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28
SpatioTemporal Coding for Wireless Communication
 IEEE Trans. Commun
, 1998
"... 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 multip ..."
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Cited by 275 (14 self)
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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 multipleinput multipleoutput (MIMO) dispersive spatially selective wireless communication channel. The multivariate information capacity is analyzed. For high signaltonoise 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 wellstudied case with multiple antennas at only one side of the radio link. A spatiotemporal vectorcoding (STVC) communication structure is suggested as a means for achieving MIMO channel capacity. The complexity of STVC motivates a more practical reducedcomplexity discrete matrix multitone (DMMT) spacefrequency coding approach. Both of these structures are shown to be asymptotically optimum. An adaptivelattice trelliscoding 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. Index TermsAdaptive arrays, adaptive coding, adaptive modulation, antenna arrays, broadband communication, channel coding, digital modulation, information rates, MIMO systems, multipath channels. I.
Joint TxRx beamforming design for multicarrier MIMO channels: a unified framework for convex optimization
 IEEE TRANS. SIGNAL PROCESSING
, 2003
"... This paper addresses the joint design of transmit and receive beamforming or linear processing (commonly termed linear precoding at the transmitter and equalization at the receiver) for multicarrier multipleinput multipleoutput (MIMO) channels under a variety of design criteria. Instead of consid ..."
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Cited by 126 (12 self)
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This paper addresses the joint design of transmit and receive beamforming or linear processing (commonly termed linear precoding at the transmitter and equalization at the receiver) for multicarrier multipleinput multipleoutput (MIMO) channels under a variety of design criteria. Instead of considering each design criterion in a separate way, we generalize the existing results by developing a unified framework based on considering two families of objective functions that embrace most reasonable criteria to design a communication system: Schurconcave and Schurconvex functions. Once the optimal structure of the transmitreceive processing is known, the design problem simplifies and can be formulated within the powerful framework of convex optimization theory, in which a great number of interesting design criteria can be easily accommodated and efficiently solved, even though closedform expressions may not exist. From this perspective, we analyze a variety of design criteria, and in particular, we derive optimal beamvectors in the sense of having minimum average bit error rate (BER). Additional constraints on the peaktoaverage ratio (PAR) or on the signal dynamic range are easily included in the design. We propose two multilevel waterfilling practical solutions that perform very close to the optimal in terms of average BER with a low implementation complexity. If cooperation among the processing operating at different carriers is allowed, the performance improves significantly. Interestingly, with carrier cooperation, it turns out that the exact optimal solution in terms of average BER can be obtained in closed form.
Optimal Designs for SpaceTime Linear Precoders and Decoders
 IEEE Trans. Signal Processing
, 2001
"... In this paper we introduce a new paradigm for the design of transmitter spacetime coding that we refer to as linear precoding. It leads to simple closed form solutions for transmission over frequency selective multipleinput multipleoutput (MIMO) channels, which are scalable with respect to the nu ..."
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Cited by 108 (5 self)
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In this paper we introduce a new paradigm for the design of transmitter spacetime coding that we refer to as linear precoding. It leads to simple closed form solutions for transmission over frequency selective multipleinput multipleoutput (MIMO) channels, which are scalable with respect to the number of antennas, size of the coding block and transmit average/peak power. The scheme operates as a block transmission system in which vectors of symbols are encoded and modulated through a linear mapping operating jointly in the space and time dimension. The specific designs target minimization of the symbol mean square error and the approximate maximization of the minimum distance between symbol hypotheses, under average and peak power constraints. The solutions are shown to convert the MIMO channel with memory into a set of parallel flat fading subchannels, regardless of the design criterion, while appropriate power/bits loading on the subchannels is the specific signature of the different designs. The proposed designs are compared in terms of various performance measures such as information rate, BER and symbol mean square error.
Gradient of mutual information in linear vector Gaussian channels
 IEEE Trans. Inf. Theory
, 2006
"... Abstract — This paper considers a general linear vector Gaussian channel with arbitrary signaling and pursues two closely related goals: i) closedform expressions for the gradient of the mutual information with respect to arbitrary parameters of the system, and ii) fundamental connections between i ..."
