A major challenge in operation of wireless communications systems is the efficient use of radio resources. One important component of radio resource management is power control, which has been studied extensively in the context of voice communications. With increasing demand for wireless data services, it is necessary to establish power control algorithms for information sources other than voice. We present a power control solution for wireless data in the analytical setting of a game theoretic framework. In this context, the quality of service (QoS) a wireless terminal receives is referred to as the utility and distributed power control is a non-cooperative power control game where users maximize their utility. The outcome of the game results in a Nash equilibrium that is ine#cient. We introduce pricing of transmit powers in order to obtain Pareto improvement of the non-cooperative power control game, i.e. to obtain improvements in user utilities relative to the case with no pricing. Specifically, we consider a pricing function that is a linear function of the transmit power. The simplicity of the pricing function allows a distributed implementation where the price can be broadcast by the base station to all the terminals. We see that pricing is especially helpful in a heavily loaded system.

In this paper we consider the downlink power allocation problem for multi-class CDMA wireless networks. We use a utility based power allocation framework to treat multi-class services in a unified way. The goal of this paper is to obtain a power allocation which maximizes the total system utility. In the wireless context, natural utility functions for each mobile are non-concave. Hence, we cannot use existing techniques on convex optimization problems to derive a social optimal solution. We propose a simple distributed algorithm to obtain an approximation to the social optimal power allocation. The proposed distributed algorithm is based on dynamic pricing and allows partial cooperation between mobiles and the base station. The algorithm consists of two stages. At the mobile selection stage, the base station selects mobiles to which power is allocated, considering the partial-cooperative nature of mobiles. This is called partial-cooperative optimal selection, since in a partial-cooperative setting and pricing scheme considered in this paper, this selection is optimal and satisfies system feasibility. At the power allocation stage, the base station allocates power to the selected mobiles. This power allocation is a social optimal power allocation among mobiles in the partial-cooperative optimal selection, thus, we call it a partial-cooperative optimal power allocation. We compare the partial-cooperative optimal power allocation with the social optimal power allocation for the single class case. From these results, we infer that the system utility obtained by the partial-cooperative optimal power allocation is quite close to the system utility obtained by the social optimal allocation.

In recent years, the number and variety of wireless network installations have dramatically increased, from small-scale installations spanning buildings and campuses to much larger-scale installations spanning cities and metropolitan areas. As these wireless networks proliferate, the population of users taking advantage of these networks for communication and access to online services and information also increases. To aid this growing population of users, many research and development efforts focus on upgrading and enhancing the services provided to the users. As part of these efforts, it is crucial to analyze real wireless networks to understand better how users take advantage of them. These analyses are important for at least two reasons. First, they are helpful for creating more realistic models of users when simulating new services, which is a common technique used in the mobile networking community to predict performance. Second, they are also helpful in focusing research on topics that will impact users the most. This thesis analyzes two very different wireless networks: the Metricom Ricochet packet radio network, a high latency, low bandwidth, metropolitan-area wireless network, and the WaveLAN network installed in the Gates Computer Science Building, a low latency, high bandwidth, localarea network. These analyses answer questions about network utilization, traffic characteristics, and user mobility rates and patterns. Among other results, we find that traffic peaks are usually caused by a single user rather than multiple users, and that significantly asymmetric network throughput would be undesirable for the WaveLAN network users. We also determine that users can indeed be categorized based on their mobility in the Metricom analysis and based on their usage ...

Recent research in wireless CDMA systems has shown that adaptive rate/power control can considerably increase network throughput relative to systems that use only power or rate control. In this paper, we consider joint power/rate optimization in the context of orthogonal modulation (OM) and investigate the additional performance gains achieved through adaptation of the OM order. We show that such adaptation can significantly increase network throughput while simultaneously reducing the per-bit energy consumption relative to fixed-order modulation systems. The optimization is carried out under two different objective functions: minimizing the maximum service time and maximizing the sum of user rates. For the first objective function, we prove that the optimization problem can be formulated as a generalized geometric program (GGP). We then show how this GGP can be transformed into a nonlinear convex program, which can be solved optimally and efficiently. For the second objective function, we obtain a lower bound on the performance gain of adaptive OM (AOM) over fixed-modulation systems. Numerical results indicate that relative to an optimal joint rate/power control fixed-order modulation scheme, the proposed AOM scheme achieves significant throughput and energy gains. I.

In this paper, we consider the joint resource allocation and base-station assignment problem for the downlink in CDMA networks with heterogeneous data services. We first study a power and rate control problem that attempts to maximize the expected throughput of the system. This problem is inherently difficult because it is in fact a nonconvex optimization problem. To solve this problem, we propose a distributed algorithm based on dynamic pricing.

In this paper we consider the downlink power allocation problem for multi-class CDMA wireless networks. We use a utility based power allocation framework to treat multi-class services in a unified way. The goal of this paper is to obtain a power allocation which maximizes the total system utility. In the wireless context, natural utility functions for each mobile are non-concave. Hence, we cannot use existing techniques on convex optimization problems to derive a social optimal solution. We propose a simple distributed algorithm to obtain an approximation to the social optimal power allocation. The proposed distributed algorithm is based on dynamic pricing and allows partial cooperation between mobiles and the base station. The algorithm consists of two stages. At the mobile selection stage, the base station selects mobiles to which power is allocated, considering the partial-cooperative nature of mobiles. This is called partial-cooperative optimal selection, since in a partial-cooperative setting and pricing scheme considered in this paper, this selection is optimal and satisfies system feasibility. At the power allocation stage, the base station allocates power to the selected mobiles. This power allocation is a social optimal power allocation among mobiles in the partial-cooperative optimal selection, thus, we call it a partial-cooperative optimal power allocation. We compare the partial-cooperative optimal power allocation with the social optimal power allocation for the single class case. From these results, we infer that the system utility obtained by the partial-cooperative optimal power allocation is quite close to the system utility obtained by the social optimal allocation.

This paper proposes a framework for performance evaluation and optimization of an emerging multimedia, packet Direct-Sequence Code Division Multiple Access (DS-CDMA) network with a wide range of Quality of Service (QoS) requirements on losses and delays. The need for a new framework arises from inability of the traditional approach, based on the outage probability, to capture the queueing aspects of DS-CDMA network behavior in presence of delay tolerant traffic. Accounting for these aspects becomes essential for emerging multimedia DS-CDMA networks attempting to approach their capacity limits by using coding and spreading gain control, retransmissions, as well as transmission scheduling/power control. Since in a DS-CDMA network transmissions compete for simultaneous access to several resources, including wireless bandwidth and transmission power, the paper proposes to approximate the feasible QoS region for the network by the intersection of the feasible QoS regions for the corresponding single-resource systems. The feasible QoS region for a single-resource system is estimated by using M/G/1 conservation laws. Based on this "bottleneck resource" approximation, the paper estimates the admission region for the network and outlines the approach to the network management aimed at maximizing the admission region.

Abstract not found