Staffordshire University logo
STORE - Staffordshire Online Repository

Compressed Sensing of Sparse Multipath MIMO Channels with Superimposed Training Sequence

Amin, Bilal, Mansoor, Babar, Nawaz, Syed Junaid, Sharma, Shree Krishna and PATWARY, Mohammad (2016) Compressed Sensing of Sparse Multipath MIMO Channels with Superimposed Training Sequence. Wireless Personal Communications. ISSN 0929-6212

11277_WIRE-D-15-01230_WPC.pdf - AUTHOR'S ACCEPTED Version (default)

Download (1MB) | Preview

Abstract or description

Recent advances in multiple-input multiple-output (MIMO) systems have renewed the interests of researchers to further explore this area for addressing various dynamic challenges of emerging radio communication networks. Various measurement campaigns reported recently in the literature show that physical multipath MIMO channels exhibit sparse impulse response structure in various outdoor radio propagation environments. Therefore, a comprehensive physical description of sparse multipath MIMO channels is presented in first part of this paper. Superimposing a training sequence (low power, periodic) over the information sequence offers an improvement in the spectral efficiency by avoiding the use of dedicated time/frequency slots for the training sequence, which is unlike the traditional schemes. The main contribution of this paper includes three superimposed training (SiT) sequence based channel estimation techniques for sparse multipath MIMO channels. The proposed techniques exploit the compressed sensing (CS) theory and prior available knowledge of channel’s sparsity. The proposed sparse MIMO channel estimation techniques are named as, SiT based compressed channel sensing (SiT-CCS), SiT based hardlimit thresholding with CCS (SiT-ThCCS), and SiT training based match pursuit (SiT-MP). Bit error rate (BER) and normalized channel mean square error (NCMSE) are used as metrics for the simulation analysis to gauge the performance of proposed techniques. A comparison of the proposed schemes with a notable first order statistics based SiT least squares (SiT-LS) estimation technique is presented to establish the improvements achieved by the proposed schemes. For sparse multipath time-invariant MIMO communication channels, it is observed that SiT-CCS, SiT-MP, and SiT-ThCCS can provide an improvement up to 2 dB, 3.5 dB, and 5.2 dB in the MSE at signal to noise ratio (SNR) of 12 dB when compared to SiT-LS, respectively. Moreover, for BER = 10−1.9 , the proposed SiT-CCS, SiT-MP, and SiT-ThCCS, compared to SiT-LS, can offer a gain of about 1 dB, 2.5 dB, and 3.5 dB in the SNR, respectively. The performance gain in MSE and BER is observed to improve with an increase in the channel sparsity.

Item Type: Article
Faculty: Previous Faculty of Computing, Engineering and Sciences > Engineering
Depositing User: Mohammad PATWARY
Date Deposited: 30 Sep 2016 15:51
Last Modified: 24 Feb 2023 13:43

Actions (login required)

View Item View Item

DisabledGo Staffordshire University is a recognised   Investor in People. Sustain Staffs
Legal | Freedom of Information | Site Map | Job Vacancies
Staffordshire University, College Road, Stoke-on-Trent, Staffordshire ST4 2DE t: +44 (0)1782 294000