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Proceedings ArticleDOI

V-BLAST: an architecture for realizing very high data rates over the rich-scattering wireless channel

TL;DR: This paper describes a wireless communication architecture known as vertical BLAST (Bell Laboratories Layered Space-Time) or V-BLAST, which has been implemented in real-time in the laboratory and demonstrated spectral efficiencies of 20-40 bps/Hz in an indoor propagation environment at realistic SNRs and error rates.
Abstract: Information theory research has shown that the rich-scattering wireless channel is capable of enormous theoretical capacities if the multipath is properly exploited In this paper, we describe a wireless communication architecture known as vertical BLAST (Bell Laboratories Layered Space-Time) or V-BLAST, which has been implemented in real-time in the laboratory Using our laboratory prototype, we have demonstrated spectral efficiencies of 20-40 bps/Hz in an indoor propagation environment at realistic SNRs and error rates To the best of our knowledge, wireless spectral efficiencies of this magnitude are unprecedented and are furthermore unattainable using traditional techniques
Citations
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Book
01 Jan 2005

9,038 citations

Journal ArticleDOI
TL;DR: While the proposed algorithms are suboptimal, they lead to simpler transmitter and receiver structures and allow for a reasonable tradeoff between performance and complexity.
Abstract: The use of space-division multiple access (SDMA) in the downlink of a multiuser multiple-input, multiple-output (MIMO) wireless communications network can provide a substantial gain in system throughput. The challenge in such multiuser systems is designing transmit vectors while considering the co-channel interference of other users. Typical optimization problems of interest include the capacity problem - maximizing the sum information rate subject to a power constraint-or the power control problem-minimizing transmitted power such that a certain quality-of-service metric for each user is met. Neither of these problems possess closed-form solutions for the general multiuser MIMO channel, but the imposition of certain constraints can lead to closed-form solutions. This paper presents two such constrained solutions. The first, referred to as "block-diagonalization," is a generalization of channel inversion when there are multiple antennas at each receiver. It is easily adapted to optimize for either maximum transmission rate or minimum power and approaches the optimal solution at high SNR. The second, known as "successive optimization," is an alternative method for solving the power minimization problem one user at a time, and it yields superior results in some (e.g., low SNR) situations. Both of these algorithms are limited to cases where the transmitter has more antennas than all receive antennas combined. In order to accommodate more general scenarios, we also propose a framework for coordinated transmitter-receiver processing that generalizes the two algorithms to cases involving more receive than transmit antennas. While the proposed algorithms are suboptimal, they lead to simpler transmitter and receiver structures and allow for a reasonable tradeoff between performance and complexity.

3,291 citations


Cites background from "V-BLAST: an architecture for realiz..."

  • ...Section V discusses coordinated transmit-receive processing, which is a framework for extending the first two algorithms to handle larger channel geometries, and finally, Section VI presents simulation results comparing the algorithms under various conditions....

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  • ...The particular challenge of the vector broadcast channel is that while the transmitter has the ability to coordinate transmission from all of its antennas, the receivers are grouped among different users that are typically unable to coordinate with each other [12]–[14]....

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Dissertation
24 Apr 2002
TL;DR: Results show that remarkable energy and spectral efficiencies are achievable by combining concepts drawn from space-time coding, multiuser detection, array processing and iterative decoding.
Abstract: Space-time codes (STC) are a class of signaling techniques, offering coding and diversity gains along with improved spectral efficiency. These codes exploit both the spatial and the temporal diversity of the wireless link by combining the design of the error correction code, modulation scheme and array processing. STC are well suited for improving the downlink performance, which is the bottleneck in asymmetric applications such as downstream Internet. Three original contributions to the area of STC are presented in this dissertation. First, the development of analytic tools that determine the fundamental limits on the performance of STC in a variety of channel conditions. For trellis-type STC, transfer function based techniques are applied to derive performance bounds over Rayleigh, Rician and correlated fading environments. For block-type STC, an analytic framework that supports various complex orthogonal designs with arbitrary signal cardinalities and array configurations is developed. In the second part of the dissertation, the Virginia Tech Space-Time Advanced Radio (VT-STAR) is designed, introducing a multi-antenna hardware laboratory test bed, which facilitates characterization of the multiple-input multiple-output (MIMO) channel and validation of various space-time approaches. In the third part of the dissertation, two novel space-time architectures paired with iterative processing principles are proposed. The first scheme extends the suitability of STC to outdoor wireless communications by employing iterative equalization/decoding for time dispersive channels and the second scheme employs iterative interference cancellation/decoding to solve the error propagation problem of Bell-Labs Layered Space-Time Architecture (BLAST). Results show that remarkable energy and spectral efficiencies are achievable by combining concepts drawn from space-time coding, multiuser detection, array processing and iterative decoding.

