Reduced Complexity Decoding for Bit-Interleaved Coded Multiple Beamforming with Constellation Precoding

TL;DR

This paper proposes a sphere decoding-based method to significantly reduce the decoding complexity of BICMB-CP, enabling full diversity achievement without high computational costs.

Contribution

It introduces a reduced complexity decoding technique for BICMB-CP using Sphere Decoding, outperforming traditional ML and SD methods in efficiency.

Findings

Achieves several orders of magnitude reduction in decoding complexity.

Enables full diversity without the condition RcS<=1.

Significantly decreases average real multiplications needed for decoding.

Abstract

Multiple beamforming is realized by singular value decomposition of the channel matrix which is assumed to be known to both the transmitter and the receiver. Bit-Interleaved Coded Multiple Beamforming (BICMB) can achieve full diversity as long as the code rate Rc and the number of employed subchannels S satisfy the condition RcS<=1. Bit-Interleaved Coded Multiple Beamforming with Constellation Precoding (BICMB-CP), on the other hand, can achieve full diversity without the condition RcS<=1. However, the decoding complexity of BICMB-CP is much higher than BICMB. In this paper, a reduced complexity decoding technique, which is based on Sphere Decoding (SD), is proposed to reduce the complexity of Maximum Likelihood (ML) decoding for BICMB-CP. The decreased complexity decoding achieves several orders of magnitude reduction, in terms of the average number of real multiplications needed to acquire one precoded bit metric, not only with respect to conventional ML decoding, but also, with respect to conventional SD.