Multiuser channel allocation algorithms achieving hard fairness

Toufik, Issam; Knopp, Raymond

doi:10.1109/glocom.2004.1377929

Cited by 13 publications

(11 citation statements)

References 20 publications

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“…However, full channel knowledge is not always attainable or practical, especially if the channel is varying rapidly or in systems with many users. As a result, there has been increased interest in studying the effect of reduced CSI on multi-user diversity and sum rate capacity, for example [1], [7], [8], [9], [10], [11], [12] among others. It was suggested in [1] that, using random beams and partial feedback, opportunistic beamforming is performed at the transmitter.…”

Section: Introductionmentioning

confidence: 99%

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Reduced feedback and random beamforming for OFDM MIMO broadcast channels

Fakhereddin

Sharif

Hassibi

2009

IEEE Trans. Commun.

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Abstract-It has been shown that random beamforming using partial channel state information (CSI) achieves the same throughput scaling as obtained from dirty paper coding for a broadcast (downlink) channel with transmit antennas and users where is large [1]. In this paper, we apply this scheme to wideband MIMO broadcast channels. By using OFDM, an -tap wideband channel can be decomposed to parallel narrowband channels (subcarriers), where > . Neighboring subcarriers are highly correlated. Therefore, we consider neighboring subcarriers as a cluster and find the closed form solution for the joint characteristic function of SINR values at two subcarriers in a cluster. We show numerically how the knowledge of the quality of the center subcarrier sheds light about the quality of other subcarriers in the same cluster, and address the issue of cluster size. In addition, through complex and asymptotic analysis, we show that for cluster size of order √ log (for large ), users need only feedback the best SINR at the center subcarrier of each cluster in order for the transmitter to perform opportunistic beamforming and maintain the same throughput scaling as when full CSI is available. Using simulation results, we verify our analytical result and show that even fewer feedback can be tolerated, and larger clusters ( 2 ) can be implemented for a small throughput hit.Index Terms-Channel state information, OFDM, broadcast channel, random beamforming, multi-user diversity, wireless communications.

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Section: Introductionmentioning

confidence: 99%

“…It has also been suggested in [10] that one bit feedback can be used at each subcarrier in order to perform opportunistic subcarrier allocation. In [12], dynamic allocation alogorithms were investigated for multiple antenna wideband systems to show that multi-user diversity can still be achieved even under a hard fairness constraint.…”

Section: Introductionmentioning

confidence: 99%

Reduced feedback and random beamforming for OFDM MIMO broadcast channels

Fakhereddin

Sharif

Hassibi

2009

IEEE Trans. Commun.

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“…[6], [7], [8], [9], [10] and references therein. However, the max-min fair allocation of power, bandwidth and time to multiple users sharing the parallel channels access still poses practical problems and needs a deeper understanding [1], [11]. The issue of maxmin fairness in (multi-user) parallel channels has been addressed in [11], [12], [13], [14] and references therein.…”

Section: Introductionmentioning

confidence: 99%

A new graph perspective on max-min fairness in Gaussian parallel channels

Wiczanowski¹,

Boche²

2008

2008 International Symposium on Information Theory and Its Applications

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In this work we are concerned with the problem of achieving max-min fairness in Gaussian parallel channels with respect to a general performance function, including channel capacity or decoding reliability as special cases. As our central results, we characterize the laws which determine the value of the achievable max-min fair performance as a function of channel sharing policy and power allocation (to channels and users). In particular, we show that the max-min fair performance behaves as a specialized version of the Lovasz function, or Delsarte bound, of a certain graph induced by channel sharing combinatorics. We also prove that, in addition to such graph, merely a certain 2-norm distance dependent on the allowable power allocations and used performance functions, is sufficient for the characterization of max-min fair performance up to some candidate interval. Our results show also a specific role played by odd cycles in the graph induced by the channel sharing policy and we present an interesting relation between max-min fairness in parallel channels and optimal throughput in an associated interference channel. Index TermsLovasz function, Delsarte bound, parallel channels, max-min fairness, graphs 1 2 is defined as (x 1 2 ) k = √ x k . The identity matrix is denoted by I, e k is the unit vector such that (e k ) k = 1 and (e k ) l = 0, k = l, and we also define vector 1 as (1) k = 1, where in all three cases the matrix/vector dimension follows from the context. By x, y we denote the inner product of x, y ∈ C K . Without introducing ambiguity, we do not differ in the notation between random values and deterministic values. The mean of a random matrix (variable) X ∈ C K×N is denoted as E(X).

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“…A very important feature of OFDMA is its capability of exploiting the Multiuser Diversity [1], which, combined with dynamic resource allocation, can increase significantly the system throughput, even in the case where hard fairness between active users is required [2], [3].…”

Section: Introductionmentioning

confidence: 99%

MIMO-OFDMA Opportunistic Beamforming with Partial Channel State Information

Toufik

Kim

2006

2006 IEEE International Conference on Communications

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Abstract-Over the past few years, a lot of interest has focused on Orthogonal Frequency Division Multiple Access (OFDMA) and Multiple Input Multiple Output (MIMO) systems thanks to the tremendous gain on system capacity they offer. Transmit beamforming is a low complexity technique that helps in achieving the full diversity afforded by the multiple antenna environment. MIMO-OFDMA systems using opportunistic beamforming are a promising solution to satisfy the growing demand in terms of data rate and Quality of Service (QoS).An important practical issue in MIMO-OFDMA systems is the feedback load. As a large number of carriers (e.g. 2048 for WiMax) is usually used in such systems, feeding back full Channel State Information at the transmitter (CSIT) for each carrier is prohibitive. In this paper, the problem of feedback reduction in MIMO-OFDMA opportunistic beamforming is addressed. We present different partial CSIT schemes that reduce significantly the feedback overload at little expense of system throughput.

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Multiuser channel allocation algorithms achieving hard fairness

Cited by 13 publications

References 20 publications

Reduced feedback and random beamforming for OFDM MIMO broadcast channels

Reduced feedback and random beamforming for OFDM MIMO broadcast channels

A new graph perspective on max-min fairness in Gaussian parallel channels

MIMO-OFDMA Opportunistic Beamforming with Partial Channel State Information

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