scholarly journals Statistical mechanical analysis of the Kronecker channel model for multiple-input multiple-output wireless communication

2009 ◽  
Vol 80 (6) ◽  
Author(s):  
Atsushi Hatabu ◽  
Koujin Takeda ◽  
Yoshiyuki Kabashima
Keyword(s):  
Wireless Communication ◽  
Channel Model ◽  
Multiple Input Multiple Output ◽  
Mechanical Analysis ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Statistical Mechanical

scholarly journals MIMO Fading Emulator Development with FPGA and Its Application to Performance Evaluation of Mobile Radio Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Yoshio Karasawa ◽  
Katsuhiro Nakada ◽  
Guijiang Sun ◽  
Rikako Kotani
Keyword(s):  
Channel Model ◽  
Multiple Input Multiple Output ◽  
New Developments ◽  
Performance Limit ◽  
Stage Scheme ◽  
Mobile Radio Systems ◽  
Multiple Input ◽  
Field Programmable ◽  
Input Multiple Output ◽  
Radio Systems

We present four new developments for a multiple-input multiple-output (MIMO) over-the-air measurement system based on our previous studies. The first two developments relate to the channel model for multipath environment generation. One is a further simplification of the circuit configuration without performance degradation by reducing the number of delay generation units, which dominate the performance limit when implementing the circuit on a field-programmable gate array (FPGA). The other is to realize spatial correlation characteristics among the input ports on the transmission side, whereas the previously proposed channel model did not consider this correlation. The third development involves the details of implementing the MIMO fading emulator on an FPGA as a two-stage scheme. The fourth is the demonstration of application examples of the developed system.

scholarly journals Gaussian MIMO relay channel with orthogonal channel components

2020 ◽  
Vol 71 (3) ◽  
pp. 222-226
Author(s):  
Zouhair Al-qudah
Keyword(s):  
Channel Model ◽  
Multiple Input Multiple Output ◽  
Relay Channel ◽  
Numerical Examples ◽  
Mimo Relay ◽  
Multiple Input ◽  
Communication Devices ◽  
Input Multiple Output ◽  
Theoretical Results

AbstractThe Gaussian multiple-input multiple-output (MIMO) orthogonal relay channel (ORC) is investigated. The transmission from source to relay is done over a channel that is orthogonal to source-destination and relay-destination channels. Practically, this assumption is made such that many communication devices from different technologies are exploited in relaying the source’s signal into its destination. For this channel model, the capacity is initially derived. Thereafter, we propose a transmission algorithm to achieve the derived capacity. Further, to support our theoretical results, many numerical examples are presented.

scholarly journals Massive MIMO and Hybrid Optimization for It's Beamforming

2019 ◽  
Vol 8 (3) ◽  
pp. 7692-7698
Keyword(s):  
Wireless Communication ◽  
High Throughput ◽  
Communication System ◽  
High Speed ◽  
Multiple Input Multiple Output ◽  
Research Work ◽  
Network Capacity ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Technology

The tremendous growth of traffic in wireless communication (WC) system has resulted in inadequate network capacity. 5th Generation (5G) is seen as next generation wireless communication system implemented with massive multiple-input multiple-output (M-MIMO) technology. It will play major role in future communication system. M-MIMO objective is high throughput and high speed. Beamforming technique is a key to high throughput objective - achieved by reduction in errors occurring in data transmission and reception. The intent of this research paper is to review - beam forming techniques implemented in M-MIMO and research work in this particular area. Paper classifies optimized beamforming techniques in detail for determining appropriate techniques that can be deployed in M-MIMO. Understanding limitations of present techniques and suggesting new approach for better throughput is outcome of retrospective analysis.

A Review of Massive Multiple Input Multiple Output for 5G Communication: Benefits and Challenges

2020 ◽  
Vol 1 (1) ◽  
pp. 22-26
Author(s):  
Shaik Nilofer ◽  
Keyword(s):  
Wireless Communication ◽  
Channel Capacity ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
System Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Primary Advantage ◽  
Time Division

Massive MIMO (mMIMO) systems become a primary advantage to overcome the problem of bandwidth restrictions. It improves the channel capacity of remote systems.The paper reviews about mMIMO systems. mMIMO consists of several number of antennas at base station (BS) which improves spectrum efficacy. The extra benefit of the mMIMO system is that the components cost is low because of utilization of less power components. The paper also discusses about the channel estimation at the BS and generally time division mode (TDD) is assumed for mMIMO systems. The paper also discusses system model, benefits for 5G wireless communication and its challenges.

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