Narrowband Internet of Things (NB-IoT) is the latest IoT connectivity solution presented by the 3rd generation partnership project (3GPP). NB-IoT introduces coverage classes and offers a significant link budget improvement by allowing repeated transmissions by nodes that experience high path loss. However, those repetitions necessarily increase the energy consumption and the latency in the whole NB-IoT system. The extent to which the whole system is affected depends on the scheduling of the uplink and downlink channels. We address this question, not treated previously, by developing a tractable model of NB-IoT access protocol operation, comprising message exchanges in random-access, control, and data channels, both in the uplink and downlink. The model is then used to analyze the impact of channel scheduling as well as the interaction of coexisting coverage classes, through derivation of the expected latency and battery lifetime for each coverage class. These results are subsequently employed in investigation of latency-energy tradeoff in NB-IoT channel scheduling as well as determining the optimized operation points. Simulations results show validity of the analysis and confirm that channel scheduling and coexistence of coverage classes significantly affect latency and battery lifetime performance of NB-IoT devices.

Mobile Edge Computing (a.k.a Fog computing) is recently proposed to provide computing service for delay-sensitive mobile applications. Despite various benefits, deploying edge servers in cellular networks would increase their energy consumption. In this paper, we investigate the provision of resources, including both communication and computation resources, of Mobile Edge Computing (MEC) systems to improve their energy efficiency (EE). In a MEC system, both the communication subsystem, which allows mobile users to access Internet and offload their computing tasks, and the computation subsystem, which accomplishes the offloaded computing tasks, affect the service latency and consume energy. Modelling the whole system as tandem queues, we study the trade-offs between these two subsystems on energy consumption and service latency. Based on the analysis results, we propose an algorithm to determine the optimal provision of both communication and computation resources to minimize the overall energy consumption without sacrificing the performance on service latency. Numerical results are provided to validate our analytical findings.

As a main enabler for the next generation (5G) cellular networks, network densification faces challenges in inter-cell interference and energy consumption. Cell discontinuous transmission (DTX) can be employed to reduce both energy consumption of base stations (BSs) and inter-cell interference. In this paper we study the control problem of cell DTX in dense small cell networks (DSCNs). We firstly formulate the network energy efficiency optimization problem. Then a centralized heuristic DTX control algorithm is presented. In order to address the issues of complexity and scalability of the centralized solution, an interference-aware distributed DTX control algorithm is proposed. Discussions on algorithm complexity and implementation are provided. The proposed algorithms are evaluated with numerical simulations. Results show that at high load region, the proposed algorithms can not only enhance network capacity by reducing inter-cell interference by up to 60% but also increase network energy efficiency by switching BSs into micro-sleep mode by 67%.

We discuss the globally optimal energy-efficient design of a 2D relay network. Different from the existing routing protocols on energy saving, which finds the minimal energy route for a given data rate, the proposed algorithm jointly optimizes routing and data rate to maximize energy efficiency (EE) defined as the achievable data rate per power consumption. We propose a low-complexity algorithm to circumvent the huge complexity of the exhaustive search for the network EE maximization and prove its global optimality. Moreover, the proposed algorithm is implemented in a distributed fashion because each relay needs to send its routing information only to the relays in its adjacent tiers, which significantly reduces the signaling overhead of the centralized implementation. Our analysis on the worst-case complexity in a fading channel shows that the complexity of the proposed algorithm increases linearly while that of the exhaustive search increases exponentially as the tier index increases. Simulation results confirm that the proposed algorithm outperforms the existing routing protocols on energy saving and achieves the globally optimal network EE at a significantly lower complexity than the exhaustive search.

Radio access management plays a vital role in delay and energy consumption of connected devices. The radio access in existing cellular networks is unable to efficiently support massive connectivity, due to its signaling overhead. In this paper, we investigate an asynchronous grant-free narrowband data transmission protocol that aims to provide low energy consumption and delay, by relaxing the synchronization/reservation requirement at the cost of sending several packet copies at the transmitter side and more complex signal processing at the receiver side. Specifically, the timing and frequency offsets, as well as sending of multiple replicas of the same packet, are exploited as form of diversities at the receiver-side to trigger successive interference cancellation. The proposed scheme is investigated by deriving closed-form expressions for key performance indicators, including reliability and battery-lifetime. The performance evaluation indicates that the scheme can be tuned to realize long battery lifetime radio access for low-complexity devices. The obtained results indicate existence of traffic load regions, where synchronous access outperforms asynchronous access and vice versa.

