A Technique for Multi-User MIMO using Spatial Channel Model for out-door environments

TL;DR

This paper develops a multi-user MIMO spatial channel model for outdoor environments, implementing it in MATLAB to evaluate parameters like angle of arrival, user distance, and BER performance with various techniques.

Contribution

The paper introduces a MATLAB implementation of a multi-user MIMO spatial channel model for outdoor environments, incorporating BER improvement techniques and analyzing multi-channel diversity effects.

Findings

BER performance improves with Viterbi-decoder, interleaving, and multiple antennas.

Multi-channel diversity enhances signal robustness in outdoor MIMO systems.

Different modulation techniques impact BER performance significantly.

Abstract

Any wireless communication system needs to specify a propagation channel model which acts as basis for performance evaluation and comparison. Spatial channel models can be divided into deterministic i.e ray tracing, measurement based which is based on channel information and geometry based stochastic channel models which are based on assumption that directional structure of channel can be modelled by last interaction between physical objects and electromagnetic waves, before waves reach the base or mobile station. Multi user double directional channel model (MDDCM) is a geometry based channel model which is used to calculate the double directional channel information in cellular system with MIMO mobile station and MIMO base station. In this research phase firstly, Multi User Multiple Input Multiple Output (MU-MIMO) spatial channel model has been implemented for different outdoor environments Urban Micro and Urban Macro using MATLAB for finding various parameters like angle of arrival of the user, user direction and the distance between user and access point (AP). Secondly coded (Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing) MIMO-OFDM system has been implemented using multipath Rayleigh faded channel and realistic Spatial Channel Model. Different BER improvement techniques are used such as, Viterbi-decoder, Time and Frequency inter-leaving. Multi-channel diversity is also observed by using multiple antennas at transmitting and receiving end [(2x2) and (2x4)] on both the channels. Effect of different modulation techniques on BER performance is also observed.