10 research outputs found
Power control algorithms for CDMA networks based on large system analysis
Power control is a fundamental task accomplished in any wireless cellular
network; its aim is to set the transmit power of any mobile terminal, so that
each user is able to achieve its own target SINR. While conventional power
control algorithms require knowledge of a number of parameters of the signal of
interest and of the multiaccess interference, in this paper it is shown that in
a large CDMA system much of this information can be dispensed with, and
effective distributed power control algorithms may be implemented with very
little information on the user of interest. An uplink CDMA system subject to
flat fading is considered with a focus on the cases in which a linear MMSE
receiver and a non-linear MMSE serial interference cancellation receiver are
adopted; for the latter case new formulas are also given for the system SINR in
the large system asymptote. Experimental results show an excellent agreement
between the performance and the power profile of the proposed distributed
algorithms and that of conventional ones that require much greater prior
knowledge.Comment: To appear in the Proceedings of the 2007 IEEE International Symposium
on Information Theory, Nice, France, June 24 - 29, 200
Adaptive Cross-Layer Distributed Energy-Efficient Resource Allocation Algorithms for Wireless Data Networks
The issue of adaptive and distributed cross-layer resource allocation for energy efficiency in uplink code-division multiple-access (CDMA) wireless data networks is addressed. The resource allocation problems are formulated as noncooperative games wherein each terminal seeks to maximize its own energy efficiency, namely, the number of reliably transmitted information symbols per unit of energy used for transmission. The focus of this paper is on the issue of adaptive and distributed implementation of policies arising from this approach, that is, it is assumed that only readily available measurements, such as the received data, are available at the receiver in order to play the considered games. Both single-cell and multicell networks are considered. Stochastic implementations of noncooperative games for power allocation, spreading code allocation, and choice of the uplink (linear) receiver are thus proposed, and analytical results describing the convergence properties of selected stochastic algorithms are also given. Extensive simulation results show that, in many instances of practical interest, the proposed stochastic algorithms approach with satisfactory accuracy the performance of nonadaptive games, whose implementation requires much more prior information
Fixed-Rate Transmission Over Fading Interference Channels Using Point-to-Point Gaussian Codes
This paper investigates transmission schemes for fixed-rate communications over a Rayleigh block-fading interference channel. There are two source-destination pairs where each source, in the presence of a short-term power constraint, intends to communicate with its dedicated destination at a fixed data rate. It encodes its messages using a point-to-point Gaussian codebook. The two users' transmissions can be conducted orthogonally or non-orthogonally. In the latter case, each destination performs either direct decoding by treating the interference as noise, or successive interference cancellation (SIC) to recover its desired message. For each scheme, we seek solutions of a power control problem to efficiently assign power to the sources such that the codewords can be successfully decoded at destinations. However, because of the random nature of fading, the power control problem for some channel realizations may not have any feasible solution and the transmission will be in outage. Thus, for each transmission scheme, we first compute a lower bound and an upper bound on the outage probability. Next, we use these results to find an outer bound and an inner bound on the \epsilon-outage achievable rate region, i.e., the rate region in which the outage probability is below a certain value \epsilon
Optimal Randomization of Signal Constellations on Downlink of a Multiuser DS-CDMA System
Cataloged from PDF version of article.In this study, the jointly optimal power control with signal constellation randomization is proposed for the downlink of a multiuser communications system. Unlike a conventional system in which a fixed signal constellation is employed for all the bits of a user (for given channel conditions and noise power), power control with signal constellation randomization involves randomization/time- sharing among different signal constellations for each user. A formulation is obtained for the problem of optimal power control with signal constellation randomization, and it is shown that the optimal solution can be represented by a randomization among (K+1) or fewer distinct signal constellations for each user, where K denotes the number of users. In addition to the original nonconvex formulation, an approximate solution based on convex relaxation is derived. Then, detailed performance analysis is presented when the receivers employ symmetric signaling and sign detectors. Specifically, the maximum asymptotical improvement ratio is shown to be equal to the number of users, and the conditions under which the maximum and minimum asymptotical improvement ratios are achieved are derived. Numerical examples are presented to investigate the theoretical results, and to illustrate performance improvements achieved via the proposed approach. © 2002-2012 IEEE
