Low Complexity MIMO Receivers

Bai, Lin; Choi, Jinho; Yu, Quan

doi:10.1007/978-3-319-04984-7

Cited by 23 publications

(12 citation statements)

References 81 publications

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“…Hence, in order to make this scenario possible under wideband assumption, we are proposing an algorithm, where it is assumed that we have complete knowledge of the channel matrix. It is clear from the Eqns.7 and 10, that a well-conditioned channel is needed for the better performance [5]. Thus, from all of the multipath channel instances, it is desired to select one best multipath component which improves the detector performance.…”

Section: Proposed Methods Of Detectionmentioning

confidence: 98%

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MIMO signal detection in multipath environment

Kumar

Pandey

Bajpai

et al. 2015

2015 IEEE UP Section Conference on Electrical Computer and Electronics (UPCON)

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This paper presents the technique to resolve multipath component at the receiver under the assumption of wideband channel. It has been proved that linear receivers show low complexity to detect MIMO signals. An algorithm is proposed to select the best multipath component of the transmitted signal in the presence of a linear Zero Forcing detector. On the basis of QR decomposition of the received multipath component and corresponding channel matrices, the proposed algorithm will select the maximum projection valued multipath component. Simulation results for various antenna configurations using different modulation techniques show significant improvement than the conventional detection approach.

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Section: Proposed Methods Of Detectionmentioning

confidence: 98%

“…The performance of ML detector can be evaluated by Pairwise Error Probability which is upper bounded as [5] P (s s ) ( 8 )…”

Section: Maximum Liklihood Detectormentioning

confidence: 99%

MIMO signal detection in multipath environment

Kumar

Pandey

Bajpai

et al. 2015

2015 IEEE UP Section Conference on Electrical Computer and Electronics (UPCON)

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“…However, at lower SNR, the OD becomes a more suitable choice. Fundamental complexity concepts are provided in [13] while more related complexity discussions are found in [1,2,14] and is not repeated here. The information theory-based calculation of the SM capacity carried out in this work confirms and approves this fact.…”

Section: Discussionmentioning

confidence: 99%

Performance Comparison of Spatial Modulation Detectors under Channel Impairments

Soujeri

Kaddoum

2015

2015 IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB)

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Abstract-Spatial modulation (SM) is a multiple antenna transmission approach that uses the index of the transmitting antenna for delivering information data. The choice on the transmitting antenna depends on the incoming bit sequence and has a random nature. The receiver estimates the transmitted symbol and the active transmit antenna index and uses both estimations to retrieve the original information bits. For best reception, individual channel links between transmit and receive antenna pairs must be unique. In fact, correct reception totally depends on the uniqueness of channel coefficients. Incorrectly interpreting channel state information at the receiver causes the BER performance to degrade and the detection to fall short. In this paper, we develop a channel model that incorporates both correlated and imperfect channel state information and use this model to study the bit-error-ratio (BER) performance of most widely used SM detectors, namely the minimum mean square error, the maximum likelihood and the optimum detector in flat Rayleigh fading channels to examine the sensitivity these detectors exhibit to the presence of either channel correlation or imperfect channel state information. The capacity of SM system is studied in comparison to other multiple-input multiple-output techniques and the influence of channel impairments on the overall system capacity is observed.

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“…The optimal detection problem in the sense of minimum joint probability or error for detecting all the symbols simultaneously is solved by the ML detector, which is known as NP-hard [1]. It can be implemented by a brute force-search over all of the possible transmitted vectors set, searching for the one that minimizes the Euclidean distance from the received vector, or using more efficient search algorithms, i.e, the sphere decoder (SD) [1], [2]. However, the expected computational complexity of the ML receiver, even when SD is applied, is unpractical for many channel scenarios and applications.…”

Section: Introductionmentioning

confidence: 99%

“…However, the expected computational complexity of the ML receiver, even when SD is applied, is unpractical for many channel scenarios and applications. Consequently, there has been much interest in implementing sub-optimal or quasi-optimal MIMO detection algorithms, such as the linear receivers, i.e, the zero-forcing (ZF) and the minimum mean squared error (MMSE) MIMO detectors [1].…”

Section: Introductionmentioning

confidence: 99%

Semidefinite Relaxation for Large Scale MIMO Detection

Negrão¹,

Mussi²,

Abrão³

2016

Anais De XXXIV Simpósio Brasileiro De Telecomunicações

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The semi-definite relaxation (SDR) is a high performance efficient approach to MIMO detection especially for low modulation orders. We focus on developing a computationally efficient approximation of the maximum likelihood detector (ML) algorithm based on semi-definite programming (SDP) for M-QAM constellations. The detector is based on a convex relaxation of the ML problem. A comparative analysis including the performance-complexity trade-off of the SDR and the lattice reduction (LR) aided linear MIMO detectors considering high number of antennas is carried out aiming to demonstrate the effectiveness of the SDR-based conventional and large scale MIMO detector. SDR-MIMO detector can provide a close, and under high order antennas cases, a better performance than the LR-aided linear MIMO detectors.

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Low Complexity MIMO Receivers

Cited by 23 publications

References 81 publications

MIMO signal detection in multipath environment

MIMO signal detection in multipath environment

Performance Comparison of Spatial Modulation Detectors under Channel Impairments

Semidefinite Relaxation for Large Scale MIMO Detection

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