Differentiated QoS provision in wireless environments via multicarrier energy allocation is examined in this work. Within this framework, differentiated QoS is applied to transmitted data classes, such as text, audio and video, simultaneously. QoS targets, or constraints, are defined by specifying distortion targets for each class, and energy is allocated to carriers of different classes to meet those targets/constraints accordingly. QoS differentiation is achieved by a concept called QoS scaling. We develop a methodology to find the set of scalars that allows each service constraint to be met. While earlier work can be viewed to offer solutions to the scalar-to-distortion mapping problem, this research solves the more challenging inverse mapping problem; namely, from distortion requirements to selection of scalars. We present two algorithms for differentiated QoS that depend upon the amount of constrained classes relative to the total amount of classes. Finally, to provide a clearer understanding of the effect of QoS scaling, we analyze the effect on distortion by varying the total number of scalars.

Effective energy allocation in a multicarrier communication system for differentiated quality of services (QoS) provision and transmit power dynamic range reduction is investigated in this work. Two different methods are analyzed and compared. The first one is to partition data classes and use their importance weights to develop a multiclass allocation scheme. The second one is to perform a single class allocation scheme at each time slot. A closed-form energy allocation algorithm is developed for fast implementation. The advantage of using multiclass allocation in dynamic range reduction is quantified. This reduction leads to smaller RF output power as well as DC power required by the system. Both theoretical and simulation results are presented in to demonstrate performance

Efficient near-optimal energy allocation for multimedia data transmission using multicarrier modulation is investigated. The optimal method typically relies on an iterative process that is computationally intensive, and it does not provide insight into the allocation process for higher order M-quadrature amplitude modulation (QAM) constellations. A sequence of two fast energy allocation algorithms are proposed in this work. First, a basic energy allocation algorithm is developed by solving a simple set of linear equations directly. It is shown to be near-optimal for almost the entire signal-to-noise ratio range. Based on this direct method, we can analyze asymptotic limits of the approximation error, carrier energy, and carrier rate conveniently. Then, we present an advanced algorithm that enhances the performance of the basic algorithm via iteration. The convergence of the advanced algorithm is studied, and an estimate of its computational complexity is derived. It is worthwhile to point out that, while limits for the special case with uniform noise and binary phase-shift keying modulation were studied previously, the derived asymptotic performance here works for a more general case with nonuniform noise and M-QAM constellations. Finally, we examine these limits with several types of multimedia and nonmultimedia sources, and show that our algorithms perform well regardless of the source type.

An efficient near-optimal energy allocation method for multimedia data transmitted using multicarrier modulation is investigated in this research. Our algorithm allocates energy to carriers by solving a simple set of linear equations, which is near-optimal for almost the entire SNR range. Furthermore, based on the proposed energy allocation algorithm, we develop asymptotic limits for the approximation error, the carrier energy, and the carrier rate. While limits for the special case with uniform noise and BPSK modulation were obtained before, our derivation applies to the more general case with nonuniform noise and higher-order M-QAM constellations. Finally, we link these limits with several types of multimedia and non-multimedia sources.