Resource allocation algorithms for minimum rates scheduling in MIMO‐OFDM systems

Klotz, Johannes; Knabe, Frederic; Huppert, Carolin

doi:10.1002/ett.1422

Cited by 6 publications

(8 citation statements)

References 5 publications

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“…In LTE and LTE‐Advanced the uplink allocation is further constrained by having a condition of contiguous allocation of resource blocks, which is comprised of a fixed number of subcarriers. Moreover, extending the work to handle MIMO channel as in has good potential.…”

Section: Resultsmentioning

confidence: 99%

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A dynamic radio resource management scheme for the IEEE 802.16 band‐adaptive modulation and coding mode with proportional rate constraints

Sokar

Elsayed

2011

Trans. Emerging Tel. Tech.

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In this paper, we consider the problem of downlink resource allocation in the IEEE 802.16 standard based on the orthogonal frequency‐division multiple access physical layer. The objective is to allocate the downlink frequency‐time slots and transmission power to different users such that the total throughput is maximized. The allocation is subject to constraints on the total transmission power and satisfying the quality of service requirements of different users expressed in terms of proportional rates. A three‐step heuristic scheme that incorporates a linear programming technique is proposed. The problem is modelled as an unbalanced transportation problem that is solved to obtain the users' slot assignment. The Vogel approximation method is used to efficiently solve the transportation problem with a slight degradation relative to the optimal solution. The Vogel approximation method gain is shown by replacing it in the three‐step heuristic by simple round‐robin or greedy slot assignment. In terms of total throughput and fairness, it is shown that the proposed scheme is a good compromise between the greedy‐oriented schemes, which aspire to maximize the total system throughput but sacrificing fairness, and a proportional rate constraints scheme introduced in the literature that achieved short‐term fairness but penalizes the total throughput. The study also shows that the proposed scheme consumes a fraction of the time needed by the proportional rate constraints scheme. Copyright © 2011 John Wiley & Sons, Ltd.

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Section: Resultsmentioning

confidence: 99%

“…Further work on multiple‐input multiple‐output (MIMO)‐OFDM resource allocation was reported by Klotz et al where they consider a MIMO‐OFDM downlink scenario, where each receiving mobile station has QoS requirements, namely minimum rate requirements. They proposed three schemes that can be used in a MIMO context only.…”

Section: Related Workmentioning

confidence: 99%

A dynamic radio resource management scheme for the IEEE 802.16 band‐adaptive modulation and coding mode with proportional rate constraints

Sokar

Elsayed

2011

Trans. Emerging Tel. Tech.

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“…Equality holds in (30) if and only if is diagonal. 9 As holds for the per-stream rates in the downlink after a stream-wise uplink-to-downlink transformation [37], the same per-user sum rate is achievable in the downlink.…”

Section: B Diagonalization Of the Mse Matricesmentioning

confidence: 87%

“…Sketch of Proof: For the sum rate of user , we have (30) where are the per-stream rates in the uplink and the righthand side of the inequality is the per-user sum rate achievable in the uplink with joint decoding of the streams of user [39]. Equality holds in (30) if and only if is diagonal.…”

Section: B Diagonalization Of the Mse Matricesmentioning

confidence: 99%

Gradient-Based Power Minimization in MIMO Broadcast Channels With Linear Precoding

Joham

Utschick

2012

IEEE Trans. Signal Process.

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We study the problem of minimizing the sum transmit power in mutliple-input multiple-output (MIMO) downlink channels with linear transceivers if per-user quality of service (QoS) constraints (expressed in terms of rates) have to be fulfilled. To find a suboptimal solution of the arising non-convex optimization problem, we introduce new auxiliary variables representing the division of the per-user rate constraints into per-stream rate targets, and we optimize these variables by means of gradient-projection steps. This new method is combined with alternating updates of the transmit and receive filters. Furthermore, the proposed algorithm ensures that the mean square error (MSE) matrices of all users are diagonal, and in the course of the execution of the algorithm, it is possible that inactive streams get activated if this leads to a decreased sum transmit power. In numerical simulations, the new algorithm turns out to be superior to the various existing methods since these methods either lead to a higher sum transmit power than the proposed scheme or have a higher computational complexity or make restrictive assumptions on the system parameters.Index Terms-Broadcast channels, gradient methods, linear transceivers, multiple-input multiple-output (MIMO), quality of service.

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“…Thus, various heuristic scheduling methods have been proposed to simplify the scheduling process , which perform close to the optimal ES for their respective precoding schemes. Further examples include for ZFB, which also incorporates some fairness measures into the scheduling, that considers orthogonal random beamforming, with clustered eigenbeamforming and that considers eigenbeamforming and zero‐forcing DPC and that attempts to provide users with minimum data rates.…”

Section: Introductionmentioning

confidence: 99%

Low complexity greedy, genetic and hybrid user scheduling algorithms for multiuser MIMO systems with successive zero‐forcing

Elliott

Sigdel

Krzymien

2012

Trans. Emerging Tel. Tech.

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In this paper, we consider low complexity user scheduling algorithms for multiuser multiple‐input multiple‐output systems employing successive zero‐forcing precoding. Optimal scheduling involves an exhaustive search (ES), which is prohibitively complex. Greedy algorithms (GrAs) with heuristic scheduling metrics achieve performance close to that of the ES. Meanwhile, genetic algorithms (GAs) are a rapid suboptimal option of optimising utility (e.g. scheduling) metrics. Herein, we evaluate the performance and complexity of greedy and genetic scheduling algorithms for successive zero‐forcing. We also propose and evaluate two hybrid algorithms combining the traits of the GrA and GA. The algorithms' performance is assessed through a series of computer simulations. We demonstrate both the GrA and GA achieve a near‐optimal sum rate with low complexity, whereas the hybrid algorithms further enhance the GrA and GA performance without an increase in the order of complexity.Copyright © 2012 John Wiley & Sons, Ltd.

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Resource allocation algorithms for minimum rates scheduling in MIMO‐OFDM systems

Cited by 6 publications

References 5 publications

A dynamic radio resource management scheme for the IEEE 802.16 band‐adaptive modulation and coding mode with proportional rate constraints

A dynamic radio resource management scheme for the IEEE 802.16 band‐adaptive modulation and coding mode with proportional rate constraints

Gradient-Based Power Minimization in MIMO Broadcast Channels With Linear Precoding

Low complexity greedy, genetic and hybrid user scheduling algorithms for multiuser MIMO systems with successive zero‐forcing

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