Multiuser Multimedia Resource Allocation Over Multicarrier Wireless Networks

Su, Yi; Schaar, Mihaela Der

doi:10.1109/tsp.2007.912258

Cited by 14 publications

(7 citation statements)

References 30 publications

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“…We do not make comparisons with other relatively new video resource allocation methods (e.g. [3]- [5]) due to the limitation that most of these methods aim at maximizing the Peak Signal-to-Noise Ratio (PSNR) of video, which is not identical to user experience. It is difficult to make a fair comparison between them.…”

Section: A Simulation Setupmentioning

confidence: 99%

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Fuzzy Logic Resource Allocator for Wireless Video Transmission in LTE System

Fei

Zhao

2015

2015 IEEE 81st Vehicular Technology Conference (VTC Spring)

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In wireless video transmission, encoded video frames are often transmitted with certain delay and reliability constrain. Due to the limited wireless bandwidth, time-variant channel conditions and the fluctuant video frame rate, it is difficult to allocate transmission resources to guarantee online video quality. In this paper, we propose a fuzzy logic resource allocator (FLRA), aiming at enhancing the user experience of different online video streams and increasing the system load. By jointly utilize the information of remainder play time of user equipments (UEs) and the varying channel conditions of different UEs, FLRA employed in the base station calculates the priority list and makes allocation in real time. The proposed FLRA is implemented in a Long Term Evolution (LTE) simulation system, in which three kinds of video streams are supported. Numerical results verify that the proposed method outperforms the conventional methods significantly, especially in high signal-to-noise ratio condition.978-1-4799-8088-8/15/$31.00 ©2015 IEEE

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Section: A Simulation Setupmentioning

confidence: 99%

“…In [3], multiuser video transmission over the uplink of multicarrier networks is studied, and resource allocation algorithm is given to maximize the total video qualities from the information-theoretic point of view. However, it does not jointly optimize system throughput and video quality together.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Resource Allocator for Wireless Video Transmission in LTE System

Fei

Zhao

2015

2015 IEEE 81st Vehicular Technology Conference (VTC Spring)

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“…The value of the variance can be minimized through iterative subcarrier exchange among PUs, and in each iteration, the exchange is only performed between two PUs. Similar to , we define A as the subcarrier exchange matrix as follows

A = [\begin{matrix} A_{11} & A_{12} & \dots & A_{1 N} \\ A_{21} & A_{22} & \dots & A_{2 N} \\ .... & .... & .... & .... \\ A_{N 1} & A_{N 2} & \dots & A_{N N} \end{matrix}],

where

A_{mn} MathClass-rel= 0 MathClass-punc, m MathClass-punc, n MathClass-rel\in {1 MathClass-punc, MathClass-op\dots MathClass-punc, N}

, if the subcarrier exchange between user N and user m is required, and A mn = 1 otherwise. To initiate, A is set to be a zero matrix.…”

Section: Co‐opetition Strategymentioning

confidence: 99%

Cooperative bargaining solution for efficient and fair spectrum management in cognitive wireless networks

Guan

Yuan

Zhang

et al. 2013

Int J Communication

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SUMMARY This paper studies the fairness among the primary users (PUs) and the secondary users (SUs) for resource allocation in cognitive radio systems. We propose a novel co‐opetition strategy based on the Kalai–Smorodinsky bargaining solution to balance the system efficiency and the fairness among users. The strategy formulates the spectrum sharing problem as a nonlinear and integral sum utility maximization subject to a set of constraints describing the co‐opetition among the PUs and the SUs. Then, we solve the maximization problem by proposing a heuristical method that consists of four steps: multi‐PU competition, PU's subcarrier contribution, multi‐SU competition, and SU's subcarrier contribution. Extensive simulation results are presented by comparing the co‐opetition strategy with several conventional ones, including the Kalai–Smorodinsky bargaining solution, sum rate maximization as well as the Max–Min. Results indicate that the co‐opetition strategy can jointly balance the system efficiency and fairness in multiuser resource allocation, as it is able to support more satisfied users and in the meanwhile improve the utility of those unsatisfied. Moreover, the co‐opetition can help enable the coexistence of the PUs and the SUs in cognitive radio systems. Copyright © 2013 John Wiley & Sons, Ltd.

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“…Results show that when the chunk bandwidth is smaller than the coherence bandwidth, the chunk-based resource allocation can significantly reduce the computational complexity while maintaining similar throughput performance compared to subcarrier-based resource allocation algorithms. Utility driven resource allocation was investigated by [11], [12] and most recently by [13], [14] in an information theoretic setting. In these papers, instead of maximizing the sum of the throughputs, the objective of the optimization is the overall utility, which is a function of throughput.…”

Section: Introduction and Related Workmentioning

confidence: 99%

Uplink Resource Management for Multiuser OFDM Video Transmission Systems: Analysis and Algorithm Design

Wang

Toni

Cosman

et al. 2013

IEEE Trans. Commun.

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Abstract-We consider a multiuser OFDM system in which users want to transmit videos via a base station. The base station knows the channel state information (CSI) as well as the rate distortion (RD) information of the video streams and tries to allocate power and spectrum resources to the users according to both physical layer CSI and application layer RD information. We analyze and derive a condition for the optimal resource allocation solution in a continuous frequency response setting. The optimality condition for this cross layer optimization scenario is similar to the equal slope condition for conventional video multiplexing resource allocation [1] [2]. Based on our analysis, we design an iterative subcarrier assignment and power allocation algorithm for an uplink system, and provide numerical performance analysis with different numbers of users. Comparing to systems with only physical layer or only application layer information available at the base station, our results show that the user capacity and the video PSNR performance can be increased significantly by using cross layer design. Bit-level simulations which take into account the imperfection of the video coding rate control, the variation of RD curve fitting, as well as channel errors are presented.

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Multiuser Multimedia Resource Allocation Over Multicarrier Wireless Networks

Cited by 14 publications

References 30 publications

Fuzzy Logic Resource Allocator for Wireless Video Transmission in LTE System

Fuzzy Logic Resource Allocator for Wireless Video Transmission in LTE System

Cooperative bargaining solution for efficient and fair spectrum management in cognitive wireless networks

Uplink Resource Management for Multiuser OFDM Video Transmission Systems: Analysis and Algorithm Design

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