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Cited by 45 (11 self)
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Abstract — This paper considers a general linear vector Gaussian channel with arbitrary signaling and pursues two closely related goals: i) closedform expressions for the gradient of the mutual information with respect to arbitrary parameters of the system, and ii) fundamental connections between information theory and estimation theory. Generalizing the fundamental relationship recently unveiled by Guo, Shamai, and Verdú [1], we show that the gradient of the mutual information with respect to the channel matrix is equal to the product of the channel matrix and the error covariance matrix of the estimate of the input given the output. I.
Optimum power allocation for parallel Gaussian channels with arbitrary input distributions
 IEEE TRANS. INF. THEORY
, 2006
"... The mutual information of independent parallel Gaussiannoise channels is maximized, under an average power constraint, by independent Gaussian inputs whose power is allocated according to the waterfilling policy. In practice, discrete signaling constellations with limited peaktoaverage ratios (m ..."
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Cited by 34 (9 self)
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The mutual information of independent parallel Gaussiannoise channels is maximized, under an average power constraint, by independent Gaussian inputs whose power is allocated according to the waterfilling policy. In practice, discrete signaling constellations with limited peaktoaverage ratios (mPSK, mQAM, etc.) are used in lieu of the ideal Gaussian signals. This paper gives the power allocation policy that maximizes the mutual information over parallel channels with arbitrary input distributions. Such policy admits a graphical interpretation, referred to as mercury/waterfilling, which generalizes the waterfilling solution and allows retaining some of its intuition. The relationship between mutual information of Gaussian channels and nonlinear minimum meansquare error (MMSE) proves key to solving the power allocation problem.
Optimum linear joint transmitreceive processing for MIMO channels with QoS constraints
 IEEE Transactions on Signal Processing
, 2004
"... Abstract—This paper considers vector communications through multipleinput multipleoutput (MIMO) channels with a set of quality of service (QoS) requirements for the simultaneously established substreams. Linear transmitreceive processing (also termed linear precoder at the transmitter and linear ..."
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Cited by 23 (3 self)
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Abstract—This paper considers vector communications through multipleinput multipleoutput (MIMO) channels with a set of quality of service (QoS) requirements for the simultaneously established substreams. Linear transmitreceive processing (also termed linear precoder at the transmitter and linear equalizer at the receiver) is designed to satisfy the QoS constraints with minimum transmitted power (the exact conditions under which the problem becomes unfeasible are given). Although the original problem is a complicated nonconvex problem with matrixvalued variables, with the aid of majorization theory, we reformulate it as a simple convex optimization problem with scalar variables. We then propose a practical and efficient multilevel waterfilling algorithm to optimally solve the problem for the general case of different QoS requirements. The optimal transmitreceive processing is shown to diagonalize the channel matrix only after a very specific prerotation of the data symbols. For situations in which the resulting transmit power is too large, we give the precise way to relax the QoS constraints in order to reduce the required power based on a perturbation analysis. We also propose a robust design under channel estimation errors that has an important interest for practical systems. Numerical results from simulations are given to support the mathematical development of the problem. Index Terms—Array signal processing, beamforming, joint transmitreceive equalization, linear precoding, MIMO channels, spacetime filtering, waterfilling. I.
Suppression of near and farend crosstalk by linear pre and postfiltering
 IEEE J. Select. Areas Commun
, 1992
"... AbstractFullduplex data communications over a multiinput/multioutput linear timeinvariant channel is considered. The minimum mean square error (MMSE) linear equalizer is derived in the presence of both near and farend crosstalk and independent additive noise, assuming correlated data, and co ..."
