We present a method, called opportunistic scheduling, for exploiting the time-varying nature of the radio environment to increase the overall performance of the system under certain quality of service/fairness requirements of users. We first introduce a general framework for opportunistic scheduling, and then identify three general categories of scheduling problems under this framework. We provide optimal solutions for each of these scheduling problems. All the proposed scheduling policies are implementable online; we provide parameter estimation algorithms and implementation procedures for them. We also show how previous work by us and others directly fits into or is related to this framework. We demonstrate via simulation that opportunistic scheduling schemes result in significant performance improvement compared with non-opportunistic alternatives.

Emerging spread spectrum high-speed data networks utilize multiple channels via orthogonal codes or frequency-hopping patterns such that multiple users can transmit concurrently. In this paper, we develop a framework for opportunistic scheduling over multiple wireless channels. With a realistic channel model, any subset of users can be selected for data transmission at any time, albeit with different throughputs and system resource requirements. We first transform selection of the best users and rates from a complex general optimization problem into a decoupled and tractable formulation: a multi-user scheduling problem that maximizes total system throughput and a control-update problem that ensures long-term deterministic or probabilistic fairness constraints. We then design and evaluate practical schedulers that approximate these objectives.

We identify optimality properties for scheduling downlink transmissions to data users in CDMA networks. For arbitrary-topology networks, we show that under certain idealizing assumptions it is optimal for a base station to transmit to only one data user at a time. Moreover, for data-only networks, we prove that a base station, when on, should transmit at maximum power for optimality. We use these two properties to obtain a mathematical programming formulation for determining the optimal transmission schedule in linear data-only networks, with time allocations playing the role of decision variables. The optimality conditions imply that there exist (i) subsets of outer users on either side of the cell that should be served when only the neighboring base station on the opposite side is on; (ii) a subset of inner users in the center of the cell that should be served when both neighbors are on; (iii) a subset of users in the intermediate regions that should receive transmissions when both n...

In this paper, we present Wireless Credit-based Fair Queueing (WCFQ), a new scheduler for wireless packet networks with provable statistical short- and long-term fairness guarantees. WCFQ exploits the fact that users contending for the wireless medium will have different "costs" of transmission depending on their current channel condition. For example, in systems with variable coding, a user with a high-quality channel can exploit its low-cost channel and transmit at a higher data rate. Similarly, a user in a CDMA system with a high quality channel can use a lower transmission power. Thus, WCFQ provides a mechanism to exploit inherent variations in channel conditions and select low cost users in order to increase the system's overall performance (e.g., total throughput). However, opportunistic selection of the best user must be balanced with fairness considerations. In WCFQ, we use a credit abstraction and a general "cost function" to address these conflicting objectives. This provides system operators with the flexibility to achieve a range of performance behaviors between perfect fairness of temporal access independent of channel conditions, and purely opportunistic scheduling of the best user without consideration of fairness. To quantify the system 's fairness characteristics within this range, we develop an analytical model that provides a statistical fairness bound in terms of the cost function and the statistical properties of the channel. An extensive set of simulations indicate that the scheme is able to achieve significant throughput gains while balancing temporal fairness constraints.

In this paper, we present a framework for "opportunistic scheduling" that exploits the variation of the wireless channel conditions to improve spectrum efficiency. The objective of the scheduling schemes in this paper is to maximize the system performance in an opportunistic fashion, while satisfying various QoS requirements. We study three types of QoS requirements: the first is fairness in resource sharing, the second is a performance-based fairness requirement, and the third is that each user has a minimumperformance requirement. We provide optimal solutions, and discuss the advantages and disadvantages of the different scheduling schemes. We also demonstrate via simulation that the schemes result in significant performance improvement compared with scheduling schemes that are not opportunistic.