2,286 citations


Cites background or methods from "V-BLAST: an architecture for realiz..."

  • ...52 3.10 D-BLAST hard-decision decoder structure . . . . . . . . . . . . . . . . . . . 52 3.11 D-BLAST encoder-decoder structure with iterative decoding . . . . . . . . 53 4.1 Trellis diagram of the 4-state delay diversity STTC, 2 Tx antennas, 2 [bps/Hz] 58 4.2 I/O function of trellis diagram . . . . . . . . . . . . . . . . . . . . . . . . . 59 4.3 Encoder block diagram of the 4-state STTC, 2 Tx antennas, 2 [bps/Hz] ....

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  • ...The Bell-Labs Layered Space-Time Architecture (BLAST) [47, 48] utilizes multiple antenna elements at both ends of the wireless link to offer unprecedented spectral efficiencies as compared with traditional single transmit antenna systems....

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  • ...143 7.13 4 state STTC, 2 taps channel, QPSK, perfect CSI, no interleaving . . . . . 144 7.14 8 state STTC, 2 taps channel, QPSK, perfect CSI, no interleaving . . . . . 144 7.15 Phase estimation errors; 4-state STTC, QPSK, 2Tx-1Rx, 3-tap channel, third iteration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 7.16 The role of iterative processing in the presence of phase estimation errors; 3-tap time dispersive channel, 4-state STTC, QPSK, 2Tx-1Rx . . . . . . . . 146 7.17 Amplitude estimation errors; 4-state STTC, QPSK, 2Tx-1Rx, 2-tap channel, third iteration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 7.18 The role of iterative processing in the presence of amplitude estimation errors; 2-tap time dispersive channel, 4-state STTC, QPSK, 2Tx-1Rx . . . . . . . . 148 7.19 Outage probability vs. frame error rate; phase estimation errors; 4-state STTC, QPSK, 2Tx-1Rx, 2-tap time dispersive channel, third iteration . . . 149 7.20 Outage probability vs. frame error rate; amplitude estimation errors; 4-state STTC, QPSK, 2Tx-1Rx, 2-tap time dispersive channel, third iteration . . . 150 8.1 V-BLAST Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 8.2 SIC V-BLAST Performance; ZF versus MMSE; with and without ordering; 4Tx-4Rx, QPSK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 8.3 PIC V-BLAST Performance; ZF versus MMSE; 4Tx-4Rx, QPSK . . . . . ....

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  • ...159 8.3.1 Variable Rate SIC Coded BLAST . . . . . . . . . . . . . . . . . . . 159 8.3.2 Iterative PIC/Decoding for Coded BLAST . . . . . . . . . . . . . . 160 8.4 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....

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  • ...156 8.4 Error propagation of SIC BLAST detector, 4Tx-4Rx, QPSK, MMSE nulling 158 8.5 Error propagation of PIC BLAST detector, 4Tx-4Rx, QPSK, MMSE nulling 158 8.6 Unequal error protection for SIC based BLAST architecture . . . . . . . . . 159 8.7 Iterative PIC/decoding BLAST architecture . . . . . . . . . . . . . . . . . . 160 8.8 Uncoded performance; unequal error protection, SIC detector, MMSE nulling, 4Tx-4Rx, QPSK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 8.9 Coded performance; unequal error protection, SIC detector, MMSE nulling, 4Tx-4Rx, QPSK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 8.10 Uncoded Performance; iterative PIC/decoding; 4 iterations; 8Tx-8Rx; QPSK 163 8.11 Iterative PIC/decoding; 4 iterations; MMSE nulling, r = 1/2, K = 7, QPSK 164 xiii 8.12 Coded performance; PIC detector, MMSE nulling, 16Tx-16Rx, r = 1/2, K = 7, QPSK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 8.13 Toeplitz and circulant covariance matrices . . . . . . . . . . . . . . . . . . . 166 8.14 Correlation at the receiver; PIC detector, MMSE nulling, 16Tx-16Rx, r = 1/2, K = 7, QPSK, SNR= 12 dB . . . . . . . . . . . . . . . . . . . . . . . . 167 8.15 Impact of correlation at the transmitter and receiver; PIC detector, MMSE nulling, 16Tx-16Rx, r = 1/2, K = 7, QPSK, SNR= 12 dB . . . . . . . . . . 168 8.16 Limited physical dimensions for linear or circular array; PIC detector, MMSE nulling, 16Tx-16Rx, r = 1/2, K = 7, QPSK . . . . . . . . . . . . . . . . . . 168 9.1 “Goodput” of scheduling over space-time architectures (4Tx-4Rx) . . . . . 173 9.2 “Goodput” of scheduling over space-time block codes (4Tx-4Rx) . . . . . ....

