A high-parallelism detection algorithm for massive MIMO systems
- Resource Type
- Conference
- Authors
- Li, Huan; Zhao, Xuying; Guo, Chen; Wang, Donglin
- Source
- 2017 7th IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC) Electronics Information and Emergency Communication (ICEIEC), 2017 7th IEEE International Conference on. :83-86 Jul, 2017
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Robotics and Control Systems
Signal Processing and Analysis
Approximation algorithms
Complexity theory
MIMO
Parallel processing
Signal processing algorithms
Detection algorithms
Convergence
Massive MIMO
Signal Detection
High Parallelism
Matrix Blocking
- Language
- ISSN
- 2377-844X
Due to the asymptotically orthogonal channel, minimum mean square error detection algorithm is near-optimal for uplink massive MIMO systems, but it involves matrix inversion with high complexity. This paper proposes a high-parallelism detection algorithm in an iterative way to avoid the complicated matrix inversion. The parallelism level is analyzed and convergence is proved in detail. The proposed algorithm can be implemented in a high level, which is equal to the max number of received data streams. The complexity can be reduced by one order of magnitude comparing with MMSE algorithm. Simulation results show that the proposed algorithm can closely match the performance of the MMSE algorithm with few number of iterations. It also outperforms Neumann Series approximation algorithm in terms of block error rate (BLER) performance with same number of iterations.