An Efficient Decoding Algorithm for STBC with Multi-dimensional Rotated Constellations

Lee, Heunchul; Cho, Jungho; Kim, Jong-Kyu; Lee, Inkyu

doi:10.1109/icc.2006.255547

Cited by 19 publications

(42 citation statements)

References 16 publications

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“…The complexity of the decoding algorithm proposed in [23] is in the order O(L N/4 ) which is equal to the complexity of the algorithm presented in [26] and will be denoted C [23], [26] in the sequel. In Table I, we give a comparison between ML, algorithms in [23] and [26], and PR in terms of the number of real multiplications and real additions considering N = 4 for different constellation sizes. The number of multiplications and additions shown include the computation of QR andȳ = Q Hỹ .…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Note that this simplification is obtained through the orthogonality properties in (13) and the QR decomposition in (14), resulting in (15) and (16). This is similar to but simpler than [23] and [26] in that all have joint detection of two real symbols (N/2 times in [23] and [26] and n s times in this work) but with minimizing a norm of size 2N in [23] and [26] while minimizing a norm of size 2 in this work. This means that the original complex ML problem is decomposed into n s = 4 parallel real-valued upper triangular problems, each of dimension 2.…”

mentioning

confidence: 89%

“…Obviously, this approach allows finding the ML solution faster, and requires a small number of computational operations compared to conventional ML, and decoding algorithms proposed in [23] and [26].…”

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confidence: 99%

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Reduction of ML decoding complexity for MIMO Sphere Decoding, QOSTBC, and OSTBC

Azzam

Ayanoğlu

2008

2008 Information Theory and Applications Workshop

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Abstract-In this paper, we discuss three applications of the QR decomposition algorithm to decoding in a number of MultiInput Multi-Output (MIMO) systems. In the first application, we propose a new structure for MIMO Sphere Decoding (SD). We show that the new approach achieves 80% reduction in the overall complexity compared to conventional SD for a 2 × 2 system, and almost 50% reduction for the 4 × 4 and 6 × 6 cases. In the second application, we propose a low complexity Maximum Likelihood Decoding (MLD) algorithm for quasiorthogonal space-time block codes (QOSTBCs). We show that for N = 8 transmit antennas and 16-QAM modulation scheme, the new approach achieves > 97% reduction in the overall complexity compared to conventional MLD, and > 89% reduction compared to the most competitive reported algorithms in the literature. This complexity gain becomes greater when the number of transmit antennas (N ) or the constellation size (L) becomes larger. In the third application, we propose a low complexity Maximum Likelihood Decoding (MLD) algorithm for orthogonal spacetime block codes (OSTBCs) based on the real-valued lattice representation and QR decomposition. For a system employing the well-known Alamouti OSTBC and 16-QAM modulation scheme, the new approach achieves > 87% reduction in the overall complexity compared to conventional MLD. Moreover, we show that for square L-QAM constellations, the proposed algorithm reduces the decoding computational complexity from O(L N/2 ) for conventional MLD to O(L) for systems employing QOSTBCs and from O(L) for conventional MLD to O( √ L) for those employing OSTBCs without sacrificing the performance.

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Section: Simulation Resultsmentioning

confidence: 99%

mentioning

confidence: 89%

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Reduction of ML decoding complexity for MIMO Sphere Decoding, QOSTBC, and OSTBC

Azzam

Ayanoğlu

2008

2008 Information Theory and Applications Workshop

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“…For example, the ISI-free QO-STBC is achieved through the rotation of one-half of the symbol constellation set [35][36][37], multidimensional rotation [38][39][40], Givens-rotations [16], EVD [17,18] and Hadamard matrices [1,17]. Although the EVD approach is less complex and will be followed, the results can be enhanced if an equivalent modal matrix can be derived without zeros terms.…”

