Improving Interference Cancellation in Spatial Division Multiplexing Using a Combination of the Channel Coding and QR-Successive Interference Cancellation

Abstract

This paper introduces QR-SIC detector to minimize the probability of error comparing to SDM system. Spatial-division-multiplexing (SDM) system is a multiple-inputs-multiple-outputs (MIMO) system used to increase data transmission rate in modern communication systems. The major disadvantage of SDM system is the interference between the received symbols. In this paper, a new trans-receiver architecture for SDM system is introduced. This receiver uses a Successive-Interference-Cancellation (SIC) detector based on QR-decomposition of the channel matrix and a Forward-Error- Correction (FEC) channel code. The proposed architecture merges the interference cancellation process in QR-SIC detector and the forward error correction process in the channel decoder. The feedback symbols in the QR-SIC detector are the output symbols from the channel decoder after they are re-encoded and re-modulated and more robust. The new architecture minimizes the probability of error in the demodulated symbols more than the conventional SDM receiver. If the conventional SDM receiver needs 100 MWATT transmitted power the proposed system needs only 64 MWATT transmitted power. So The new architecture of the SDM receiver can save up to 36% of the transmitted signal power used with the conventional SDM receiver. At BER of 10-4, the convolution codes of code rates 3/4, 1/2, and 1/4 achieve coding gains of 15 dB, 24 dB, and 30 dB with respect to the uncoded 4-antennas SDM receiver. the proposed SDM receiver at BER of 10-4 is 2dB, 1.5 dB, and 0.9 dB better than the BER performance of the conventional coded SDM receiver at the same code rates and the same number of antenna. The enhancement in the BER performance of the proposed SDM receiver increases as the code gain of the used code. This increase in the power efficiency and bandwidth comes at the expense of an increase in the receiver complexity and latency