Joint scheduling and resource allocation in uplink OFDM systems for broadband wireless access networks

Huang, Jianwei; Subramanian, Vijay; Agrawal, Rajeev; Berry, Randall A.

doi:10.1109/jsac.2009.090213

Cited by 260 publications

(200 citation statements)

References 22 publications

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“…For example, joint scheduling and zero-forcing beamforming is studied in [41], and joint scheduling and opportunistic beamforming is studied [42], but both without power optimization, while [43], [44] consider beamforming with power allocation, but without scheduling. Finally, [45], [46], [47], [48], [49] consider joint scheduling and power control, but without beamforming,…”

Section: E Related Workmentioning

confidence: 99%

Multicell Coordination via Joint Scheduling, Beamforming, and Power Spectrum Adaptation

Kwon

Shin

2013

IEEE Trans. Wireless Commun.

168

147

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Abstract-The mitigation of intercell interference is a central issue for future generation wireless cellular networks where frequencies are reused aggressively and where hierarchical cellular structures may heavily overlap. The paper examines the benefit of coordinating transmission strategies and resource allocation schemes across multiple cells for interference mitigation. For a multicell network serving multiple users per cell sectors and where both the base-stations and the remote users are equipped with multiple antennas, this paper proposes a joint proportionally fair scheduling, spatial multiplexing, and power spectrum adaptation method that coordinates multiple basestations with an objective of optimizing the overall network utility. The proposed scheme optimizes the user schedule, transmit and receive beamforming vectors, and transmit power spectra jointly, while taking into consideration both the intercell and intracell interference and the fairness among the users. The proposed system is shown to significantly improve the overall network throughput while maintaining fairness as compared to a conventional network with per-cell zero-forcing beamforming and with fixed transmit power spectrum. The proposed system goes toward the vision of a fully coordinated multicell network, whereby transmission strategies and resource allocation schemes (rather than transmit signals) are coordinated across the basestations as a first step. I. OVERVIEW A. IntroductionIntercell interference is a fundamental limiting factor in wireless cellular networks. A promising idea for the mitigation of intercell interference in future cellular networks is the coordination of multiple base-stations. In a fully coordinated multicell system, multiple antennas across multiple basestations can be thought of as forming a large antenna array, where intercell interference can be actively exploited. The realization of such a fully coordinated system, however, also requires high-capacity backhaul communication. As antennas from across multiple base-stations need to jointly transmit and receive signals for multiple mobile users, data streams of multiple users must be shared among multiple base-stations. This paper explores a different type of coordination where user transmission strategies and resource allocation schemes, rather than data signals, are coordinated across the basestations. The coordination of transmission strategies clearly requires much less backhaul communication, and is much easier to implement in a practical deployment. The goal of this paper is to show that by jointly setting the scheduling, power allocation, and beamforming strategies of multiple basestations and multiple mobile users within each cell, intercell interference can already be alleviated, and the overall performance of the network can already be improved significantly as compared to the current generation of wireless networks where cells operate independently.Resource management has been the focus of extensive studies for cellular networks in the past, but tr...

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Section: E Related Workmentioning

confidence: 99%

Multicell Coordination via Joint Scheduling, Beamforming, and Power Spectrum Adaptation

Kwon

Shin

2013

IEEE Trans. Wireless Commun.

168

147

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“…Joint power control and scheduling has been investigated in the literature for both single-cell [10,11] and multicell systems [12][13][14][15]. The overall problem setup of this paper is closely related to that in [14,15], where power spectrum adaptation is jointly performed with proportionally fair scheduling.…”

Section: Related Workmentioning

confidence: 99%

Power spectrum optimization for interference mitigation via iterative function evaluation

Dahrouj

Tang

2012

J Wireless Com Network

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Power spectrum optimization is a well-known difficult nonconvex optimization problem for which only local optimality can typically be assured. This paper unifies several classes of local optimization methods and proposes efficient and new methods for power spectrum optimization by observing that methods for reaching the local optimal points can often be expressed in the form of an iterative function evaluation. This proposed new approach is based on the fact that the gradient of the objective function is zero at a local optimum, and that different manipulations of the optimality condition can then lead to different power update equations. As a practical application, this paper examines the benefit of dynamic power spectrum optimization for interference mitigation in a wireless backhaul network in which remote radio units are deployed to serve mobile users in areas with high data traffic demand. The remote radio units, called remote terminals (RT), are connected to access nodes (AN) via orthogonal frequency division multiple access (OFDMA) over a fixed bandwidth with one RT active in each frequency tone. The system performance is thus limited by internode interference solely, and no intranode interference. This paper shows that iterative function evaluation based methods provide a significant improvement in the overall network throughput in this setting as compared to a conventional network with fixed transmit power spectrum. The proposed methods have computationally fast convergence and can be implemented in a distributed fashion assuming reasonable amount of internode information exchange. Further, some of the proposed methods can be implemented asynchronously at each AN, which makes them amenable to practical utilization.

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“…The solution generated by the iterative algorithm satisfies the fairness constrains. Huang et al (2009) propose a gradient-based scheduling framework that changes the OFDM resource allocation into convex optimisation problem and solves it with Lagrange multiplier method. Unfortunately, the Lagrange method can not be used to solve the inequality constrained optimisation problem.…”

Section: Introductionmentioning

confidence: 99%

“…For the resource allocation model, the fairness of 4G mobile communication system has attracted many scholars' attention, such as Seo and Lee (2004), Mahmoud and Al-Rayyah (2010), and Huang et al (2009). A lot earlier research did not consider the fairness of the mobile communication system.…”

Section: Introductionmentioning

confidence: 99%

A resource allocation evolutionary algorithm for OFDM system

Wang

Liu

Li³

et al. 2017

IJCSE

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Abstract:Resource allocation for orthogonal frequency division multiplexing Orthogonal Frequency Division Multiplexing (OFDM) system, as a core technology for the 4th generation mobile communication system, has shown significant importance in the improvement of system transmission rate. At present, the two-step algorithm is described as a main method to deal with resource allocation for OFDM system. As carrier allocation and power allocation are not independent of each other, the two-step algorithm may result in lower complexity but poor convergence. This paper proposes a mixed evolutionary algorithm to allocate sub-carrier and power at the same time. It combines the simulated annealing algorithm and evolutionary algorithm. This paper also improves the definition of fairness in OFDM system. It can achieves perfect fairness among users while maintaining the efficient capacity performance. Simulation results demonstrate that the proposed resource allocation algorithm can achieve perfect performance, and increase the convergence rate greatly meanwhile efficiently improving the system capacity.Keywords: OFDM; resource allocation; evolutionary algorithm; simulated annealing algorithm.Reference to this paper should be made as follows: Wang, Q., Liu, H-L., Li, J-c. and Li, Y. Q. Wang et al.This paper is a revised and expanded version of a paper entitled 'Resource allocation for OFDM system based on evolutionary algorithm' presented at International

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Joint scheduling and resource allocation in uplink OFDM systems for broadband wireless access networks

Cited by 260 publications

References 22 publications

Multicell Coordination via Joint Scheduling, Beamforming, and Power Spectrum Adaptation

Multicell Coordination via Joint Scheduling, Beamforming, and Power Spectrum Adaptation

Power spectrum optimization for interference mitigation via iterative function evaluation

A resource allocation evolutionary algorithm for OFDM system

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