Resource allocation for layered broadcast over relay-assisted channels

The topic of this thesis is on the application of “multilayer transmission” using the broadcast approach on a “relay-assisted” channel. Unlike single layer transmission, where all transmitted information bits have the same protection level by the channel coding scheme, multilayer transmission schemes combine successive refinement layered source coding with ordered protection levels of the source layers. Consequently, the receiver will be able to decode “some” information when the channel is faded and “all” information when the channel is good. The multilayer transmission schemes have gained a lot of interest in the information theory and the communication theory literature, where most researchers are interested in the “broadcast approach” since it is the optimal transmission strategy. In this thesis, we consider a fading relay channel where the source uses layered source coding with successive refinement. The source layers are transmitted using superposition coding at the source with optimal resource allocation. The destination applies successive interference cancellation after optimally combining the direct and relayed signals. The resource allocation for the layers is subject to optimization in order to maximize the expected user satisfaction that is usually defined by a differentiable concave increasing utility function of the total decoded rate at the destination. As special cases, we consider two utility functions; namely, the expected total decoded rate at the receiver and the expected rate distortion of a Gaussian source. We also assume that only the channel statistics are known at the receiver. The relay is half-duplex and applies different relaying strategies, and we have investigated the Amplify-and-Forward, and Decode-and-Forward strategies in particular. First, we consider the case of Decode-and-Forward relays where we consider two layers only with predetermined rates for simplicity, and we solve the problem of optimal power allocation among the two layers at the source and the relay using random search methods. After that, we solve the optimal power allocation problem for any number of layers with fixed rates over an Amplify-and-Forward relays. An approximation for the end-to-end channel quality is presented in terms of the statistics of the three links of the channel model. Furthermore, we obtain that for some conditions, it is optimal to send only one layer. Finally, we solve the joint optimal power and rate allocation problem for any number of layers over an Amplify-and-Forward relays. We also consider the theoretical case of infinite number of layers representing an upper bound for the performance. Moreover, we show that with a small number of layers, we can approach the performance upper bound. We provide many numerical examples for the three cases above to show the prospected gains of using the relays on the expected utility for different channel conditions

Two-Layered Superposition of Broadcast/Multicast and Unicast Signals in Multiuser OFDMA Systems

We study optimal delivery strategies of one common and $K$ independent messages from a source to multiple users in wireless environments. In particular, two-layered superposition of broadcast/multicast and unicast signals is considered in a downlink multiuser OFDMA system. In the literature and industry, the two-layer superposition is often considered as a pragmatic approach to make a compromise between the simple but suboptimal orthogonal multiplexing (OM) and the optimal but complex fully-layered non-orthogonal multiplexing. In this work, we show that only two-layers are necessary to achieve the maximum sum-rate when the common message has higher priority than the $K$ individual unicast messages, and OM cannot be sum-rate optimal in general. We develop an algorithm that finds the optimal power allocation over the two-layers and across the OFDMA radio resources in static channels and a class of fading channels. Two main use-cases are considered: i) Multicast and unicast multiplexing when $K$ users with uplink capabilities request both common and independent messages, and ii) broadcast and unicast multiplexing when the common message targets receive-only devices and $K$ users with uplink capabilities additionally request independent messages. Finally, we develop a transceiver design for broadcast/multicast and unicast superposition transmission based on LTE-A-Pro physical layer and show with numerical evaluations in mobile environments with multipath propagation that the capacity improvements can be translated into significant practical performance gains compared to the orthogonal schemes in the 3GPP specifications. We also analyze the impact of real channel estimation and show that significant gains in terms of spectral efficiency or coverage area are still available even with estimation errors and imperfect interference cancellation for the two-layered superposition system

Distortion Minimization in Gaussian Layered Broadcast Coding with Successive Refinement

A transmitter without channel state information (CSI) wishes to send a delay-limited Gaussian source over a slowly fading channel. The source is coded in superimposed layers, with each layer successively refining the description in the previous one. The receiver decodes the layers that are supported by the channel realization and reconstructs the source up to a distortion. The expected distortion is minimized by optimally allocating the transmit power among the source layers. For two source layers, the allocation is optimal when power is first assigned to the higher layer up to a power ceiling that depends only on the channel fading distribution; all remaining power, if any, is allocated to the lower layer. For convex distortion cost functions with convex constraints, the minimization is formulated as a convex optimization problem. In the limit of a continuum of infinite layers, the minimum expected distortion is given by the solution to a set of linear differential equations in terms of the density of the fading distribution. As the bandwidth ratio b (channel uses per source symbol) tends to zero, the power distribution that minimizes expected distortion converges to the one that maximizes expected capacity. While expected distortion can be improved by acquiring CSI at the transmitter (CSIT) or by increasing diversity from the realization of independent fading paths, at high SNR the performance benefit from diversity exceeds that from CSIT, especially when b is large.Comment: Accepted for publication in IEEE Transactions on Information Theor

Achievable Rate and Optimal Physical Layer Rate Allocation in Interference-Free Wireless Networks

We analyze the achievable rate in interference-free wireless networks with physical layer fading channels and orthogonal multiple access. As a starting point, the point-to-point channel is considered. We find the optimal physical and network layer rate trade-off which maximizes the achievable overall rate for both a fixed rate transmission scheme and an improved scheme based on multiple virtual users and superposition coding. These initial results are extended to the network setting, where, based on a cut-set formulation, the achievable rate at each node and its upper bound are derived. We propose a distributed optimization algorithm which allows to jointly determine the maximum achievable rate, the optimal physical layer rates on each network link, and an opportunistic back-pressure-type routing strategy on the network layer. This inherently justifies the layered architecture in existing wireless networks. Finally, we show that the proposed layered optimization approach can achieve almost all of the ergodic network capacity in high SNR.Comment: 5 pages, to appear in Proc. IEEE ISIT, July 200

Ultra-Reliable Cloud Mobile Computing with Service Composition and Superposition Coding

An emerging requirement for 5G systems is the ability to provide wireless ultra-reliable communication (URC) services with close-to-full availability for cloud-based applications. Among such applications, a prominent role is expected to be played by mobile cloud computing (MCC), that is, by the offloading of computationally intensive tasks from mobile devices to the cloud. MCC allows battery-limited devices to run sophisticated applications, such as for gaming or for the "tactile" internet. This paper proposes to apply the framework of reliable service composition to the problem of optimal task offloading in MCC over fading channels, with the aim of providing layered, or composable, services at differentiated reliability levels. Inter-layer optimization problems, encompassing offloading decisions and communication resources, are formulated and addressed by means of successive convex approximation methods. The numerical results demonstrate the energy savings that can be obtained by a joint allocation of computing and communication resources, as well as the advantages of layered coding at the physical layer and the impact of channel conditions on the offloading decisions.Comment: 8 pages, 5 figures, To be presented at CISS 201

Distortion Exponent in MIMO Channels with Feedback

The transmission of a Gaussian source over a block-fading multiple antenna channel in the presence of a feedback link is considered. The feedback link is assumed to be an error and delay free link of capacity 1 bit per channel use. Under the short-term power constraint, the optimal exponential behavior of the end-to-end average distortion is characterized for all source-channel bandwidth ratios. It is shown that the optimal transmission strategy is successive refinement source coding followed by progressive transmission over the channel, in which the channel block is allocated dynamically among the layers based on the channel state using the feedback link as an instantaneous automatic repeat request (ARQ) signal.Comment: Presented at the IEEE Information Theory Workshop (ITW), Taormina, Italy, Oct. 200

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