Section: Full-diversity Qo-stbc Using Evd and The Proposedmentioning

confidence: 99%

Full-Diversity QO-STBC Technique for Large-Antenna MIMO Systems

et al. 2017

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The need to achieve high data rates in modern telecommunication systems, such as 5G standard, motivates the study and development of large antenna and multiple-input multiple-output (MIMO) systems. This study introduces a large antenna-order design of MIMO quasi-orthogonal space-time block code (QO-STBC) system that achieves better signal-to-noise ratio (SNR) and bit-error ratio (BER) performances than the conventional QO-STBCs with the potential for massive MIMO (mMIMO) configurations. Although some earlier MIMO standards were built on orthogonal space-time block codes (O-STBCs), which are limited to two transmit antennas and data rates, the need for higher data rates motivates the exploration of higher antenna configurations using different QO-STBC schemes. The standard QO-STBC offers a higher number of antennas than the O-STBC with the full spatial rate. Unfortunately, also, the standard QO-STBCs are not able to achieve full diversity due to self-interference within their detection matrices; this diminishes the BER performance of the QO-STBC scheme. The detection also involves nonlinear processing, which further complicates the system. To solve these problems, we propose a linear processing design technique (which eliminates the system complexity) for constructing interference-free QO-STBCs and that also achieves full diversity using Hadamard modal matrices with the potential for mMIMO design. Since the modal matrices that orthogonalize QO-STBC are not sparse, our proposal also supports O-STBCs with a well-behaved peak-to-average power ratio (PAPR) and better BER. The results of the proposed QO-STBC outperform other full diversity techniques including Givens-rotation and the eigenvalue decomposition (EVD) techniques by 15 dB for both MIMO and multiple-input single-output (MISO) antenna configurations at 10 −3 BER. The proposed interference-free QO-STBC is also implemented for 16 × N R and 32 × N R MIMO systems, where N R ≤ 2. We demonstrate 8, 16 and 32 transmit antenna-enabled MIMO systems with the potential for mMIMO design applications with attractive BER and PAPR performance characteristics.

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“…Whereupon, QOSTBCs with constellation rotation were proposed in [19,20], which can provide full diversity and higher code rate. However, the ML decoding for QOSTBCs is generally more complex than that of OSTBCs.…”

Section: Introductionmentioning

confidence: 99%

Cooperative Transmission Using Quasi-Orthogonal Space-Time Block Codes with Adaptive Decode-and-Forward Relaying Protocol

Gao

2010

Wireless Pers Commun

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In this paper, we propose a cooperative transmission scheme using quasiorthogonal space-time block codes (QOSTBCs) for multiple-input multiple-output (MIMO) relay networks. Comparing with the conventional cooperative transmission scheme using orthogonal space-time block codes (OSTBCs), the proposed scheme can achieve higher bandwidth efficiency with the same decoding complexity. Moreover, an adaptive decodeand-forward (ADF) relaying protocol is proposed based on one-bit channel state information (CSI) feedback. According to the CSI feedback, a better transmission mode can be selected between the direct transmission and decode-and-forward (DF) cooperative transmission. In addition, the outage performance of the proposed scheme is investigated and a closed-form upper bound on the outage probability is derived. The performance analysis shows that the proposed scheme can achieve a full diversity order, which is higher than that of the direct and DF cooperative transmissions.Keywords Multiple-input multiple-output (MIMO) relay · Space-time block codes (STBCs) · Channel state information (CSI) feedback · Decode-and-forward (DF) · Outage probability

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An Efficient Decoding Algorithm for STBC with Multi-dimensional Rotated Constellations

Cited by 19 publications

References 16 publications

Reduction of ML decoding complexity for MIMO Sphere Decoding, QOSTBC, and OSTBC

Reduction of ML decoding complexity for MIMO Sphere Decoding, QOSTBC, and OSTBC

Full-Diversity QO-STBC Technique for Large-Antenna MIMO Systems

Cooperative Transmission Using Quasi-Orthogonal Space-Time Block Codes with Adaptive Decode-and-Forward Relaying Protocol

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