Performance tradeoffs in resource provisioning for mixed internet-of-things (IoT) and human-oriented-communications (HoC) services over cellular networks are investigated. First, we present a low-complexity model of cellular connectivity in the uplink direction in which both access reservation and scheduled data transmission procedures are included. This model is employed subsequently in deriving analytical expressions for energy efficiency, spectral efficiency, and experienced delay in data transmission of connected devices as well as energy consumption of base stations. The derived expressions indicate that the choice of uplink resource provisioning strategy introduces tradeoffs between battery lifetime for IoT communications, quality of service (QoS) for HoC, spectral efficiency and energy consumption for the access network. Then, the impacts of system and traffic parameters on the introduced tradeoffs are investigated. Performance analysis illustrates that improper resource provisioning for IoT traffic not only degrades QoS of high-priority services and decreases battery lifetime of IoT devices, but also increases energy consumption of the access network. The presented analytical and simulations results figure out the ways in which spectral/energy efficiency for the access network and QoS for high-priority services could be traded to prolong battery lifetimes of connected devices by compromising on the level of provisioned radio resources.

Cell discontinuous transmission (DTX) has been proposed as a solution to reduce the energy consumption of cellular networks. This paper investigates the impact of network traffic load on the spectral and energy efficiency of cellular networks with DTX. The signal-to-interference-plus-noise ratio (SINR) distribution as a function of traffic load is derived first. Then, the sufficient condition for ignoring thermal noise and simplifying the SINR distribution is investigated. Based on the simplified SINR distribution, the network spectral and energy efficiency as functions of network traffic load are derived. It is shown that the network spectral efficiency increases monotonically in traffic load, while the optimal network energy efficiency depends on the ratio of the sleep-mode power consumption to the active-mode power consumption of base stations. If the ratio is larger than a certain threshold, the network energy efficiency increases monotonically with network traffic load and is maximized when the network is fully loaded. Otherwise, the network energy efficiency first increases and then decreases in network traffic load. The optimal load can be identified with a binary search algorithm. The power ratio threshold depends solely on the path loss exponent α, e.g., 56% for α = 4. All these analytic results are further validated by the numerical simulations.

Proximity-based applications are becoming fast growing markets suggesting that device-to-device (D2D) communications is becoming an essential part of the future mobile data networks. We propose scalable admission and power control methods for D2D communications underlay cellular networks to increase the reuse of frequency resources and thus network capacity while maintaining QoS to all users. In practice, as D2D communications will generate a new layer of interference, it is essential to take D2D interference into account in inter-cell interference coordination for multi-cell communications. The aim of the proposed methods is to maximize the number of D2D links under QoS constraints, therefore maximizing network frequency reuse in a practical 5G multi-cell environment. Different schemes are designed for applications that have different levels of complexity and availability of channel state information. Numerical results show that by using D2D and the proposed multi-cell interference coordination and low power transmission method, the network spectral efficiency can be increased by as much as ten times, while low outage probability can be assured to provide QoS for all users.

Fundamental tradeoffs in green cellular networks with coexistence of machine-oriented and human-oriented traffic are investigated. First, we present a queuing system to model the uplink transmission of a green base station which serves two types of distinct traffic with strict requirements on delay and battery lifetime. Then, the energy-lifetime and energy-delay tradeoffs are introduced, and closed-form expressions for energy consumption of the base station, average experienced delay in data transmission, and expected battery lifetime of machine devices are derived. Furthermore, we extend the derived results to the multi-cell scenario, and investigate the impacts of system and traffic parameters on the energy-lifetime and energy-delay tradeoffs using analytical and numerical results. Numerical results show the impact of energy saving for the access network on the introduced tradeoffs, and figure out the ways in which energy could be saved by compromising on the level of performance.

In this paper, we study the energy-efficient resource allocation (EERA) for heterogeneous networks, where different quality of service (QoS) requirements, including minimum-rate guarantee services and best effort (BE) services are taken into consideration. We formulate EERA scheme as a mixed-integer non-convex optimization problem, in which the power and sub- carrier allocation are jointly optimized to maximize the network utility, mitigate the cross-tier interference, and guarantee the fairness between the two classes of services and the fairness among the BE services. After transforming the problem into a convex optimization problem by some mathematic manipulations, we design an efficient iterative algorithm to solve this problem by Lagrangian dual decomposition method and gradient-based method. Simulation results validate the convergence and effec- tiveness of the proposed scheme.

In this paper, we investigate energy-efficient clustering and medium access control for cellular-based machine-to-machine (M2M) networks to minimize device energy consumption and prolong network battery lifetime. First, we present an accurate energy consumption model that considers both static and dynamic energy consumptions, and utilize this model to derive the network lifetime. Second, we find the cluster size to maximize the network lifetime and develop an energy-efficient cluster-head selection scheme. Furthermore, we find feasible regions where clustering is beneficial in enhancing network lifetime. We further investigate communications protocols for both intra- and inter-cluster communications. While inter-cluster communications use conventional cellular access schemes, we develop an energy-efficient and load-adaptive multiple access scheme, called n-phase carrier sense multiple access with collision avoidance (CSMA/CA), which provides a tunable tradeoff between energy efficiency, delay, and spectral efficiency of the network. The simulation results show that the proposed clustering, cluster-head selection, and communications protocol design outperform the others in energy saving and significantly prolong the lifetimes of both individual nodes and the whole M2M network.

