Abstract
We propose a joint MAP channel estimation and data detection technique based on the expectation maximization (EM) method with paralel interference cancelation (PIC) for downlink multicarrier (MC) code division multiple access (CDMA) systems in the presence of frequency selective channels. The quality of multiple access interference (MAI), which can be improved by using channel estimation and data estimation of all active users, affects considerably the performance of PIC detector. Therefore, data and channel estimation performance obtained in the initial stage has a significant relationship with the performance of PIC. So obviously it is necessary to make excellent joint data and channel estimation for initialization of PIC detector. The EM algorithm derived estimates the complex channel parameters of each subcarrier iteratively and generates the soft information representing the data a posterior probabilities. The soft information is then employed in a PIC module to detect the symbols efficiently. Moreover, the MAP-EM approach considers the channel variations as random processes and applies the Karhunen-Loeve (KL) orthogonal series expansion. The performance of the proposed approach is studied in terms of bit-error rate (BER) and mean square error (MSE). Throughout the simulations, extensive comparisons with previous works in literature are performed, showing that the new scheme can offer superior performance.
Highlights
Traditional wireless technologies are confronted with new challenges in meeting the ubiquity and mobility requirements of cellular systems
In this work we have presented an efficient expectation maximization (EM)-maximum a posteriori (MAP) channel-estimation-based paralel interference cancelation (PIC) receiver structure for downlink MC-code division multiple access (CDMA) systems
This algorithm performs an iterative estimation of the channel according to the MAP criterion, using the EM algorithm employing MPSK modulation scheme with additive Gaussian noise
Summary
Traditional wireless technologies are confronted with new challenges in meeting the ubiquity and mobility requirements of cellular systems. The major contribution of the paper is to obtain EM-based channel estimation algorithm approach as opposed to the existing works in the literature which mostly assumed that the data is known at the receiver through a training sequence. The proposed EM-MAP receiver compared with the combined MMSE-PIC receiver in the case of LS, LMMSE, and perfect channel estimation [4] Another significant contribution of the paper comes from the fact that the proposed approach considers the channel variations as random processes and applies the Karhunen-Loeve (KL) orthogonal series expansion. It was shown that KL expansion enable us to estimate the channel in a very simple way without taking inverse of largedimensional matrices for OFDM system [11, 12] Notation: Vectors (matrices) are denoted by boldface lower (upper) case letters; all vectors are column vectors; (·)T , (·)† and (·)−1 denote the transpose, conjugate transpose, and matrix inversion, respectively; IL denotes the L × L identity matrix; diag{·} denotes a diagonal matrix
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
