QoS aware power allocation for combined guaranteed performance and best effort users in OFDMA systems

Anas, M.; Kim, Kanghee; Shin, Seokjoo; Kim, Kiseon

doi:10.1109/ispacs.2004.1439101

Cited by 22 publications

(20 citation statements)

References 9 publications

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“…To solve the above equation, LU factorization (factorization of a matrix in to lower and upper triangular matrices of the same size respectively) is performed on the coefficient matrix. Finally, using forwards-backwards substitution, the individual user powers are given by The power of individual subchannel is found using the water-filling algorithm [10].…”

Section: Linear Methods Of Subcarrier and Power Allocationmentioning

confidence: 99%

Adaptive Subcarrier and Bit Allocation for Downlink OFDMA System with Proportional Fairness

Lande¹,

Helonde²,

Pande³

et al. 2011

IJWMN

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Section: Linear Methods Of Subcarrier and Power Allocationmentioning

confidence: 99%

Adaptive Subcarrier and Bit Allocation for Downlink OFDMA System with Proportional Fairness

Lande¹,

Helonde²,

Pande³

et al. 2011

IJWMN

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show abstract

“…However, due to the strict proportionality, the utilization of subcarriers is low and thus decreasing the overall sum rate. Considering the same problem formulation, two types of users' applications, best-effort (BE) and guaranteed-performance (GP), were distinguished on the basis of required QoS in [9]. The proposed method maximizes the sum capacity of BE users subject to rate constraints of GP users.…”

Section: Related Workmentioning

confidence: 99%

A cross-layer resource allocation scheme for spatial multiplexing-based MIMO-OFDMA systems

Akbudak

Al-Shatri

Czylwik

2011

J Wireless Com Network

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We investigate the resource allocation problem for the downlink of a multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) system. The sum rate maximization itself cannot cope with fairness among users. Hence, we address this problem in the context of the utility-based resource allocation presented in earlier papers. This resource allocation method allows to enhance the efficiency and guarantee fairness among users by exploiting multiuser diversity, frequency diversity, as well as time diversity. In this paper, we treat the overall utility as the quality of service indicator and design utility functions with respect to the average transmission rate in order to simultaneously provide two services, real-time and best-effort. Since the optimal solutions are extremely computationally complex to obtain, we propose a suboptimal joint subchannel and power control algorithm that converges very fast and simplifies the MIMO resource allocation problem into a single-input single-output resource allocation problem. Simulation results indicate that using the proposed method achieves near-optimum solutions, and the available resources are distributed more fairly among users.Keywords: Cross-layer optimization, Utility-based resource allocation, MIMO-OFDMA, Water-filling I IntroductionExploiting the channel variation across users, channelaware resource allocation can substantially improve network performance through multiuser diversity [1]. The key idea is to select those users having the best channel condition at each individual subchannel independently. This maximizes the sum rate as well as spectral efficiency. However, sum rate maximization is sometimes unfair to cell-edge users or those with bad channel conditions [2] and thus cannot guarantee their quality of service (QoS) requirements. On the other hand, absolute fairness may decrease efficiency and system capacity. Therefore, a practical resource allocation scheme should carefully tradeoff efficiency versus fairness. As a result, joint channel-and QoS-aware resource allocation would be more beneficial compared to channel-aware resource allocation.In this paper, we consider a single-cell of a cellular orthogonal frequency division multiple access (OFDMA) network with multiple types of services, namely besteffort and real-time, which are distinguished by their required QoS. For each service type, we introduce a utility function depending on the average transmission rate in order not only to balance fairness and efficiency but also to achieve cross-layer optimization. The overall network utility, which is the sum of the utilities of all users, is then treated as the optimization objective. For the considered problem, we propose a joint sub-carrier and power allocation algorithm that simplifies the multipleinput multiple-output (MIMO) resource allocation into a single-input single-output (SISO) resource allocation problem. By employing the proposed algorithm, it will be shown that real-time users get higher priorities than best-ef...

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“…So the subchannels among CBR users and BE are allocated dynamically and efficiently, and both parts can utilize any subchannel independent of their services. Relative to partitioning subchannels for different services [6], the proposed scheme allocates the resources more efficiently.…”

Section: ) Initializationmentioning

confidence: 99%

“…Anas et. al.,in [6], propose an efficient algorithm for power distribution among two types of OFDMA users, but their subchannel allocation method is inefficient since it is fixed in time. In [7] like [6], K. Kim et.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

QoS Aware Dynamic Resource Allocation in Multiuser OFDM Systems with Priority for Different Services

Ramezani

Lavafi

Abolhassani

2008

2008 International Wireless Communications and Mobile Computing Conference

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In this paper, we propose an algorithm for dynamic resource allocation in OFDM (orthogonal frequency division multiplexing) or OFDMA (OFD multiple access) based networks. We consider two groups of users consisting of group 1 called constant bit-rate (CBR) users (who are delay-sensitive and data-rate sensitive) and group 2 called best effort (BE) users. The proposed algorithm gives higher priority to the first group at the time of resource (transmitted power levels and subchannels) allocation to each user, to meet their CBR requirements. The performance of the proposed algorithm is evaluated through computer simulations, which show that the algorithm performs near optimum with the added superiority of meeting the bit requirements of the first group users.

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QoS aware power allocation for combined guaranteed performance and best effort users in OFDMA systems

Cited by 22 publications

References 9 publications

Adaptive Subcarrier and Bit Allocation for Downlink OFDMA System with Proportional Fairness

Adaptive Subcarrier and Bit Allocation for Downlink OFDMA System with Proportional Fairness

A cross-layer resource allocation scheme for spatial multiplexing-based MIMO-OFDMA systems

QoS Aware Dynamic Resource Allocation in Multiuser OFDM Systems with Priority for Different Services

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