Low-Complexity MAP Detection and Decoding to Improve BER Performance of Satellite Broadcasting Systems With LDM

Abstract

This paper proposes low-complexity detection and decoding based on the maximum $a$ posteriori (MAP) criterion for satellite broadcasting systems that use layered division multiplexing (LDM). The first component of this scheme exploits pilot signals to compensate for nonlinear distortion caused by satellite transponders. Specifically, received data signals suffer from nonlinear distortion and are classified into several bit-dependent clusters, of which the centroids can be obtained from the corresponding received pilot signals. The distance between each centroid and a received data signal yields the log likelihood ratio (LLR) of each data bit with sufficient accuracy. Since this component can almost nullify the nonlinear distortion, it is expected to outperform conventional successive interference cancellation (SIC), which has been widely used with the LDM system. To further improve LDM performance, the second component of the proposed scheme performs iterative decoding that reduces the otherwise prohibitive computational complexity in the MAP decoding. To cope with the short-loop issue inherent in the iterative decoding for LDM, the decoding process and associated parameters are optimized on the basis of numerical analyses. Specifically, a new decoding scheme that uses the $a$ posteriori LLR as a criterion is derived from an analysis of the relationship between prior and extrinsic information in iterative decoding. This scheme can determine whether specific extrinsic information should be used for the iterative decoding or not. Numerical analyses also show how inter-layer interference dominance depends on the inter-layer power ratio and how the resulting LLR reliability affects the decoding performance in LDM. Computer simulations over nonlinear channels created by emulating actual satellite transponder characteristics demonstrate that the pilot-aided compensation (the first component) can successfully mitigate the nonlinear distortion, while the optimized iterative decoding (the second component) can further improve the bit error rate (BER).