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Journal ArticleDOI

QR-LRL Signal Detection for Spatially Multiplexed MIMO Systems

01 Oct 2008-IEICE Transactions on Communications (The Institute of Electronics, Information and Communication Engineers)-Vol. 91, Iss: 10, pp 3383-3386
TL;DR: It is shown that the selection of the first layer impacts the error performance significantly, and based on the observation, a novel signal detection method QR-LRL is proposed, which is shown to be the best choice in terms of noise enhancement in detecting the other layers.
Abstract: The performance of the ordered successive interference cancellation (OSIC) signal detection method is well known to depend on the successful detection of the first layer. In a previous work, in an effort to mitigate the error propagation effect, all the constellation points were tried as the first layer symbol, thereby achieving a better performance. In this letter, we show that the selection of the first layer impacts the error performance significantly, and based on the observation, we propose a novel signal detection method QR-LRL. In the proposed work, the least reliable layer (LRL) is chosen to be the first layer, which is shown to be the best choice in terms of noise enhancement in detecting the other layers. Also, we discuss Log Likelihood Ratio (LLR) computation when the proposed method is used. Computer simulations confirm the efficacy of the proposed method.
Citations
More filters
01 Jan 2007
TL;DR: In this article, a maximum likelihood estimator for digital sequences disturbed by Gaussian noise, intersymbol interference (ISI) and interchannel interference (ICI) is derived.
Abstract: A maximum likelihood (ML) estimator for digital sequences disturbed by Gaussian noise, intersymbol interference (ISI) and interchannel interference (ICI) is derived. It is shown that the sampled outputs of the multiple matched filter (MMF) form a set of sufficient statistics for estimating the input vector sequence. Two ML vector sequence estimation algorithms are presented. One makes use of the sampled output data of the multiple whitened matched filter and is called the vector Viterbi algorithm. The other one is modification of the vector Viterbi algorithm and uses directly the sampled output of the MMF. It appears that, under a certain condition, the error performance is asymptotically as good as if both ISI and ICI were absent.

13 citations

Journal ArticleDOI
TL;DR: A novel receiver scheme for multiple-input-multiple-output (MIMO) single-carrier frequency-division multiple access (SC-FDMA) systems that takes advantage of the sparse channel structure, offering higher postprojection signal-to-noise ratios (SNRs) of the resulting subsystems than those of a naive projection that does not exploit the channel structure.
Abstract: In this paper, we propose a novel receiver scheme for multiple-input–multiple-output (MIMO) single-carrier frequency-division multiple access (SC-FDMA) systems. Various optimal and near-optimalMIMO detection techniques developed for flat-fading channels are not readily applied to MIMO SC-FDMA systems due to the large dimensions of the effective channels. Recently, the system equation of single-input–single-output (SISO) SC-FDMA systems was divided into a number of disjoint subsystems with moderate dimensions, and a previous MIMO detection technique was applied to the subsystems. In this paper, instead of naively extending the previous scheme for SISO SC-FDMA to MIMO SC-FDMA systems, we first express the large system equation of MIMO SC-FDMA, such that the effective channels are block circulant for an arbitrary number of transmit and receive antennas. The block circulant channel structure is then exploited to lower the computational complexity of projections to construct nonoverlapping subsystems. The proposed circulant projection also takes advantage of the sparse channel structure, offering higher postprojection signal-to-noise ratios (SNRs) of the resulting subsystems than those of a naive projection that does not exploit the channel structure. The simulations confirm the desirable performance of the proposed scheme when a relatively small number of subcarriers are used. The proposed technique is also compared with the previous iterative block decision feedback equalization (IB-DFE) and minimum-mean-square-error–prewhitened-maximum-likelihood (MMSE-prewhitened-ML) detection techniques.

12 citations


Cites methods from "QR-LRL Signal Detection for Spatial..."

  • ...tems, such as M-algorithm-based detection [4], QR-least reliable layer (QR-LRL) detection [5], sphere-decoding-based techniques [6], minimum mean square error (MMSE)-based joint detection [7], graphtheory-based detection [8], Lenstra–Lenstra–Lovász-based detection...

    [...]

  • ...We use QR-LRL joint detection [5] for the subsystems concerning SBNT = 6 symbols in both the naive and proposed schemes....

    [...]

