After about a decade of intense research, spurred by both economic and operational considerations, and by environmental concerns, energy efficiency has now become a key pillar in the design of communication networks. With the advent of the fifth generation of wireless networks, with millions more base stations and billions of connected devices, the need for energy-efficient system design and operation will be even more compelling. This survey provides an overview of energy-efficient wireless communications, reviews seminal and recent contribution to the state-of-the-art, including the papers published in this special issue, and discusses the most relevant research challenges to be addressed in the future.

As it becomes common for wireless service providers (WSP) to employ multiple heterogeneous radio access technologies (RAT), the management of the combined resources across multiple RATs arises as an important issue. The WSP's objective is to assign different users to the different RATs so as to maximize network capacity (or total utility) while ensuring that individual users' quality of service (QoS) requirements are met. In this paper, we consider this resource allocation problem for two scenarios: voice communication and video communication. For voice communication, we propose a stable and optimal assignment scheme based on the deferred acceptance algorithm for both static and online cases. For video communication, identifying the NP-hardness of the problem, we propose and compare a set of heuristic algorithms including a low-complexity, high-performance scheme.

This paper investigates joint power control and routing policies for general multihop wireless networks when all the transmitting nodes are subject to a long-term average power constraint. The main contribution of this paper is to propose online power and rate control algorithms and prove that these policies stabilize the entire queuing network whenever the packet arrival rates at each node are in the corresponding region of achievable rates. The online policies are time varying and based on the queue size at each node and the instantaneous channel conditions. The theoretical results are supported by simulations for the illustrative cases of both a multiple-access channel and a relay channel

This paper considers the problem of assigning mobile data users to base stations and modulating their transmit powers according to their respective channel gains in order to maximize the total system throughput. We consider two scenarios of time-invariant and time-varying channel behaviors. We show that the base station assignment problem is NP complete and propose sub-optimal polynomial time algorithms and bound their performance. When the channel gains are time-varying, we present an iterative algorithm to compute the assignment and power control functions according to the probability distribution of the channel gains. This algorithm is shown to converge to the optimal allocation in the special cases of a single user or a single base station. Simulation results demonstrate the performance of our algorithms, which are especially significant under asymmetric loading of the network

Abstract Coexistence of different access technologies, hierarchical cellular deployment, a wide variety of data services, requirements for transparent operation across different technologies, adaptivity to varying network conditions and mobility and quality of service (QoS) constraints introduce a number of challenges in the design of future generation systems and the specification of new air interfaces, such as efficiency and flexibility in the utilization of spectrum, dynamic resource allocation and exploitation of the multiuser diversity and reconfigurable interference management and inter‐cell coordination. In this paper, three critical issues for the design of next generation systems are addressed: (i) duplexing, (ii) scheduling and resource allocation and (iii) interference and inter‐cell coordination. A number of research directions are presented, which constitute promising potential candidates for next generation systems specification. Copyright © 2005 John Wiley & Sons, Ltd.

The Transmission Control Protocol (TCP) has been designed to provide reliable transport of packets by adjusting the transmission rate to the network congestion level. While TCP can adapt to small fluctuations in the delay between the sender and the receiver, adverse affects (most importantly, spurious timeouts) have been observed under large delay variability. We exhibit the presence of such delay spikes in wireless networks and discuss their possible origins. We then investigate a new methodology for avoiding spurious TCP timeouts by appropriately injecting additional random delay along the communication path. Different algorithms for the delay injection are presented and we assess their relative performances and merits through simulations. In particular, we show, by numerical examples, that the delay injection methodology can significantly decrease the number of timeouts and increase the achieved TCP throughput by about 8% in the network scenario considered. One of the attractive features of the new methodology is that it does not require any changes to the TCP and can be applied independently of the TCP version used.

Current and next-generation wireless networks rely on multiuser diversity and scheduling techniques, such as the commonly used proportional fair (PF) algorithm, to achieve greater system throughput and higher efficiencies for wireless data applications over a time-varying wireless channel. We show that the variability of the inter-scheduling intervals, as introduced by the PF scheduling algorithm, can have adverse effects on TCP and its congestion control mechanism and lead to spurious timeouts and unnecessarily low throughput. We propose an enhanced scheduling algorithm that is explicitly tuned towards throughput performance at the TCP layer. However, this algorithm does not use any explicit information from the TCP layer and solely relies on information readily available at the link layer at which the scheduler resides. The performance of this improved algorithm is assessed through extensive simulations to show an average TCP throughput improvement of 12% compared to PF. In addition, the TCP-level fairness across all users is increased, as is the individual user throughput.

Hierarchical wireless overlay networks have been proposed as an attractive alternative and extension of cellular network architectures to provide the necessary cell capacities to effectively support next-generation wireless data applications. In addition, they allow for flexible mobility management strategies and quality-of-service differentiation. One of the crucial problems in hierarchical overlay networks is the assignment of wireless data users to the different layers of the overlay architecture. In this paper, we present a framework and several analytical results pertaining to the performance of two assignment strategies based on the user's velocity and the amount of data to be transmitted. The main contribution is to prove that the minimum average number of users in the system, as well as the minimum expected system load for an incoming user, are the same under both assignment strategies. We provide explicit analytical expressions as well as unique characterizations of the optimal thresholds on the velocity and amount of data to be transmitted. These results are very general and hold for any distribution of user profiles and any call arrival rates. We also show that intelligent assignment strategies yield significant gains over strategies that are oblivious to the user profiles. Adaptive and on-line strategies are derived that do not require any a priori knowledge of the user population and the network parameters. Extensive simulations are conducted to support the theoretical results presented and conclude that the on-line strategies achieve near-optimal performance when compared with off-line strategies.

One of the crucial problems in hierarchical overlay networks is the assignment of users to the different layers of the overlay architecture. In an earlier paper [T.E. Klien and S.J. Han, March 12-14, 2003], we have investigated the system-wide performance of assignment strategies based on the users' profile information of velocity and amount of data to be transmitted. The optimal assignment strategies that minimize the average number of users in the system rely on knowledge of the cell capacities, the call arrival rates and the statistical description of the users' profiles. In realistic operating conditions, this knowledge may not be available and would typically be time-varying. In this paper, we propose adaptive and online assignment strategies that do not require any a priori knowledge, but still achieve the same performance as if such knowledge were available.