Stochastic Stability Analysis of Power Control in Wireless Networks via a Norm-inequality-based Approach
Owing to the requirements from realistic wireless networks, the stochastic stability analysis for discrete-time power control, which concerns the randomness brought by the fading channels and noise of wireless systems, is of practical significance. By developing a norm-inequality-based framework of analyzing the stochastic stability of linear systems with random parameters, we show that a typical powercontrol law with linear system model is stable in the sense of the pth-moment stability. Several conditions of achieving the pth-moment stability for the considered power-control law are obtained, which can easily applied to realistic wireless networks. Besides, within this study, the stability analysis of power control for the first time takes into account the effect of multiple-access methods
Stochastic Modeling and Estimation of Wireless Channels with Application to Ultra Wide Band Systems
This thesis is concerned with modeling of both space and time variations of Ultra Wide Band (UWB) indoor channels. The most common empirically determined amplitude distribution in many UWB environments is Nakagami distribution. The latter is generalized to stochastic diffusion processes which capture the dynamics of UWB channels. In contrast with the traditional models, the statistics of the proposed models are shown to be time varying, but converge in steady state to their static counterparts.
System identification algorithms are used to extract various channel parameters using received signal measurement data, which are usually available at the receiver. The expectation maximization (EM) algorithm and the Kalman filter (KF) are employed in estimating channel parameters as well as the inphase and quadrature components, respectively. The proposed algorithms are recursive and therefore can be implemented in real time. Further, sufficient conditions for the convergence of the EM algorithm are provided. Comparison with recursive Least-square (LS) algorithms is carried out using experimental measurements.
Distributed stochastic power control algorithms based on the fixed point theorem and stochastic approximations are used to solve for the optimal transmit power problem and numerical results are also presented.
A framework which can capture the statistics of the overall received signal and a methodology to estimate parameters of the counting process based on the received signal is developed. Furthermore, second moment statistics and characteristic functions are computed explicitly and considered as an extension of Rice’s shot noise analysis.
Another two important components, input design and model selection are also considered. Gel’fand n-widths and Time n-widths are used to represent the inherent error introduced by input design. Kolmogorov n-width is used to characterize the representation error introduced by model selection. In particular, it is shown that the optimal model for reducing the representation error is a finite impulse response (FIR) model and the optimal input is an impulse at the start of the observation interval
Stochastic Signal Processing and Power Control for Wireless Communication Systems
This dissertation is concerned with dynamical modeling, estimation and identification of wireless channels from received signal measurements. Optimal power control algorithms, mobile location and velocity estimation methods are developed based on the proposed models.
The ultimate performance limits of any communication system are determined by the channel it operates in. In this dissertation, we propose new stochastic wireless channel models which capture both the space and time variations of wireless systems. The proposed channel models are based on stochastic differential equations (SDEs) driven by Brownian motions. These models are more realistic than the time invariant models encountered in the literature which do not capture and track the time varying characteristics of the propagation environment. The statistics of the proposed models are shown to be time varying, and converge in steady state to their static counterparts. Cellular and ad hoc wireless channel models are developed.
In urban propagation environment, the parameters of the channel models can be determined from approximating the band-limited Doppler power spectral density (DPSD) by rational transfer functions. However, since the DPSD is not available on-line, a filterbased expectation maximization algorithm and Kalman filter to estimate the channel parameters and states, respectively, are proposed. The algorithm is recursive allowing the inphase and quadrature components and parameters to be estimated on-line from received signal measurements. The algorithms are tested using experimental data, and the results demonstrate the method’s viability for both cellular and ad hoc networks.
Power control increases system capacity and quality of communications, and reduces battery power consumption. A stochastic power control algorithm is developed using the so-called predictable power control strategies. An iterative distributed algorithm is then deduced using stochastic approximations. The latter only requires each mobile to know its received signal to interference ratio at the receiver