scholarly journals A Novel Joint Transmitting and Receiving Antenna Selection for Spatial Multiplexing Systems

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mingjie Zhuang ◽  
Haitao Li ◽  
Yisong Lin
Keyword(s):  
Computational Complexity ◽  
Optimal Algorithm ◽  
Antenna Selection ◽  
Mimo System ◽  
Antenna System ◽  
Spatial Multiplexing ◽  
Mimo Channel ◽  
Maximum Capacity ◽  
Receiving Antenna ◽  
Transmitting Antenna

AbstractHow to reduce the hardware cost and high power consumption of RF link of communication device is the key problem to be solved for multi-transmitting antenna and multi-receiving antenna system (MIMO). Always choose the best antennas connection a limited number of RF circuits, which is called antenna selection technology (AS), are a perfect solution to the problem, Assuming that the spatial range of the antenna meets the requirements of signal multiplexing and based on the maximum capacity criterion of the selected MIMO system, the manuscript proposes a low computational complexity (CC) and high performance joint transmitting and receiving antenna selection technique (JTRAS). Starting from the traditional capacity formula and the full matrix of MIMO channel, we utilize a simplified channel capacity expression through repeatedly iterating to delete a row and a column of the equivalent decrement channel matrix, which is to remove a pair of transmitting and receiving antennas. Based on the decreasing JTRAS (DJTRAS) algorithm, the capacity results of simulating calculation indicate that its median capacity overtakes other ones, such as optimum selection (OS), AS based on Frobenius 2 norm (NBS), and concise joint AS criterion (CJAS) etc., and the novel DJTRAS scheme can significantly reduce computational complexity (CC) compared to the exhaustive search method with maximum capacity, which defined as optimal algorithm in the curve graphs. This new technology of the AS is particularly suited to large number of selected antennas, such as Lt ≥ NT/2,Lr ≥ NR/2.

scholarly journals Analysis between Various Random MIMO Systems Model on the Basis of Channel Capacity

2016 ◽  
Author(s):  
Shree Krishna Acharya
Keyword(s):  
Outage Probability ◽  
Channel Capacity ◽  
Mimo Systems ◽  
Mimo System ◽  
Antenna System ◽  
System Model ◽  
Mimo Channel ◽  
Systems Model ◽  
Capacity Model ◽  
Transmitting Antenna

Finding a good MIMO system model also major issue in Wireless Communication system. It is facing with so many problem, one of the major problem is finding good system model in terms of capacity and transmitting antenna system. In this paper, we analyze the channel capacity of various MIMO system model with some constant SNR level and outage probability. We establish a novel idea for MIMO system models as consider as 2N- MIMO system model and find-out change in channel capacity when different transmitting antennas with constant SNR and outage probability. The channel capacity ratio CCR is presented here on the basis of 2N- MIMO channel capacity model. Number of transmitted antenna presented in MIMO system is increases is well-known however paper shows change in capacity in simple form.

A Successive Iterative Optimal Pre-Coding Algorithm for Downlink Multi-User MIMO System

2012 ◽  
Vol 457-458 ◽  
pp. 1012-1018
Author(s):  
Xian Kun Gao ◽  
Jian Hua Qu ◽  
Chuan An Yao ◽  
Yong Chang Yu
Keyword(s):  
System Performance ◽  
Optimal Algorithm ◽  
Mimo System ◽  
Spatial Multiplexing ◽  
Considerable Improvement ◽  
The Other ◽  
Multiple Data ◽  
Simulation Results ◽  
Mimo Downlink ◽  
To Receive

Spatial multiplexing in the multi-user MIMO downlink allows each user in the system to receive multiple data subchannels simultaneously using the same time and spectral resources. In this paper, a successive iterative optimal algorithm based on signal-to-leakage-and-noise-ratio (SLNR) maximization algorithm is proposed, which make use of the unused subspace of some known users to improve the space gain of the other users and has no strict constraint on transmit and receive antennas numbers. According to the simulation results, the proposed algorithm outperforms the original SLNR algorithm, and has a considerable improvement in the system performance.

