Joint Detection And Decoding For MIMO Systems:Algorithms And Architecture

With multiple transmission and receiving antennas,multiple-input multiple-output(MIMO)has been widely used in modern wireless communication systems.In order to make most use of the capability of diversity and multiplexing for MIMO systems,the number of transmission and receiving antennas has risen from tens to hundreds.In5 G systems,this number has reached 128 which is much bigger than the one for traditional MIMO systems.The cooperative MIMO systems group several base stations into a large server to handle all signals from different users.This technique achieves meaningful performance gains but it also increases the computational complexity of signal recovery.The inter-user and iter-signal interference increase with the number of antennas.And the large amount of processing data affect the performance and processing speed of the base stations.Under this situation,the detection algorithms and decoders for traditional MIMO systems can not meet the requirement of the modern wireless communication systems.Therefore,many researchers have drawn attention to the joint detection and decoding(JDD)systems which combines the detection with the decoding process.The performance gains of JDD systems are obvious but the high computational complexity and processing latency are still unsolved.In this paper,we review the basic knowledge of MIMO systems,channel encoder,MIMO detection and the JDD systems.We propose a novel optimized algorithm which adopts K-best detection and the linear block codes.The cyclic redundancy check(CRC)code is also used in the proposed algorithm to check the stored paths.With matlab simulation and ASIC results,this paper proves that the proposed system has outstanding performance gains and efficient hardware architecture.The proposed system is hardware-friendly with low computational complexity,which is expected to achieve a high performance with a low latency.