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Cited by 21 (1 self)
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AbstractFullduplex data communications over a multiinput/multioutput linear timeinvariant channel is considered. The minimum mean square error (MMSE) linear equalizer is derived in the presence of both near and farend crosstalk and independent additive noise, assuming correlated data, and colored noise. The MMSE equalizer is completely specified in terms of the channel and crosstalk transfer functions by using a generalization of previous work due to Salz. Conditions are given under which the equalizer can completely eliminate both near and farend crosstalk and intersymbol interference. The MMSE transmitter filter, subject to a transmitted power constraint, is specified when the channel and crosstalk transfer functions are bandlimited to the Nyquist frequency. Also considered is the design of MMSE transmitter and receiver filters when the data signals are arbitrary widesense stationary continuous or discretetime signals, corresponding to the situation where the crosstalk is not phasesynchronous with the desired signal. For a particular twoinput/twooutput discretetime channel model, we study the behavior of the MMSE, assuming FIR transmitter and receiver filters, as a function of how the matrix taps are allocated between these filters, and on timing phase. In this case, the jointly optimal transmitter and receiver filters are obtained numerically using an iterative technique. For the channel model considered, the MSE is a very sensitive function of timing phase, but is nearly independent of how taps are allocated between the transmitter and receiver filters. I.
Multiuser MIMOOFDM for NextGeneration Wireless Systems
, 2007
"... This overview portrays the 40year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multipleinput multipleoutput (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highl ..."
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Cited by 17 (4 self)
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This overview portrays the 40year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multipleinput multipleoutput (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the socalled rankdeficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their stateoftheart solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMOOFDM systems and characterizes their achievable performance. A further section aims for identifying novel cuttingedge genetic algorithm (GA)aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GAassisted optimization techniques, which were recently proposed also
Transmitter and receiver optimization in multicarrier CDMA systems
 IEEE Trans. Commun
, 2000
"... Abstract—In this paper, we consider transmitter and receiver optimization in multicarrier codedivision multipleaccess (MCCDMA) systems under Rayleigh fading channels. Receiver optimization is performed in a decentralized manner, while transmitter optimization can be performed through either centr ..."
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Cited by 17 (2 self)
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Abstract—In this paper, we consider transmitter and receiver optimization in multicarrier codedivision multipleaccess (MCCDMA) systems under Rayleigh fading channels. Receiver optimization is performed in a decentralized manner, while transmitter optimization can be performed through either centralized or decentralized control of the powers of different carriers. Results show that when the number of users is smaller than or equal to the number of carriers, each transmitter often tends to concentrate its power on a different carrier which does not suffer deep fading. The MCCDMA system then tends to a frequencydivision multipleaccess system with nearoptimal frequency assignment. When the number of users gets large, each user tends to choose more than one carrier, which do not suffer deep fading, while interference suppression is performed across the chosen carriers by the corresponding receiver. Index Terms—Codedivision multiple access, fading channels, multicarrier modulation, power control, transmitter–receiver optimization. I.
Multichannel signal processing for data communications in the presence of crosstalk
 IEEE Trans. Commun
, 1990
"... Abstruct We consider transmission of data over multiple coupled channels, such as bundles of twistedpair copper wires in the local subscriber loop, and between central offices in the public switched telephone network. Transceiver designs for such channels typically treat the crosstalk between ad ..."
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Cited by 14 (0 self)
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Abstruct We consider transmission of data over multiple coupled channels, such as bundles of twistedpair copper wires in the local subscriber loop, and between central offices in the public switched telephone network. Transceiver designs for such channels typically treat the crosstalk between adjacent twisted pairs as random noise uncorrelated with the transmitted signal. We propose a transmitterheceiver pair that compensates for crosstalk by treating an entire bundle of twisted pairs as a single multiinput~ultioutput channel with a (slowly varying) matrix transfer function. The proposed transceiver uses multichannel adaptive FIR filters to cancel near and farend crosstalk, and to pre and postprocess the input/output of the channel. The linear pre and postprocessors that minimize mean squared error between the received and transmitted signal in the presence of both near and farend crosstalk are derived. The performance of an adaptive nearend crosstalk canceller using the stochastic gradient (LMS) transversal algorithm is illustrated via numerical simulation. Plots of mean squared error versus time and eye diagrams are presented assuming a standard transmission line model for the channel. A signal design algorithm that maps a vector input bit stream to a stream of channel symbol vectors is also presented. This algorithm is illustrated explicitly for a simple model of two coupled channels. It is shown that the achievable rate using the proposed signaling scheme is very close to the rate attainable in the absence of farend crosstalk, and is significantly greater than the achievable rate assuming that farend crosstalk is treated as additive noise with unknown statistics. 0 I.