scholarly journals Power Constrained Space-Time Processing for Suppression of Electromagnetic Fields

2017 ◽  
Vol 1 (1) ◽  
pp. 71 ◽  
Author(s):  
Tommy Hult ◽  
Abbas Mohammed
Keyword(s):  
Electromagnetic Field ◽  
Power Density ◽  
Active Control ◽  
Mimo System ◽  
Superposition Principle ◽  
Human Head ◽  
Antenna System ◽  
Space Time ◽  
Time Processing ◽  
Transmitting Antenna

Active suppression of noise and vibrations is a well established field of research with many applications in acoustic and mechanical industries. In this paper we investigate the possibility of applying these adaptive active control methods with the aim of lowering the electromagnetic power density at a specific volume in space using the superposition principle and space-time processing employing the full MIMO (Multiple Input Multiple Output) antenna system setup. The application that we evaluated is a model of a mobile phone equipped with one ordinary transmitting antenna and two actuator-antennas whichpurpose is to cancel out the electromagnetic field at the human head while maintaining a predefined level of the overall output power of the system. This power control is achieved through the use of a quadratic constraint on the active control algorithm. Simulation results show the promise of using the adaptive control algorithms and MIMO system to attenuate the electromagnetic field power density.

scholarly journals Low-Complexity Transmit Antenna Selection in Large-Scale Spatial Modulation Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Peng Wei ◽  
Lu Yin ◽  
Yue Xiao ◽  
Xu He ◽  
Shaoqian Li
Keyword(s):  
Computational Complexity ◽  
System Performance ◽  
Large Scale ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Spatial Modulation ◽  
Transmit Antenna Selection ◽  
Input Multiple Output

Transmit antenna selection (TAS) is an efficient way for improving the system performance of spatial modulation (SM) systems. However, in the case of large-scale multiple-input multiple-output (MIMO) configuration, the computational complexity of TAS in large-scale SM will be extremely high, which prohibits the application of TAS-SM in a real large-scale MIMO system for future 5G wireless communications. For solving this problem, in this paper, two novel low-complexity TAS schemes, named as norm-angle guided subset division (NAG-SD) and threshold-based NAG-SD ones, are proposed to offer a better tradeoff between computational complexity and system performance. Simulation results show that the proposed schemes can achieve better performance than traditional TAS schemes, while effectively reducing the computational complexity in large-scale spatial modulation systems.

scholarly journals Measurement-Based Spatial Correlation and Capacity of Indoor Distributed MIMO System

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Yan Zhang ◽  
Limin Xiao ◽  
Shidong Zhou ◽  
Jing Wang
Keyword(s):  
Spatial Correlation ◽  
Antenna Selection ◽  
Mimo System ◽  
Correlation Coefficients ◽  
Small Scale ◽  
Channel Measurements ◽  
Wireless Access Networks ◽  
Indoor Scenarios ◽  
Transmitting Antenna ◽  
The Impact

Distributed MIMO (D-MIMO) system is one of the candidates for future wireless access networks. In this study, the spatial correlation and capacity in indoor D-MIMO system are presented. All results are from the actual channel measurements in typical indoor scenarios, including office and corridor. Based on measured data, spatial correlation coefficients between distributed transmitting antennas are analyzed. Although the literature about D-MIMO system assumes the small scale fading between distributed antennas is independent, we find that spatial correlation may still exist in specific propagation scenario. This correlation can also degrade the performance of D-MIMO system. To mitigate the impact of spatial correlation, one efficient method is to use transmitting antenna selection technique.

scholarly journals Performance Comparison of MIMO Technology over LTE-A System

2019 ◽  
Vol 12 (1) ◽  
pp. 120-125
Author(s):  
Khalid Hussein Rashid
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Performance Metrics ◽  
Mimo System ◽  
Adaptive Modulation ◽  
Multiple Input Multiple Output ◽  
Performance Comparison ◽  
Spatial Multiplexing ◽  
Mimo Channel ◽  
Data Traffic ◽  
Maximum Throughput