  • ...Once the nonoverlapping subsystems are constructed, not only the detection in [4] but also the various well-developed MIMO detection techniques in [5]–[10] can be used....

    [...]

Journal ArticleDOI
TL;DR: A novel detection method is proposed which can generate reliable soft-outputs while avoiding the empty vector set problem and efficiently uses the upper triangular structure in QR decomposition.
Abstract: A simple detector named QR-LRL for MIMO systems was proposed in [7] and it was shown that QR-LRL approached the hard-output ML performance. However, its soft-output performance is not capable of approaching the near ML performance. In this letter, we propose a novel detection method which can generate reliable soft-outputs while avoiding the empty vector set problem. The proposed detector efficiently uses the upper triangular structure in QR decomposition. Simulation results show that the proposed detector can approach the near soft-output ML performance as well as hard-output with feasible complexity.

9 citations

Journal ArticleDOI
TL;DR: The proposed detector effectively solves the EVS problem and achieves soft ML performance while keeping the computation complexity low, especially at low modulation order.
Abstract: An enlargement of the candidate vector set of QR-least reliable layer (QR-LRL) based MIMO detector for efficient soft output generation is proposed. Previous work (Bahng et al. in IEICE Trans Commun, E89---B(10):2956---2960, 2008) shows that the QR-LRL based MIMO detector approaches hard decision output ML performance, but does not match soft output ML performance due to empty candidate vector set problem. Performance degradation is more severe when modulation order is low. Some of the previous methods have provided solutions to empty vector set (EVS) problem (Kawai et al. in IEICE Trans Commun, E88---B(1):47---57, 2005; Bahng et al. in IEICE Trans Commun, E89---B(10):2956---2960, 2008; Kim et al. in IEICE Trans Commun, E92---B(11):3512---3515, 2009), but are not efficient in terms of performance or computation complexity. In this paper, we enlarge the candidate vector set of QR-LRL detector by applying every constellation point at each layer. The proposed detector thus effectively solves the EVS problem and achieves soft ML performance while keeping the computation complexity low, especially at low modulation order.

6 citations

References
More filters
Journal ArticleDOI
Gerard J. Foschini1
TL;DR: This paper addresses digital communication in a Rayleigh fading environment when the channel characteristic is unknown at the transmitter but is known (tracked) at the receiver with the aim of leveraging the already highly developed 1-D codec technology.
Abstract: This paper addresses digital communication in a Rayleigh fading environment when the channel characteristic is unknown at the transmitter but is known (tracked) at the receiver. Inventing a codec architecture that can realize a significant portion of the great capacity promised by information theory is essential to a standout long-term position in highly competitive arenas like fixed and indoor wireless. Use (n T , n R ) to express the number of antenna elements at the transmitter and receiver. An (n, n) analysis shows that despite the n received waves interfering randomly, capacity grows linearly with n and is enormous. With n = 8 at 1% outage and 21-dB average SNR at each receiving element, 42 b/s/Hz is achieved. The capacity is more than 40 times that of a (1, 1) system at the same total radiated transmitter power and bandwidth. Moreover, in some applications, n could be much larger than 8. In striving for significant fractions of such huge capacities, the question arises: Can one construct an (n, n) system whose capacity scales linearly with n, using as building blocks n separately coded one-dimensional (1-D) subsystems of equal capacity? With the aim of leveraging the already highly developed 1-D codec technology, this paper reports just such an invention. In this new architecture, signals are layered in space and time as suggested by a tight capacity bound.

6,812 citations

Book
30 Nov 2008
TL;DR: The goal of this paper is to present in a comprehensive fashion the theory underlying bit-interleaved coded modulation, to provide tools for evaluating its performance, and to give guidelines for its design.
Abstract: Zehavi (1992) showed that the performance of coded modulation over a Rayleigh fading channel can be improved by bit-wise interleaving the encoder output and by using an appropriate soft-decision metric as an input to a Viterbi decoder. The goal of this paper is to present in a comprehensive fashion the theory underlying bit-interleaved coded modulation, to provide tools for evaluating its performance, and to give guidelines for its design.

