Fractionally Spaced Constant Modulus Algorithm for Wireless Channel Equalization

Abstract

Abstract-Wireless channel identification and equalization is one of the most challenging tasks because broadcast channels are often subject to frequency selective, time varying fading and there are several bandwidth limitations. Furthermore, each receiver channel has vastly different types of channel characteristics and signals to noise ratio. Here in this paper we consider channel equalization and estimation problem from trans-receiver perspective, specifically we try to estimate blind equalization schemes particularly using constant modulus Algorithm (CMA). We try to estimate a linear channel model driven by a QAM source and adapt a FSE (T /2) using CMA. It has been shown CMA-FSE successfully reduces the cluster variance so that transfer to a decision directed mode is possible and simultaneously error is reduced.

Adaptive Turbo-Equalizer Design for Multi-User Mobile Communication Channel

“…For the model of a wireless mobile communication channel [15][16][17][18] to be realistic, it has to include many aspects, fading phase & frequency distortion, inter-symbol, co-channel & multiple access interference, near far cross talk as well as colored and white noise also influences a transmitter [19,21,24]. Here we will model only AWGN & ISI referred in Fig.…”

“…The signal r is thus processed by an adaptive equalizer, consisting of LMS or NLMS algorithm [25] & leads to estimation ofx CDMA . Next a matched filter adjusted to users spreading sequences & estimates [12][13][14][15] the modulation symbols of this userx QAM,1 . Simultaneously one user is selected in the Logmap among the user of interest.…”