and n users, downlink capacity increases as log2⁡m bps/Hz, and the capacity per user reduces as log2⁡n bps/Hz. This capacity can be achieved by power sharing and using signal weighting vectors aligned to respective 1×m channels of the users. For low bit rate transmission, time sharing achieves the capacity as much as power sharing does. System capacity reduces as channel coupling factor increases. Interference avoidance or minimization strategies can be used to achieve the available capacity in such scenarios. Probability distribution of channel coupling factor is a convenient tool to predict the number of antennas needed to qualify a system as massive MIMO.

scholarly journals A Fast Adaptive Receive Antenna Selection Method in MIMO System

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Chaowei Wang ◽  
Weidong Wang ◽  
Cheng Wang ◽  
Shuai Wang ◽  
Yang Yu
Keyword(s):  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
System Capacity ◽  
Adaptive Antenna ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Hardware Costs ◽  
Receive Antenna

Antenna selection has been regarded as an effective method to acquire the diversity benefits of multiple antennas while potentially reduce hardware costs. This paper focuses on receive antenna selection. According to the proportion between the numbers of total receive antennas and selected antennas and the influence of each antenna on system capacity, we propose a fast adaptive antenna selection algorithm for wireless multiple-input multiple-output (MIMO) systems. Mathematical analysis and numerical results show that our algorithm significantly reduces the computational complexity and memory requirement and achieves considerable system capacity gain compared with the optimal selection technique in the same time.

A Comparison of Norm Based Antenna Selection and Random Antenna Selection with Regard to Energy Efficiency in Wireless System with Large Number of Users

2020 ◽  
Vol 10 (2) ◽  
pp. 189-196
Author(s):  
Ashu Taneja ◽  
Nitin Saluja
Keyword(s):  
Energy Efficiency ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Transmit Antenna Selection ◽  
Wireless System ◽  
Multiple Input ◽  
Input Multiple Output

Background: The paper considers the wireless system with large number of users (more than 50 users) and each user is assigned large number of antennas (around 200) at the Base Station (BS). Objective: The challenges associated with the defined system are increased power consumption and high complexity of associated circuitry. The antenna selection is introduced to combat these problems while the usage of linear precoding reduces computational complexity. The literature suggests number of antenna selection techniques based on statistical properties of signal. However, each antenna selection technique suits well to specific number of users. Methods: In this paper, the random antenna selection is compared with norm-based antenna selection. It is analysed that the random antenna selection leads to inefficient spectral efficiency if the number of users are more than 50 in Multi-User Multiple-Input Multiple Output (MU-MIMO) system. Results: The paper proposes the optimization of Energy-Efficiency (EE) with random transmit antenna selection for large number of users in MU-MIMO systems. Conclusion: Also the computation leads to optimization of number of transmit antennas at the BS for energy efficiency. The proposed algorithm results in improvement of the energy efficiency by 27% for more than 50 users.

scholarly journals Performance Analysis of Rate Splitting in Massive MIMO Systems with Low Resolution ADCs/DACs

2021 ◽  
Vol 11 (20) ◽  
pp. 9409
Author(s):  
Roger Kwao Ahiadormey ◽  
Kwonhue Choi
Keyword(s):  
Mimo Systems ◽  
Mimo System ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Quantization Noise ◽  
High Signal ◽  
Low Resolution ◽  
Rate Splitting ◽  
Noise Ratio

In this paper, we propose rate-splitting (RS) multiple access to mitigate the effects of quantization noise (QN) inherent in low-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs). We consider the downlink (DL) of a multiuser massive multiple-input multiple-output (MIMO) system where the base station (BS) is equipped with low-resolution ADCs/DACs. The BS employs the RS scheme for data transmission. Under imperfect channel state information (CSI), we characterize the spectral efficiency (SE) and energy efficiency (EE) by deriving the asymptotic signal-to-interference-and-noise ratio (SINR). For 1-bit resolution, the QN is very high, and the RS scheme shows no rate gain over the non-RS scheme. As the ADC/DAC resolution increases (i.e., 2–3 bits), the RS scheme achieves higher SE in the high signal-to-noise ratio (SNR) regime compared to that of the non-RS scheme. For a 3-bit resolution, the number of antennas can be reduced by 27% in the RS scheme to achieve the same SE as the non-RS scheme. Low-resolution DACs degrades the system performance more than low-resolution ADCs. Hence, it is preferable to equip the system with low-resolution ADCs than low-resolution DACs. The system achieves the best SE/EE tradeoff for 4-bit resolution ADCs/DACs.

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.

Adaptive Antenna Selection Algorithm for Spatial Multiplexing MIMO Systems

2007 ◽  
Author(s):  
Seyed Aidin Bassam ◽  
Mohammad Kalantari ◽  
Slim Boumaiza ◽  
Robert Davies ◽  
Fadhel M. Ghannouchi
Keyword(s):  
Mimo Systems ◽  
Antenna Selection ◽  
Spatial Multiplexing ◽  
Adaptive Antenna ◽  
Selection Algorithm
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