A low ML-decoding complexity, full-diversity, full-rate MIMO precoder

Srinath, K. Pavan; Rajan, B. Sundar

doi:10.1109/isit.2011.6034111

Cited by 6 publications

(18 citation statements)

References 12 publications

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“…Hence, we can conclude from this example that an 16QAM input constellation can be replaced by an infinite lattice constellation without appreciatly affecting the results. It can also be numerically verified, in accordance with the results in [7], [8], [11], that when the constellation size increases, the value of s 1 /s 2 for which the precoder changes gets higher and higher. Thus, above a certain cardinality of the alphabet, the same precoder is optimal for all channels S for which s 1 /s 2 is below some large threshold.…”

Section: Applicationssupporting

confidence: 83%

“…Since B is now known, it remains to find the optimal basis matrix Z in order to solve (11). This section describes the core idea of the algorithms that find the optimal real-valued and complex-valued Z, respectively, for the case when A = I.…”

Section: Optimal Matrix Zmentioning

confidence: 99%

“…The work in [10] proposes real-valued precoders with low ML-decoding complexity. [11] considers real-valued precoders that are approximately optimal among real-valued ones with respect to the minimum distance for M × 2 systems, and are easy to calculate for large QAM constellations. In [12] and [13], it is proposed to design F based on dense lattice packings.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Two-Dimensional Lattices for Precoding of Linear Channels

Kapetanović

Cheng

Mow

et al. 2013

IEEE Trans. Wireless Commun.

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Abstract-Consider the communication system model y = HFx+n, where H and F are the channel and precoder matrices, x is a vector of data symbols drawn from some lattice-type constellation, such as M-QAM, n is an additive white Gaussian noise vector and y is the received vector. It is assumed that both the transmitter and the receiver have perfect knowledge of the channel matrix H and that the transmitted signal Fx is subject to an average energy constraint. The columns of the matrix HF can be viewed as the basis vectors that span a lattice, and we are interested in the precoder F that maximizes the minimum distance of this lattice. This particular problem remains open within the theory of lattices and the communication theory. This paper provides the complete solution for any nonsingular M × 2 channel matrix H. For real-valued matrices and vectors, the solution is that HF spans the hexagonal lattice. For complex-valued matrices and vectors, the solution is that HF, when viewed in four-dimensional real-valued space, spans the Schläfli lattice D4.

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Section: Applicationssupporting

confidence: 83%

Section: Optimal Matrix Zmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal Two-Dimensional Lattices for Precoding of Linear Channels

Kapetanović

Cheng

Mow

et al. 2013

IEEE Trans. Wireless Commun.

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“…Then, the subchannels are paired to obtain a set of 2 × 2 MIMO subsystems, and 2 × 2 subprecoders are designed to maximize the free distance in the MIMO subsystems. We refer to this approach as precoding with X-structure, which has been considered in [17]- [19]. Precoding with X-structure not only facilitates the precoder design but yields 0018-9545 © 2013 IEEE a low-complexity ML receiver as well since we only have to deal with 2 × 2 MIMO subsystems.…”

Section: Introductionmentioning

confidence: 99%

“…A numerical search is required for the angle in higher QAM constellations. More recently, an optimum real-valued subprecoder has been developed [19]. It also requires the numerical search in design and lookup tables in run time.…”

Section: Introductionmentioning

confidence: 99%

X-Structured Precoder Designs for Spatial-Multiplexing MIMO and MIMO Relay Systems

Lin

2013

IEEE Trans. Veh. Technol.

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In multiple-input-multiple-output (MIMO) transmission, precoding has been considered a promising technique to improve the system performance. In general, the criterion of precoder design depends on the detector used at the receiver. For the maximum-likelihood (ML) detector, the criterion is to maximize the minimum distance of the received signal constellation. Unfortunately, the derivation of the optimum solution is known to be difficult, and suboptimum solutions have then been developed. One promising approach confines the precoder having an X-structure. Several methods have been developed to solve the X-structured precoder. However, most of them use numerical searches to find their solutions and require lookup tables during run time. In this paper, we propose a systematic design method to solve the problems. The proposed precoder has a simple closedform expression, and no numerical searches and lookup tables are required. Simulation results show that the proposed method can yield almost the same performance as the existing methods. We also consider the problem of joint source/relay precoder design in a two-hop amplify-and-forward MIMO relay system. Since the problem is much more involved and a closed-form solution is intractable to find, we then extend the use of the proposed X-structured precoder so that the problem can be reformulated as a simple scalar-valued optimization problem. Simulations show that the proposed method can significantly outperform existing joint design methods.Index Terms-Free distance, geometric mean decomposition (GMD), maximum-likelihood (ML) detection, MIMO, multiple-input-multiple-output (MIMO) relay systems, spatial multiplexing, X-structured precoder.

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Adaptive Minimum-Distance Based Precoder for NB-LDPC Coded MIMO Transmission

Chehade

Collin

Rostaing

et al. 2015

2015 IEEE Global Communications Conference (GLOBECOM)

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In this paper, we focus on a multiple-input multiple-output (MIMO) linear precoder based on the minimum Euclidean distance criterion, the max-precoder. We propose an optimization of this precoder for the case of an association with a non-binary low density parity check code (NB-LDPC). After recalling the well-known max-precoder, we set forth an optimization of the mutual information of initial message, i.e., through the extrinsic information transfer (EXIT) analysis of the system. We present a new adaptive precoder whose forms are determined in function of an adaptive threshold angle, optimized in terms of the mutual information , and depending on the signal-to-noise ratio at the reception ( ). The performance of the new precoder is brought out through a theoretical study along with a series of numerical simulations.

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A low ML-decoding complexity, full-diversity, full-rate MIMO precoder

Cited by 6 publications

References 12 publications

Optimal Two-Dimensional Lattices for Precoding of Linear Channels

Optimal Two-Dimensional Lattices for Precoding of Linear Channels

X-Structured Precoder Designs for Spatial-Multiplexing MIMO and MIMO Relay Systems

Adaptive Minimum-Distance Based Precoder for NB-LDPC Coded MIMO Transmission

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