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.

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On Limits of Wireless Communications in a Fading Environment when UsingMultiple Antennas

Wireless Communications

Alhussein Abouzeid Rensselaer Polytechnic Institute Raviraj Adve University of Toronto Dharma Agrawal University of Cincinnati Walid Ahmed Tyco M/A-COM Sonia Aissa University of Quebec, INRSEMT Huseyin Arslan University of South Florida Nallanathan Arumugam National University of Singapore Saewoong Bahk Seoul National University Claus Bauer Dolby Laboratories Brahim Bensaou Hong Kong University of Science and Technology Rick Blum Lehigh University Michael Buehrer Virginia Tech Antonio Capone Politecnico di Milano Javier Gómez Castellanos National University of Mexico Claude Castelluccia INRIA Henry Chan The Hong Kong Polytechnic University Ajit Chaturvedi Indian Institute of Technology Kanpur Jyh-Cheng Chen National Tsing Hua University Yong Huat Chew Institute for Infocomm Research Tricia Chigan Michigan Tech Dong-Ho Cho Korea Advanced Institute of Science and Tech. Jinho Choi University of New South Wales Carlos Cordeiro Philips Research USA Laurie Cuthbert Queen Mary University of London Arek Dadej University of South Australia Sajal Das University of Texas at Arlington Franco Davoli DIST University of Genoa Xiaodai Dong, University of Alberta Hassan El-sallabi Helsinki University of Technology Ozgur Ercetin Sabanci University Elza Erkip Polytechnic University Romano Fantacci University of Florence Frank Fitzek Aalborg University Mario Freire University of Beira Interior Vincent Gaudet University of Alberta Jairo Gutierrez University of Auckland Michael Hadjitheodosiou University of Maryland Zhu Han University of Maryland College Park Christian Hartmann Technische Universitat Munchen Hossam Hassanein Queen's University Soong Boon Hee Nanyang Technological University Paul Ho Simon Fraser University Antonio Iera University "Mediterranea" of Reggio Calabria Markku Juntti University of Oulu Stefan Kaiser DoCoMo Euro-Labs Nei Kato Tohoku University Dongkyun Kim Kyungpook National University Ryuji Kohno Yokohama National University Bhaskar Krishnamachari University of Southern California Giridhar Krishnamurthy Indian Institute of Technology Madras Lutz Lampe University of British Columbia Bjorn Landfeldt The University of Sydney Peter Langendoerfer IHP Microelectronics Technologies Eddie Law Ryerson University in Toronto

Wireless communications

An approach to the general problem of signal parameter estimation is described. The algorithm differs from its predecessor in that a total least-squares rather than a standard least-squares criterion is used. Although discussed in the context of direction-of-arrival estimation, ESPRIT can be applied to a wide variety of problems including accurate detection and estimation of sinusoids in noise. It exploits an underlying rotational invariance among signal subspaces induced by an array of sensors with a translational invariance structure. The technique, when applicable, manifests significant performance and computational advantages over previous algorithms such as MEM, Capon's MLM, and MUSIC. >

ESPRIT-estimation of signal parameters via rotational invariance techniques

A cellular base station serves a multiplicity of single-antenna terminals over the same time-frequency interval. Time-division duplex operation combined with reverse-link pilots enables the base station to estimate the reciprocal forward- and reverse-link channels. The conjugate-transpose of the channel estimates are used as a linear precoder and combiner respectively on the forward and reverse links. Propagation, unknown to both terminals and base station, comprises fast fading, log-normal shadow fading, and geometric attenuation. In the limit of an infinite number of antennas a complete multi-cellular analysis, which accounts for inter-cellular interference and the overhead and errors associated with channel-state information, yields a number of mathematically exact conclusions and points to a desirable direction towards which cellular wireless could evolve. In particular the effects of uncorrelated noise and fast fading vanish, throughput and the number of terminals are independent of the size of the cells, spectral efficiency is independent of bandwidth, and the required transmitted energy per bit vanishes. The only remaining impairment is inter-cellular interference caused by re-use of the pilot sequences in other cells (pilot contamination) which does not vanish with unlimited number of antennas.

Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas

The paper investigates the use of sphere decoding on multiple-input multiple-output (MIMO) maximum-likelihood (ML) detection for complexity reduction. The problem is important for both multiuser detection and space-time decoding. In particular, we focus on the design of the decoding order which, if designed properly, can miniaturize the decoding hypersphere faster, leading to much complexity reduction. Our proposal is to sort the lattice points, within the intervals defined by the radius of the hypersphere, according to their distance from a given reference signal point, and search the coordinates closest to the chosen reference. A rather surprising result is that by defining the reference point as the soft-output signal point of a conventional receiver, such as zero-forcing (ZF), minimum mean-square-error (MMSE), or interference cancellation (IC), we can naturally combine any known receivers into a sphere decoder for ML detection and greatly reduce the decoding complexity without compromising the performance.

On the decoding order of MIMO maximum-likelihood sphere decoder: linear and non-linear receivers

We consider a source radiated signal arriving at an array as a group of wavefronts, each having a different angle of arrival and with arbitrary amplitude, phase and inter wavefront correlation. Several such sources may be present and the measurement data is assumed to be corrupted by sensor to sensor uncorrelated noise. The task of the beamformer is to make optimal estimates of each source signal of interest by using the information in all the wavefronts generated by the source. The proposed processor begins with no apriori information about the environment and constructs the optimal beamformer by a bootstrapping approach which uses a two tier eigenstructure analysis of the array covariance. We show that this new beamformer has substantial advantages over the usual optimal beamformers and present results of computer simulation carried out to verify its performance.

On beamforming in presence of multipath

We analyze the performance of sequential geometric programming (SGP) in solving the nonconvex power control problem of maximizing the sum capacity of the interference channel with no multiuser decoding. We focus on the 2x2 interference channel, for which we know the optimal power allocation tuples. We validate the SGP approaches of single and double condensation methods and we analyze the accuracy and convergence performance of each.

Sequential Geometric Programming for 2 × 2 Interference Channel Power Control

We present a simple adaptive modulation scheme for multiple antenna systems. Assuming a linear MMSE receiver and a QoS requirement, we show how to use the signal to interference and noise ratio (SINR) information at the receiver output to optimize the data rate for each transmit antenna. Next, we present an iterative adaptive modulation scheme that provides better throughput when compared to the previous scheme, but takes a hit in implementation complexity. We assume perfect channel knowledge at the receiver and the existence of some minimal feedback link to the transmit antennas.

Arogyaswami Paulraj

Papers

On the decoding order of MIMO maximum-likelihood sphere decoder: linear and non-linear receivers

On beamforming in presence of multipath

Sequential Geometric Programming for 2 × 2 Interference Channel Power Control

Adaptive modulation for multiple antenna systems

On the decoding order of MIMO maximum-likelihood sphere decoder: linear and non-linear receivers