2,098 citations

Journal ArticleDOI
TL;DR: The theoretical foundations of BICM are reviewed under the unified framework of error exponents for mismatched decoding, which allows an accurate analysis without any particular assumptions on the length of the interleaver or independence between the multiple bits in a symbol.
Abstract: The principle of coding in the signal space follows directly from Shannon's analysis of waveform Gaussian channels subject to an input constraint. The early design of communication systems focused separately on modulation, namely signal design and detection, and error correcting codes, which deal with errors introduced at the demodulator of the underlying waveform channel. The correct perspective of signal-space coding, although never out of sight of information theorists, was brought back into the focus of coding theorists and system designers by Imai's and Ungerbock's pioneering works on coded modulation. More recently, powerful families of binary codes with a good tradeoff between performance and decoding complexity have been (re-)discovered. Bit-Interleaved Coded Modulation (BICM) is a pragmatic approach combining the best out of both worlds: it takes advantage of the signal-space coding perspective, whilst allowing for the use of powerful families of binary codes with virtually any modulation format. BICM avoids the need for the complicated and somewhat less flexible design typical of coded modulation. As a matter of fact, most of today's systems that achieve high spectral efficiency such as DSL, Wireless LANs, WiMax and evolutions thereof, as well as systems based on low spectral efficiency orthogonal modulation, feature BICM, making BICM the de-facto general coding technique for waveform channels. The theoretical characterization of BICM is at the basis of efficient coding design techniques and also of improved BICM decoders, e.g., those based on the belief propagation iterative algorithm and approximations thereof. In this text, we review the theoretical foundations of BICM under the unified framework of error exponents for mismatched decoding. This framework allows an accurate analysis without any particular assumptions on the length of the interleaver or independence between the multiple bits in a symbol. We further consider the sensitivity of the BICM capacity with respect to the signal-to-noise ratio (SNR), and obtain a wideband regime (or low-SNR regime) characterization. We review efficient tools for the error probability analysis of BICM that go beyond the standard approach of considering infinite interleaving and take into consideration the dependency of the coded bit observations introduced by the modulation. We also present bounds that improve upon the union bound in the region beyond the cutoff rate, and are essential to characterize the performance of modern randomlike codes used in concatenation with BICM. Finally, we turn our attention to BICM with iterative decoding, we review extrinsic information transfer charts, the area theorem and code design via curve fitting. We conclude with an overview of some applications of BICM beyond the classical coherent Gaussian channel.

1,245 citations

Journal ArticleDOI
TL;DR: A V-BLAST-type combination of orthogonal frequency-division multiplexing with MIMO (MIMO-OFDM) for enhanced spectral efficiency and multiuser downlink throughput and a new joint data detection and channel estimation algorithm is proposed which combines the QRD-M algorithm and Kalman filter.
Abstract: The use of multiple transmit/receive antennas forming a multiple-input multiple-output (MIMO) system can significantly enhance channel capacity. This paper considers a V-BLAST-type combination of orthogonal frequency-division multiplexing (OFDM) with MIMO (MIMO-OFDM) for enhanced spectral efficiency and multiuser downlink throughput. A new joint data detection and channel estimation algorithm for MIMO-OFDM is proposed which combines the QRD-M algorithm and Kalman filter. The individual channels between antenna elements are tracked using a Kalman filter, and the QRD-M algorithm uses a limited tree search to approximate the maximum-likelihood detector. A closed-form symbol-error rate, conditioned on a static channel realization, is presented for the M=1 case with QPSK modulation. An adaptive complexity QRD-M algorithm (AC-QRD-M) is also considered which assigns different values of M to each subcarrier according to its estimated received power. A rule for choosing M using subcarrier powers is obtained using a kernel density estimate combined with the Lloyd-Max algorithm.

304 citations

Journal ArticleDOI
TL;DR: A maximum likelihood estimator for digital sequences disturbed by Gaussian noise, intersymbol interference and interchannel interference is derived and it appears that, under a certain condition, the error performance is asymptotically as good as if both ISI and ICI were absent.
Abstract: A maximum likelihood (ML) estimator for digital sequences disturbed by Gaussian noise, intersymbol interference (ISI) and interchannel interference (ICI) is derived It is shown that the sampled outputs of the multiple matched filter (MMF) form a set of sufficient statistics for estimating the input vector sequence Two ML vector sequence estimation algorithms are presented One makes use of the sampled output data of the multiple whitened matched filter and is called the vector Viterbi algorithm The other one is a modification of the vector Viterbi algorithm and uses directly the sampled output of the MMF It appears that, under a certain condition, the error performance is asymptotically as good as if both ISI and ICI were absent

299 citations