For massive MIMO system uplink

conventional minimum mean square error (MMSE) linear detection algorithm can achieve nearly optimal performance

but it involves complicated matrix inversion. A low-complexity detection algorithm based on Kaczmarz method is proposed in this paper

which can circumvent the matrix inverse operation and hence reduce the complexity from

O

(

K

3

) to

O

(

K

2

). Meanwhile

an optimal relaxation parameter is introduced to further accelerate the algorithm convergence

and two approximate methods of log-likelihood ratios (LLR) estimation for channel decoding are g

iven as well. Simulation results verify that the proposed algorithm outperforms the Neumann series expansion algorithms on both bit error ratio (BER) and computational complexity. It converges rapidly and achieves its performance quite close to that of the MMSE algorithm with only a small number of iterations.