Mohammed, Saif K. ; Zaki, Ahmed ; Chockalingam, A. ; Rajan, B. Sundar (2009) High-rate space–time coded large-MIMO systems: low-complexity detection and channel estimation IEEE Journal of Selected Topics in Signal Processing, 3 (6). pp. 958-974. ISSN 1932-4553
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Official URL: http://ieeexplore.ieee.org/document/5370678/
Related URL: http://dx.doi.org/10.1109/JSTSP.2009.2035862
Abstract
In this paper, we present a low-complexity algorithm for detection in high-rate, non-orthogonal space-time block coded (STBC) large-multiple-input multiple-output (MIMO) systems that achieve high spectral efficiencies of the order of tens of bps/Hz. We also present a training-based iterative detection/channel estimation scheme for such large STBC MIMO systems. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed multistage likelihood ascent search (M-LAS) detector in conjunction with the proposed iterative detection/channel estimation scheme at low complexities. The fact that we could show such good results for large STBCs like 16×16 and 32×32 STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot based training for channel estimation and turbo coding) establishes the effectiveness of the proposed detector and channel estimator. We decode perfect codes of large dimensions using the proposed detector. With the feasibility of such a low-complexity detection/channel estimation scheme, large-MIMO systems with tens of antennas operating at several tens of bps/Hz spectral efficiencies can become practical, enabling interesting high data rate wireless applications.
Item Type: | Article |
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Source: | Copyright of this article belongs to Institute of Electrical and Electronics Engineers. |
Keywords: | Non-Orthogonal Space–time Block Codes; Channel Estimation; High Spectral Efficiencies; Large-Multiple-Input Multiple-Output (MIMO) Systems; Low-Complexity Detection |
ID Code: | 100675 |
Deposited On: | 28 Mar 2017 09:22 |
Last Modified: | 28 Mar 2017 09:22 |
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