A Throughput Analysis for Opportunistic Beamforming with Quantized Feedback

Vicario, José López; Bosisio, R.; Spagnolini, Umberto; Antón-Haro, Carles

doi:10.1109/pimrc.2006.253978

Cited by 18 publications

(9 citation statements)

References 14 publications

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“…Single feedback bit versions of this work can be found in [77], [240], [359]. Multiple feedback bit analysis is contained in [189]. This technique can also be extended to probe with multiple precoders [119].…”

Section: ) Single Receive Antennasmentioning

confidence: 99%

An overview of limited feedback in wireless communication systems

Love

Heath

Lau

et al. 2008

IEEE J. Select. Areas Commun.

1,343

918

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Abstract-It is now well known that employing channel adaptive signaling in wireless communication systems can yield large improvements in almost any performance metric. Unfortunately, many kinds of channel adaptive techniques have been deemed impractical in the past because of the problem of obtaining channel knowledge at the transmitter. The transmitter in many systems (such as those using frequency division duplexing) can not leverage techniques such as training to obtain channel state information. Over the last few years, research has repeatedly shown that allowing the receiver to send a small number of information bits about the channel conditions to the transmitter can allow near optimal channel adaptation. These practical systems, which are commonly referred to as limited or finite-rate feedback systems, supply benefits nearly identical to unrealizable perfect transmitter channel knowledge systems when they are judiciously designed. In this tutorial, we provide a broad look at the field of limited feedback wireless communications. We review work in systems using various combinations of single antenna, multiple antenna, narrowband, broadband, single-user, and multiuser technology. We also provide a synopsis of the role of limited feedback in the standardization of next generation wireless systems.

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Section: ) Single Receive Antennasmentioning

confidence: 99%

An overview of limited feedback in wireless communication systems

Love

Heath

Lau

et al. 2008

IEEE J. Select. Areas Commun.

1,343

918

View full text Add to dashboard Cite

show abstract

“…Independently from our work (part of it initially presented in [13], [14]), the pure concept of beam selection has been recently investigated and further developed in [15] and [16]. Our contribution here is more extensive as we compare different beam selection methods and consider the inherent trade-offs in terms of system performance vs. the amount of information required in the feedback channel.…”

Section: Relation To Prior Workmentioning

confidence: 99%

“…Finally, by introducing the previous result in (14) and by taking into account (13), one can re-writte the aggregated throughput in the presence of adaptive modulation as:…”

Section: A Closed-form Expressionmentioning

confidence: 99%

Beam Selection Strategies for Orthogonal Random Beamforming in Sparse Networks

Vicario

Bosisio

Antón-Haro

et al. 2008

IEEE Trans. Wireless Commun.

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Abstract-Orthogonal random beamforming (ORB) constitutes a mean to exploit spatial multiplexing and multi-user diversity (MUD) gains in multi-antenna broadcast channels. To do so, as many random beamformers as transmit antennas (M ) are generated and on each beam the user experiencing the most favorable channel conditions is scheduled. Whereas for a large number of users the sum-rate of ORB exhibits an identical growth rate as that of dirty paper coding, performance in sparse networks (or in networks with an uneven spatial distribution of users) is known to be severely impaired. To circumvent that, in this paper we modify the scheduling process in ORB in order to select a subset out of the M available beams. We propose several beam selection algorithms and assess their performance in terms of sum-rate and aggregated throughput (i.e., rate achieved with practical modulation and coding schemes), along with an analysis of their computational complexity. Since ORB schemes require partial channel state information (CSI) to be fed back to the transmitter, we finally investigate the impact of CSI quantization on system performance. More specifically, we prove that most of the MUD can be still exploited with very few quantization bits and we derive a beam selection approach trading-off system performance vs. feedback channel requirements.Index Terms-Orthogonal Random Beamforming (ORB), beam selection, sparse networks, opportunistic scheduling, Multiuser Diversity (MUD), broadcast channel, feedback quantization.

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“…In [6], for instance, the authors found that in a SISO context most of the MUD gain can still be extracted when the measured SNRs are quantized with very few bits. In a MIMO context, we analyzed in [7] This work is partially supported by the IST projects NEWCOM (50725) and ACE2 (26957) and the Generalitat de Catalunya (SGR2005-00690) the impact of CSI quantization on the throughput and the sum-rate of ORB beamforming. The limiting case of one-bit quantizers deserves some attention as well.…”

Section: Introductionmentioning

confidence: 99%

“…in a MIMO setting); (2) identifying the optimal set of quantization thresholds and, (3) comparing the performance of such optimal quantizer with that of a uniform one. We also go one step beyond [7] and move from a heuristic quantization law to the optimal one, being this de ned by a set of pdf-matched quantization intervals. Since this problem cannot be solved analytically we must resort to a numerical solution.…”

Section: Introductionmentioning

confidence: 99%

Optimal Quantization Schemes for Orthogonal Random Beamforming - A Cross-Layer Approach

Antón-Haro

2007

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07

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Orthogonal random beamforming (ORB) has recently attracted signi cant interest because of its ability to exploit multi-user diversity and spatial multiplexing gains by exclusively using partial channel state information (CSI). In this paper, we explore the impact of CSI quantization on the performance of ORB. By resorting to a dynamic programming formulation, we identify the optimal (i.e. pdfmatched) quantizer for which the sum-rate distortion is minimized. This is a cross-layer approach in the sense that the optimal quantizer (physical layer) actually depends on other layers' parameters such as the number of admitted users (link layer). Performance is assessed by means of computer simulations and compared with that of a uniform quantizer.

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A Throughput Analysis for Opportunistic Beamforming with Quantized Feedback

Cited by 18 publications

References 14 publications

An overview of limited feedback in wireless communication systems

An overview of limited feedback in wireless communication systems

Beam Selection Strategies for Orthogonal Random Beamforming in Sparse Networks

Optimal Quantization Schemes for Orthogonal Random Beamforming - A Cross-Layer Approach

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