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Journal ArticleDOI
08 Nov 2004
TL;DR: An overview of MIMO wireless technology covering channel models, performance limits, coding, and transceiver design is provided, in principle, to meet the 1 Gb/s data rate requirement with a single-transmit single-receive antenna wireless system.
Abstract: High data rate wireless communications, nearing 1 Gb/s transmission rates, is of interest in emerging wireless local area networks and home audio/visual networks. Designing very high speed wireless links that offer good quality-of-service and range capability in non-line-of-sight (NLOS) environments constitutes a significant research and engineering challenge. Ignoring fading in NLOS environments, we can, in principle, meet the 1 Gb/s data rate requirement with a single-transmit single-receive antenna wireless system if the product of bandwidth (measured in hertz) and spectral efficiency (measured in bits per second per hertz) is equal to 10/sup 9/. A variety of cost, technology and regulatory constraints make such a brute force solution unattractive, if not impossible. The use of multiple antennas at transmitter and receiver, popularly known as multiple-input multiple-output (MIMO) wireless, is an emerging cost-effective technology that offers substantial leverages in making 1 Gb/s wireless links a reality. The paper provides an overview of MIMO wireless technology covering channel models, performance limits, coding, and transceiver design.

2,154 citations

Journal Article
TL;DR: An analytical approach for symbol error ratio (SER) analysis of the SM algorithm in independent identically distributed Rayleigh channels results closely match and it is shown that SM achieves better performance in all studied channel conditions, as compared with other techniques.
Abstract: Spatial modulation (SM) is a recently developed transmission technique that uses multiple antennas. The basic idea is to map a block of information bits to two information carrying units: 1) a symbol that was chosen from a constellation diagram and 2) a unique transmit antenna number that was chosen from a set of transmit antennas. The use of the transmit antenna number as an information-bearing unit increases the overall spectral efficiency by the base-two logarithm of the number of transmit antennas. At the receiver, a maximum receive ratio combining algorithm is used to retrieve the transmitted block of information bits. Here, we apply SM to orthogonal frequency division multiplexing (OFDM) transmission. We develop an analytical approach for symbol error ratio (SER) analysis of the SM algorithm in independent identically distributed (i.i.d.) Rayleigh channels. The analytical and simulation results closely match. The performance and the receiver complexity of the SM-OFDM technique are compared to those of the vertical Bell Labs layered space-time (V-BLAST-OFDM) and Alamouti-OFDM algorithms. V-BLAST uses minimum mean square error (MMSE) detection with ordered successive interference cancellation. The combined effect of spatial correlation, mutual antenna coupling, and Rician fading on both coded and uncoded systems are presented. It is shown that, for the same spectral efficiency, SM results in a reduction of around 90% in receiver complexity as compared to V-BLAST and nearly the same receiver complexity as Alamouti. In addition, we show that SM achieves better performance in all studied channel conditions, as compared with other techniques. It is also shown to efficiently work for any configuration of transmit and receive antennas, even for the case of fewer receive antennas than transmit antennas.

1,996 citations


Cites background from "V-BLAST: an architecture for realiz..."

  • ...widely been discussed: 1) diagonal BLAST (D-BLAST) [3] and 2) vertical BLAST (V-BLAST) [14]....

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  • ...ment, assuming a practical signal-to-noise ratio (SNR) range and bit error performance, respectively [14]....

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References
More filters
Book
01 Jan 1983

34,729 citations


"V-BLAST: an architecture for realiz..." refers background in this paper

  • ..., k i of H and + denotes the Moore-Penrose pseudoinverse [5]....

