Channel Estimation for DS-CDMA Rake Receiver using Sparse Recovery Approach

Abstract

In the literature of direct-sequence code-division multiple-access (DS-CDMA), for issues related to channel estimation, some exclusive architectures have been proposed, which are characterized by known channel noise statistics and noise observation. But in reality, the channel parameters are frequently assessed utilizing training sequences that lead to difficulty in obtaining the channel noise statistics. Channel estimation quality has been proved to play an important role in the performance of rake receiver. This paper addresses the issues of optimizing DS–CDMA rake receiver channel estimation equipped with an Iterative least square sparse recovery (IL2SR) channel estimator. Moreover, the ambient noises corrupt the signal received and multiple-access interference further aggravates it. Because of this observation noises become hard to acquire. Hence this paper proposes as an iterative least square structure for channel estimation algorithm in rake receiver employed in DS-CDMA communication systems. Further, examination of blind channel estimation problem for rake-based DS-CDMA communication framework having multi-path fading channels with time variation is also attempted. The validity of the proposed techniques has been verified through results obtained from simulation for different channel parameters and spreading codes. Further exploration has been carried out with execution of the IL2SR with Rake receiver in DS-CDMA framework for multi-path fading channels. It is found that better performance is obtained with this framework under various channels with different spreading codes. The proposed system is compared with Kalman based techniques and it was found that DS-CDMA framework under additive white gaussian noise (AWGN)channel with IL2SR receiver reveals better outcomes in terms of bit error rate (BER). Also, there has been improvement in video quality while using the proposed IL2SR receiver with increase in the values of ratio of signal to noise ratio.