Third generation partnership project (3GPP) has been introducing The Long Term Evolution (LTE) (release8) and LTE advance (LTE-A) (release 10)fourth generations as a new access technology to mobile communication in order to meet the tremendous requirement  of data traffic.   LTE-A have adopted modern techniques such as Multiple-Input Multiple Output (MIMO)and Orthogonal Frequency Division Multiplexing OFDM to satisfy all the requirements and meet the tremendous growth of data. LTE-A with MIMO system scheme based on transmission mode Close Loop Spatial Multiplexing (CLSM).CLSM  transmission modes used for doubling the bit stream and consequently increased the data rate with Adaptive modulation schemes. In this paper, The performance metrics considered are throughput. These are used to evaluate the performance of LTE-A in (AWGN) channel and Rayleigh Fading channel with detection schemes for CLSM with different band width (3, 5 and 10 MHz) and the following results has been obtained : at the same bandwidth (10 MHz) for 8x8 MIMO channel and AWGN at SNR (25dB) the maximum throughput equal(224.3 Mb/S) while in Rayleigh the throughput equal(203.8 Mb/S) . A MATLAB simulation version  R2013a has been used to complete the analysis and comparison.

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 PSO-CCO_MIMO-SA: A particle swarm optimization based channel capacity optimzation for MIMO system incorporated with smart antenna

2020 ◽  
Vol 10 (6) ◽  
pp. 6276
Author(s):  
Shivapanchakshari T. G. ◽  
H. S. Aravinda
Keyword(s):  
Particle Swarm Optimization ◽  
Channel Capacity ◽  
Power Efficiency ◽  
Smart Antenna ◽  
Antenna Selection ◽  
Mimo System ◽  
Particle Swarm ◽  
Spatial Diversity ◽  
Mimo Channel ◽  
Swarm Optimization

With the radio channels physical limits, achieving higher data rate in the multi-channel systems is been a biggest concern. Hence, various spatial domain techniques have been introduced by incorporating array of antenna elements (i.e., smart antenna) in recent past for the channel limit expansion in mobile communication antennas. These smart antennas help to yield the improved array gain or bearm forming gain and hence by power efficiency enhanmaent in the channel and antenna range expansion. The use of smart antenna leads to spatial diversity and minimizes the fading effect and improves link reliability. However, in the process of antenna design, the proper channel modelling is is biggest concern which affect the wireless system performance. The recent works of MIMO design systems have discussed the issues in number of antenna selection which suggests that optimization of MIMO channel capacity is required. Hence, a Particle Swarm Optimization based channel capacity optimzation for MIMO system incorporated with smart antenna is introduced in this paper. From the outcomes it is been found that the proposed PSO based MIMO system achieves better convergenece speed which results in better channel capacity.

PERFORMANCE ANALYSIS OF SPATIAL MODULATION IN MIMO- A SURVEY

2015 ◽  
Vol 2 (2) ◽  
Author(s):  
PILITHA CHANDRAN K ◽  
C.D. SURIYAKALA
Keyword(s):  
Data Transmission ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Main Idea ◽  
Time Instant ◽  
Antenna System ◽  
Spatial Modulation ◽  
Modulation Scheme ◽  
Mimo Antenna

Spatial modulation (SM) is a recently developed transmission technique that uses index of antenna in a multiple input multiple output (MIMO) antenna system, as additional means of data transmissions. The use of index of the active antennas at any time instant is the main idea behind spatial modulation. The information bits to be transmitted are divided into two parts. The first part is mapped to a symbol chosen from the signaling constellation, where depending on modulation scheme the number of bits per symbol varies. The second part determines the antenna index to be selected from a set of antennas available for data transmission. Thereby increases the spectral efficiency and decreases the complexity at receiver section. The rate of data transmission can much more increased by mapping into subsets of antennas in MIMO. The paper summarizes some of the recent works and issues of SM MIMO. The antenna selection in spatial modulation mainly depends on the incoming information data which is unlike the antenna selection in conventional MIMO system which depends on the channel state information (CSI) and the received signal strength.

Sign in / Sign up

Export Citation Format

Share Document