VCG Auction based Optimal Allocation for Scalable Video Communication

Abstract-In this paper, we propose a novel application of the Vickrey-Clarke-Groves (VCG) auction based time-frequency resource allocation for H.264 SVC based scalable video transmission in 4G wireless systems. The net transmitted video quality corresponding to the given bitrate constrained wireless system can be maximized by optimally allocating the OFDMA time-frequency resources amongst the video streams requested by the different unicast/ multicast groups. However, such a centralized allocation is susceptible to subversion resulting from misrepresentation of the characteristic video parameters by malicious users. This, in addition to resulting in a degradation of the net video quality, might also benefit the users reporting incorrect parameter values through disproportionate resource allocation. Our simulation results demonstrate that application of the proposed VCG procedure maximizes the net utility in broadcast/ multicast video streaming when true characteristic parameters are reported, while punishing malicious users when one or more parameters are misreported

Optimal 4G OFDMA Dynamic Subcarrier and Power Auction-based Allocation towards H.264 Scalable Video Transmission

In this paper, authors presented a price maximization scheme for optimal orthogonal frequency division for multiple access (OFDMA) subcarrier allocation for wireless video unicast/multicast scenarios. They formulate a pricing based video utility function for H.264 based wireless scalable video streaming, thereby achieving a trade-off between price and QoS fairness. These parametric models for scalable video rate and quality characterization arederived from the standard JSVM reference codec for the SVC extension of the H.264/AVC, and hence are directly applicable in practical wireless scenarios. With the aid of these models, they proposed auction based framework for revenue maximization of the transmitted video streams in the unicast and multicast 4G scenario. A closedform expression is derived for the optimal scalable video quantization step-size subject to the constraints of theunicast/multicast users in 4G wireless systems. This yields the optimal OFDMA subcarrier allocation for multi-userscalable video multiplexing. The proposed scheme is cognizant of the user modulation and code rate, and is henceamenable to adaptive modulation and coding (AMC) feature of 4G wireless networks. Further, they also consider aframework for optimal power allocation based on a novel revenue maximization scheme in OFDMA based wireless broadband 4G systems employing auction bidding models. This is formulated as a constrained convex optimization problem towards sum video utility maximization. We observe that as the demand for a video stream increases inbroadcast/multicast scenarios, higher power is allocated to the corresponding video stream leading to a gain in the overall revenue/utility. We simulate a standard WiMAX based 4G video transmission scenario to validate the performance of the proposed optimal 4G scalable video resource allocation schemes. Simulations illustrate that the proposed optimal band width and power allocation schemes result in a significant performance improvement over the suboptimal equal resource allocation schemes for scalable video transmission.Defence Science Journal, 2013, 63(1), pp.15-24, DOI:http://dx.doi.org/10.14429/dsj.63.375

Optimal H.264 Scalable Video Scheduling Policies for 3G/4G Wireless Cellular and Video Sensor Networks

We consider the problem of optimal H.264 scalable video scheduling, with an objective of maximizing the end-user video quality while ensuring fairness in 3G/4G broadband wireless networks and video sensor networks. We propose a novel framework to characterize the video quality-based utility of the H.264 temporal and quality scalable video layers. Subsequently, we formulate the scalable video scheduling framework as a Markov decision process (MDP) for long-term average video utility maximization and derive the optimal index based-scalable video scheduling policies ISVP and ISVPF towards video quality maximization. Further, we extend this framework to multiuser and multisubchannel scenario of 4G wireless networks. In this context, we propose two novel schemes for long-term streaming video quality performance optimization based on maximum weight bipartite and greedy matching paradigms. Simulation results demonstrate that the proposed algorithms achieve superior end-user video experience compared to competing scheduling policies such as Proportional Fairness (PF), Linear Index Policy (LIP), Rate Starvation Age policy (RSA), and Quality Proportional Fair Policy (QPF)

Cramer-Rao Lower Bound for Constrained Complex Parameters

Abstract-An expression for the Cramer-Rao lower bound (CRB) on the covariance of unbiased estimators of a constrained complex parameter vector is derived. The application and usefulness of the result is demonstrated through its use in the context of a semiblind channel estimation problem