In MIMO (multiple-input, multiple-output) systems, signals from differenttransmitting antennas interfere at each receiving antenna and multiuser detection (MUD)algorithms may be adopted to improve the system performance. This paper proposes anovel multiuser detection algorithm in MIMO systems based on the idea of “beliefpropagation” which has achieved great accomplishment in decoding of low-densityparity-check codes. The proposed algorithm has a low computation complexityproportional to the square of transmitting/receiving antenna number. Simulation resultsshow that under low signal-to-noise ratio (SNR) circumstances, the proposed algorithmoutperforms the traditional linear minimum mean square error (MMSE) detector while itencounters a “floor’ of bit error rate under high SNR circumstances. So the proposedalgorithm is applicable to MIMO systems with channel coding and decoding. Although inthis paper the proposed algorithm is derived in MIMO systems, obviously it can be appliedto ordinary code-division m In MIMO (multiple-input, multiple-output) systems, signals from different transmissmitting antennas interfere at each receiving antenna and multiuser detection (MUD) algorithms may be adopted to improve the system performance. This paper proposes anovel multiuser detection algorithm in MIMO systems based on the idea of ​​ ”beliefpropagation “ which has achieved great accomplishment in decoding of low-density parity-check codes. The proposed algorithm has a low computation complexityproportional to the square of transmitting / receiving antenna number. Simulation resultsshow that under low signal-to- noise ratio (SNR) cases, the proposed algorithm outperforms the traditional linear minimum mean square error (MMSE) detector while itencounters a ”floor ’of bit error rate under high SNR conditions. So the proposed algorithm is applicable to MIMO systems with channel coding and decoding Although inthis paper the proposed algorithm is derived in MIMO systems, obviously it can be applied to ord inary code-division m