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Journal ArticleDOI
TL;DR: In this article, the authors examined the performance of using multi-element array (MEA) technology to improve the bit-rate of digital wireless communications and showed that with high probability extraordinary capacity is available.
Abstract: This paper is motivated by the need for fundamental understanding of ultimate limits of bandwidth efficient delivery of higher bit-rates in digital wireless communications and to also begin to look into how these limits might be approached. We examine exploitation of multi-element array (MEA) technology, that is processing the spatial dimension (not just the time dimension) to improve wireless capacities in certain applications. Specifically, we present some basic information theory results that promise great advantages of using MEAs in wireless LANs and building to building wireless communication links. We explore the important case when the channel characteristic is not available at the transmitter but the receiver knows (tracks) the characteristic which is subject to Rayleigh fading. Fixing the overall transmitted power, we express the capacity offered by MEA technology and we see how the capacity scales with increasing SNR for a large but practical number, n, of antenna elements at both transmitter and receiver. We investigate the case of independent Rayleigh faded paths between antenna elements and find that with high probability extraordinary capacity is available. Compared to the baseline n = 1 case, which by Shannon‘s classical formula scales as one more bit/cycle for every 3 dB of signal-to-noise ratio (SNR) increase, remarkably with MEAs, the scaling is almost like n more bits/cycle for each 3 dB increase in SNR. To illustrate how great this capacity is, even for small n, take the cases n = 2, 4 and 16 at an average received SNR of 21 dB. For over 99% of the channels the capacity is about 7, 19 and 88 bits/cycle respectively, while if n = 1 there is only about 1.2 bit/cycle at the 99% level. For say a symbol rate equal to the channel bandwith, since it is the bits/symbol/dimension that is relevant for signal constellations, these higher capacities are not unreasonable. The 19 bits/cycle for n = 4 amounts to 4.75 bits/symbol/dimension while 88 bits/cycle for n = 16 amounts to 5.5 bits/symbol/dimension. Standard approaches such as selection and optimum combining are seen to be deficient when compared to what will ultimately be possible. New codecs need to be invented to realize a hefty portion of the great capacity promised.

10,526 citations

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

Journal ArticleDOI
TL;DR: This paper shows that the presence of multipath greatly improves achievable data rate if the appropriate communication structure is employed, and an adaptive-lattice trellis-coding technique is suggested as a method for coding across the space and frequency dimensions that exist in the DMMT channel.
Abstract: Multipath signal propagation has long been viewed as an impairment to reliable communication in wireless channels. This paper shows that the presence of multipath greatly improves achievable data rate if the appropriate communication structure is employed. A compact model is developed for the multiple-input multiple-output (MIMO) dispersive spatially selective wireless communication channel. The multivariate information capacity is analyzed. For high signal-to-noise ratio (SNR) conditions, the MIMO channel can exhibit a capacity slope in bits per decibel of power increase that is proportional to the minimum of the number multipath components, the number of input antennas, or the number of output antennas. This desirable result is contrasted with the lower capacity slope of the well-studied case with multiple antennas at only one side of the radio link. A spatio-temporal vector-coding (STVC) communication structure is suggested as a means for achieving MIMO channel capacity. The complexity of STVC motivates a more practical reduced-complexity discrete matrix multitone (DMMT) space-frequency coding approach. Both of these structures are shown to be asymptotically optimum. An adaptive-lattice trellis-coding technique is suggested as a method for coding across the space and frequency dimensions that exist in the DMMT channel. Experimental examples that support the theoretical results are presented.

1,593 citations


"V-BLAST: an architecture for realiz..." refers background in this paper

  • ...INTRODUCTION In the past few years, theoretical investigations have revealed that the multipath wireless channel is capable of enormous capacities, provided that the multipath scattering is sufficiently rich and is properly exploited through the use of an appropriate processing architecture [1-4]....

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Journal ArticleDOI
TL;DR: The authors investigate the canceller's bit error rate (BER) performance in both the absence and presence of errors in the amplitude and phase estimates of each user's received signal.
Abstract: The authors propose and analyze a direct-sequence spread-spectrum multiaccess (DS/SSMA) receiver that employs a cascade of cochannel interference (CCl) cancellers for communication over multipath fading channels. The receiver first coherently demodulates and despreads the received signal to produce correlator outputs and initial data estimates. Based on these estimates, the cancellation scheme essentially creates replicas of the contributions of the CCl embedded in the correlator outputs and removes them for a second improved hard data decision. By repeating this operation over and over, a cascade of CCl cancellers is derived. Through theoretical analysis and simulation, the authors investigate the canceller's bit error rate (BER) performance in both the absence and presence of errors in the amplitude and phase estimates of each user's received signal. Numerical results show the considerably large improvement in performance that can be attained by the cancellation scheme, even under partially degraded estimates. >

301 citations


"V-BLAST: an architecture for realiz..." refers background in this paper

  • ...Although the "best first" cancellation approach is widely known within the multi-user community [ 7-8 ], essentially being the defacto approach, we are not aware of any previous proof of its optimality in the sense given here....

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