1,223 research outputs found
Power Efficient MISO Beamforming for Secure Layered Transmission
This paper studies secure layered video transmission in a multiuser
multiple-input single-output (MISO) beamforming downlink communication system.
The power allocation algorithm design is formulated as a non-convex
optimization problem for minimizing the total transmit power while guaranteeing
a minimum received signal-to-interference-plus-noise ratio (SINR) at the
desired receiver. In particular, the proposed problem formulation takes into
account the self-protecting architecture of layered transmission and artificial
noise generation to prevent potential information eavesdropping. A
semi-definite programming (SDP) relaxation based power allocation algorithm is
proposed to obtain an upper bound solution. A sufficient condition for the
global optimal solution is examined to reveal the tightness of the upper bound
solution. Subsequently, two suboptimal power allocation schemes with low
computational complexity are proposed for enabling secure layered video
transmission. Simulation results demonstrate significant transmit power savings
achieved by the proposed algorithms and layered transmission compared to the
baseline schemes.Comment: Accepted for presentation at the IEEE Wireless Communications and
Networking Conference (WCNC), Istanbul, Turkey, 201
Optimization of Occlusion-Inducing Depth Pixels in 3-D Video Coding
The optimization of occlusion-inducing depth pixels in depth map coding has
received little attention in the literature, since their associated texture
pixels are occluded in the synthesized view and their effect on the synthesized
view is considered negligible. However, the occlusion-inducing depth pixels
still need to consume the bits to be transmitted, and will induce geometry
distortion that inherently exists in the synthesized view. In this paper, we
propose an efficient depth map coding scheme specifically for the
occlusion-inducing depth pixels by using allowable depth distortions. Firstly,
we formulate a problem of minimizing the overall geometry distortion in the
occlusion subject to the bit rate constraint, for which the depth distortion is
properly adjusted within the set of allowable depth distortions that introduce
the same disparity error as the initial depth distortion. Then, we propose a
dynamic programming solution to find the optimal depth distortion vector for
the occlusion. The proposed algorithm can improve the coding efficiency without
alteration of the occlusion order. Simulation results confirm the performance
improvement compared to other existing algorithms
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Joint rate control and scheduling for providing bounded delay with high efficiency in multihop wireless networks
This thesis considers the problem of supporting traffic with elastic bandwidth requirements and hard end-to-end delay constraints in multi-hop wireless networks, with focus on source transmission rates and link data rates as the key resource allocation decisions. Specifically, the research objective is to develop a source rate control and scheduling strategy that guarantees bounded average end-to-end queueing delay and maximises the overall utility of all incoming traffic, using network utility maximisation framework. The network utility maximisation based approaches to support delay-sensitive traffic have been predominantly based on either reducing link utilisation, or approximation of links as M/D/1 queues. Both approaches lead to unpredictable transient behaviour of packet delays, and inefficient link utilisation under optimal resource allocation. On the contrary, in this thesis an approach is proposed where instead of hard delay constraints based on inaccurate M/D/1 delay estimates, traffic end-to-end delay requirements are guaranteed by proper forms of concave and increasing utility functions of their transmission rates. Specifically, an alternative formulation is presented where the delay constraint is omitted and sources’ utility functions are multiplied by a weight factor. The alternative optimisation problem is solved by a distributed scheduling algorithm incorporating a duality-based rate control algorithm at its inner layer, where optimal link prices correlate with their average queueing delays. The proposed approach is then realised by a scheduling algorithm that runs jointly with an integral controller whereby each source regulates the queueing delay on its paths at the desired level, using its utility weight coefficient as the control variable. Since the proposed algorithms are based on solving the alternative concave optimisation problem, they are simple, distributed and lead to maximal link utilisation. Hence, they avoid the limitations of the previous approaches. The proposed algorithms are shown, using both theoretical analysis and simulation, to achieve asymptotic regulation of end-to-end delay given the step size of the proposed integral controller is within a specified range
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