This paper proposes a framework for evaluating mobile-to-mobile inter-system interference which occurs between two time division duplex (TDD) WiMAX systems deployed in adjacent frequency blocks and the same geographical area. The need for a new framework arises from inability of the traditional approaches to capture several important factors, such as power control and non-uniform user distribution because of high user density areas (hotspots). Accounting for these aspects becomes essential for accurately quantifying the effect of mobile-to-mobile interference for the purpose of spectrum engineering and system deployment. Based on the proposed framework, the quantitative per user performance degradation was obtained and we are also able to analyze the impact of guard band, frequency coordination between systems and partial synchronization on mobile-to-mobile interference.

We consider the allocation of power across forward-link packets in a wireless data network. The packets arrive according to a random (Poisson) process, and have fixed length so that the data rate for a given packet is determined by the assigned power and the channel gain to the designated user. Each user's service preferences are specified by a utility function that depends on the received data rate. The objective is to determine a power assignment policy that maximizes the time-averaged utility rate, subject to a constraint on the probability that the total power exceeds a limit (corresponding to an outage). For a large, heavily loaded network, we introduce a Gaussian approximation for the total transmitted power, which is used to decompose the power constraint into three more tractable constraints. We present a solution to the modified optimization problem that is a combination of admission control and pricing. The optimal trade-off between these approaches is characterized. Numerical examples illustrate the achievable utility rate and power allocation as a function of the packet arrival rate.

In this paper, we consider packet scheduling for the downlink in a wireless network, where each packet's service preferences are captured by a utility function that depends on the total delay incurred. The goal is to schedule packet transmissions to maximize the total utility. In this setting, we examine a simple gradient-based scheduling algorithm called the U/spl dot/R-rule, which is a type of generalized c/spl mu/-rule (Gc/spl mu/) that takes into account both a user's channel condition and derived utility when making scheduling decisions. We study the performance of this scheduling rule for a draining problem, where there is a given set of initial packets and no further arrivals. We formulate a "large system" fluid model for this draining problem where the number of packets becomes large while the packet-size decreases to zero, and give a complete characterization of the behavior of the U/spl dot/R scheduling rule in this limiting regime. Comparison with simulation results show that the fluid limit accurately predicts the corresponding behavior of finite systems of interest. We then give an optimal control formulation for finding the optimal scheduling policy for the fluid draining model. Using Pontryagin's minimum principle, we show that, when the user rates are chosen from a TDM-type of capacity region, the U/spl dot/R rule is in fact optimal in many cases. Sufficient conditions for optimality are also given. Finally, we consider a general capacity region and show that the U/spl dot/R rule is optimal only in special cases.

We consider forward link power allocation for voice users in a code-division multiple-access wireless network. Admission control policies are investigated, which base a new call admission decision not only upon available capacity, but also upon the required forward link transmit power and upon the user's willingness to pay. We assume that each voice user has a utility function that describes the user's willingness to pay as a function of forward link signal-to-interference plus noise ratio. The network objective is to maximize either total utility summed over all users or total revenue generated from all users. Properties of the optimal power and code allocations are presented. Our key results show how these optimal allocations can be achieved using pricing. The analysis is complemented with a numerical study, which shows how the optimal prices and corresponding utility or revenue vary with load.

The radio link control (RLC) protocol uses multiple-reject ARQ for reliable data transfer in UMTS systems. In this paper, we analyzed RLC performance with respect to ARQ window sizes and polling periods. Due to the complexity of the RLC protocol and the great number of UMTS radio configurations, a simulation analysis was conducted. Our results show that RLC performance shall benefit from a large window size and a relatively small polling period. We also investigated the polling and unsolicited status report mechanisms of RLC and provided some guidance on configuring them.

We consider "opportunistic" downlink scheduling of data traffic in a wireless network. In particular, we focus on the delay performance of such schedulers. First a channel-dependent scheduling algorithm is considered that maximizes throughput by always transmitting to the user with the best channel conditions. The delay distribution of this scheduling rule is analyzed and asymptotic results are given when the number of competing users becomes large. Simulations show these asymptotic results are a good approximation for even a small number of users. This scheduling rule may result in unfair treatment of users that have relative bad channels for a long period of time; to remedy this we propose a simple utility-based scheduling algorithm. The motivation is to maximize the time-averaged utility, where utility is a decreasing function of the delay incurred when serving a request. The scheduling algorithm takes into account both the utility function and the channel state. We give simulation results that characterize the performance of the scheduling algorithm. The effect of the temporal correlation of the channel of the performance is also studied.

We consider forward-link power allocation in a wireless network with stochastically varying data requests. We assume a user's service preferences are specified via a utility function that depends on the received data rate. The allocation of power across users is studied, where this allocation may depend on both a user's channel and utility. The objective is to maximize the time-averaged utility rate subject to a stochastic total power constraint at the transmitter. For a large, heavily loaded network, we introduce a Gaussian approximation for the total transmitted power, which is used to decompose the power constraint into three more tractable constraints. We present a solution to this problem that is a combination of admission control and pricing of power. The optimal trade-off between these approaches is characterized. Numerical examples are given to illustrate these ideas.

This paper studies pricing as a means for resource allocation in a wireless direct-sequence (DS) code division multiple access (CDMA) system. We consider the forward link of a single cell with orthogonal codes and voice traffic. The base station announces a price per unit transmitted power and a price per code, and the users respond according to their individual utilities. The objective is to set prices to maximize either total user utility or total revenue. The solution to the former problem (maximize utility) is presented. To study the latter problem we derive the large system revenue as the number of users and codes tend to infinity with fixed ratio. The large system revenue depends on the distribution of utilities and path loss across the user population, and may not be a unimodal function of the prices. Numerical results based on a simple model for user utility show how the optimal prices and revenue vary with the offered load.