Efficient Detection for MIMO Systems Based on Gradient Search

Ming Xian Chang, Wang Yueh Chang

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Multiple-input-multiple-output (MIMO) technology can efficiently use the spectrum to increase the communication throughput. Designing low-complexity detection algorithms with high performance for the MIMO system has been an important issue. In this paper, we propose efficient detection algorithms for MIMO systems based on differential metrics. We first define differential metrics and give their recursive calculation of different orders. Based on differential metrics, we give the principle of gradient search. We then propose a gradient search algorithm (GSA) that can provide a tradeoff between performance and complexity. The GSA applies the indicative functions such that we can determine in advance some maximum-likelihood (ML) bits of the initial sequence and reduce the searching range. The GSA also uses a stop condition with which we can stop the search if the proper condition is satisfied. The GSA does not need QR decomposition (QRD) or matrix inversion. The multiplicative operations are only necessary before the searching process, during which only the additive operations are needed. For large-scaled MIMO systems, we also give a simple searching algorithm based on differential metrics. Finally, we propose a fixed-complexity gradient algorithm (FCGA), which has a fixed number of operations during the searching process and is appropriate for pipelined hardware implementation. The simulation results validate the efficiency of the proposed algorithms.

Original languageEnglish
Article number7457318
Pages (from-to)10057-10063
Number of pages7
JournalIEEE Transactions on Vehicular Technology
Volume65
Issue number12
DOIs
Publication statusPublished - 2016 Dec

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Applied Mathematics

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