An Adaptive Bayesian Computation Model for CDMA Multiuser Detection using Evolutionary Computation Scheme Nirmaladevi R.1, Rao K. Kishan2 1Dept. of Electronics & Instrumentation Engineering, KITS, Warangal, Andhra Pradesh, India 2Dept. of Electronics & Communication Engineering, Vaagdevi Group of institutions, Andhra Pradesh, India Online published on 4 June, 2019. Abstract Demand of wireless communication is increasing drastically where CDMA (Code Division Multiple Access) is considered as most promising technique for real-time communication. However, due to extreme utilization of these technologies several challenges occur such as interference and packet drop resulting in poor communication. To address these issues, multi-user detection schemes have been adopted widely which are based on the filtering techniques and MMSE (Minimum Mean Square Error) based multiuser detection schemes. In this work we address these issues and proposed a novel approach of multi-user detection for asynchronous CDMA using combined optimization and evolutionary computation. Bayesian computation model is applied which helps to compute the Log Likelihood Ratio (LLR) using Monte Carlo simulation. Later genetic algorithm is incorporated to obtain the optimal solution for LLR probability resulting in reliable communication. An extensive simulation study is presented which shows significant improvement in the performance when compared with state-of-art multiuser detection schemes. Top Keywords CDMA, Multiple access interference (MAI), Multi user detection, Bayesian Model, evolutionary computation, Log-Likelihood ratio. Top |