A new weighted proportional fair scheduling algorithm for SDMA/OFDMA systems

Huang, Wei; Sun, Kai; Tan, Bo

doi:10.1109/chinacom.2008.4685083

Cited by 2 publications

(14 citation statements)

References 8 publications

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“…with constraints (12)(13)(14)(15). The value of the dual function Θ at some point (λ, µ) is obtained by minimizing the Lagrange function over the primal variables…”

Section: Dual-based Solution Methodsmentioning

confidence: 99%

“…In [13], the objective is to maximize a utility function without any hard minimum rate constraints for the RT users. The channel quality information is added to the utility function to favor users with good channel conditions and priorities are set by increasing user weights in the utility function.…”

Section: State Of the Artmentioning

confidence: 99%

“…Constraint (12) guarantees that we do not choose more than M users for each subcarrier, constraint (13) guarantees that if we have chosen two users k and j, they meet the ZF constraints and is redundant for other users, and constraint (14) guarantees that the beamforming vector is zero for users that are not chosen. Problem (9)(10)(11)(12)(13)(14) is a non-linear mixed integer program (MIP) and these are known to be very hard to solve exactly. In this paper, whenever we need to get an exact solution, we use a complete enumeration of the binary variables α satisfying the constraints (12).…”

Section: Zero-forcing Beamformingmentioning

confidence: 99%

“…Algorithm 1 finds the optimal dual variables (λ * , µ * ) that solve the dual problem (18) using the subgradient method [19] with a fixed step size δ and therefore yields an upper bound to problem (9)(10)(11)(12)(13)(14)(15). In algorithm 1, the pseudoinverse matrices G + k,n,s can be computed by any number of well known algorithms.…”

Section: Algorithm 1 Calculation Of the Dual Problemmentioning

confidence: 99%

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Dual-based bounds for resource allocation in zero-forcing beamforming OFDMA-SDMA systems

Perea-Vega

Girard

Frigon

2013

J Wireless Com Network

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We consider multi-antenna base stations using orthogonal frequency-division multiple access and space division multiple access techniques to serve single-antenna users. Some users, called real-time users, have minimum rate requirements and must be served in the current time slot while others, called non real-time users, do not have strict timing constraints and are served on a best-effort basis. The resource allocation (RA) problem is to find the assignment of users to subcarriers and the transmit beamforming vectors that maximize the total user rates subject to power and minimum rate constraints. In general, this is a nonlinear and non-convex program and the zero-forcing technique used here makes it integer as well, exact optimal solutions cannot be computed in reasonable time for realistic cases. For this reason, we present a technique to compute both upper and lower bounds and show that these are quite close for some realistic cases. First, we formulate the dual problem whose optimum provides an upper bound to all feasible solutions. We then use a simple method to get a primal-feasible point starting from the dual optimal solution, which is a lower bound on the primal optimal solution. Numerical results for several cases show that the two bounds are close so that the dual method can be used to benchmark any heuristic used to solve this problem. As an example, we provide numerical results showing the performance gap of the well-known weight adjustment method and show that there is considerable room for improvement.

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“…with constraints (12)(13)(14)(15). The value of the dual function Θ at some point (λ, µ) is obtained by minimizing the Lagrange function over the primal variables…”

Section: Dual-based Solution Methodsmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

Section: Zero-forcing Beamformingmentioning

confidence: 99%

Section: Algorithm 1 Calculation Of the Dual Problemmentioning

confidence: 99%

See 2 more Smart Citations

Dual-based bounds for resource allocation in zero-forcing beamforming OFDMA-SDMA systems

Perea-Vega

Girard

Frigon

2013

J Wireless Com Network

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“…[6], [7], [8]. More generic (p, α)-PF fair scheduling was investigated in [9], and modified PF schedulers that may be interpreted as (p, α)-PF fair were suggested in [10], [11], although this in not explicitly stated in the papers. All the above mentioned papers utilize the so called gradient scheduling principle, in which sub-channels are assigned based on a metric u ′ i (x i )µ ij where µ ij denotes the data rate of the sub-channel j if user i is assigned to it, and u ′ i (x i ) denotes derivative the utility function u i (x i ) that describes the utility that user i obtains if it achieves mean throughput x i .…”

Section: Introductionmentioning

confidence: 99%

On α-proportional fair packet scheduling in OFDMA downlink

Tirkkonen

Jäntti

2012

2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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We consider resource allocation in block fading downlink Orthogonal Frequency Division Multiple access systems with infinitely divisible resources. The proportional fairness of the scheduler is characterized by a parameter α. In block-fading channels, one-shot utility maximization may be performed. We investigate properties of resulting α-Proportionally Fair scheduling decisions. We find that an optimal schedule is cycle free: no K users share K resources so that each gets a fraction of at least two resources. Most scheduling weights vanish. For N users sharing M resources, there are at most N +M −1 non-zero scheduling weights.

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A new weighted proportional fair scheduling algorithm for SDMA/OFDMA systems

Cited by 2 publications

References 8 publications

Dual-based bounds for resource allocation in zero-forcing beamforming OFDMA-SDMA systems

Dual-based bounds for resource allocation in zero-forcing beamforming OFDMA-SDMA systems

On α-proportional fair packet scheduling in OFDMA downlink

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A new weighted proportional fair scheduling algorithm for SDMA/OFDMA systems

Cited by 2 publications

References 8 publications

Dual-based bounds for resource allocation in zero-forcing beamforming OFDMA-SDMA systems

Dual-based bounds for resource allocation in zero-forcing beamforming OFDMA-SDMA systems

On &#x03B1;-proportional fair packet scheduling in OFDMA downlink

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On α-proportional fair packet scheduling in OFDMA downlink