In this paper the scheduling and transmit power control are investigated to minimize the energy consumption for battery-driven devices deployed in LTE networks. To enable efficient scheduling for a massive number of machine-type subscribers, a novel distributed scheme is proposed to let machine nodes form local clusters and communicate with the base-station through the cluster-heads. Then, uplink scheduling and power control in LTE networks are introduced and lifetime-aware solutions are investigated to be used for the communication between cluster-heads and the base-station. Beside the exact solutions, low-complexity suboptimal solutions are presented in this work which can achieve near optimal performance with much lower computational complexity. The performance evaluation shows that the network lifetime is significantly extended using the proposed protocols.

In this paper the uplink scheduling and transmit power control are investigated to minimize the energy consumption for battery-driven devices deployed in cellular networks. A lifetime metric, based on the accurate energy consumption model for cellular-based machine devices, is provided and used to formulate the uplink scheduling and power control problems as network-lifetime maximization problems. Then, lifetime-aware uplink scheduling and power control protocols which maximize the overall network-lifetime are investigated based on the different lifetime definitions. Besides the exact solution, a low-complexity suboptimal solution is presented in this work which can achieve near optimal lifetime-performance with much lower computational complexity. The performance evaluation shows that the network lifetime is significantly extended under proposed protocols.

This paper considers a scenario in which multiple device-to-device (D2D) users can reuse the uplink resources of a cellular network to transmit directly to their corresponding receivers. The aggregated interference from the D2D users is limited by applying a threshold on the allowable interference in the base station. The problem is solved under two types of constraints, namely, the peak interference and average interference constraints. In the former, we assume that full channel state information (CSI) is available at the base station, and we optimize the allowable transmit power for the D2D users so that the number of coexisting D2D communications is maximized. We further define a quality-of-service constraint for the D2D users. In practice, however, it is difficult to have complete CSI at the base station as it imposes heavy signaling overhead. Therefore, in the latter scenario, we assume that no knowledge about the location of D2D users and their CSI are available at the base station. This approach does not impose any signaling overhead. Our results show that even with no CSI knowledge, we are able to improve the system performance in terms of throughput by allowing coexisting D2D communications while satisfying the cellular user's constraints.

The increasing traffic demands bring heavy load to both the data and control planes of cellular networks, along with substantial energy consumption. To solve the issue, new network architecture that separates signaling and data has been proposed in literature for future green cellular networks. In this paper, we analyze the data and signaling resource configuration problem in this new network architecture. We find the optimal resource partitioning parameters to optimize the blocking performance and to minimize the overall network power consumption with a blocking probability constraint. More specifically, we adopt traffic-aware resource allocation between the data and signaling base stations (BSs) to improve network access capability while reducing the overall network power consumption. Two types of resource partitioning patterns, complete partitioning and partial partitioning, are studied. Numerical results show that great energy-saving gain can be achieved compared with the traditional fixed and traffic-proportional resource partitioning patterns. Moreover, power consumption and blocking performance tradeoffs are explored, based on which the appropriate resource partitioning pattern can be chosen according to different quality of service (QoS) requirements.

We propose a non-cooperative game-theoretic power allocation (NGPA) scheme for interference mitigation in long term evolution (LTE) uplink in this paper. We first set up the interference model employing conventional soft frequency reuse (SFR) scheme for inter-cell interference coordination (ICIC) in a nineteen-cell LTE network. Since each user may selfishly maximize its own performance in power allocation, we design a utility function that considers both quality of service (QoS) satisfaction and energy consumption. We then investigate the existence of Nash equilibrium and derive a sufficient condition to assure its uniqueness. Simulation results show that the proposed scheme improves throughput and coverage performances compared with conventional SFR schemes. Moreover, this scheme only requires limited signaling overhead among cells, which can be readily implemented in a distributed manner for practical systems.

In this paper, an energy-efficient non-cooperative game approach is proposed for channel-aware distributed medium access control (EN-CDMAC) in slotted-Aloha systems, where users act selfishly to improve their own utilities. To resolve the network contention in a distributed manner, the capture model is employed and a pricing-based non- cooperative game scheme is designed to enable selfish users effectively achieve multi-user diversity by adjusting their equilibrium thresholds while guaranteeing fairness by the pricing mechanism. Then the existence of Nash equilibrium is proved, and the necessary and sufficient condition is derived to ensure its uniqueness. Furthermore, the equilibrium stability is investigated with stochastic process theory. Simulation results show that the proposed approach significantly improves the network throughput and delay performance without sacrificing energy efficiency compared to the conventional slotted-Aloha scheme. In particular, the proposed approach is more applicable for high- load systems.

In this paper, we develop an uplink pilot and downlink link adaptation approach to improve the energy efficiency (EE) of mobile users in time division duplexing (TDD) multi-user multiple input and multiple output (MU-MIMO) systems. Assuming reciprocity between uplink and downlink channels, the downlink transmission is based on uplink channel estimation. While more uplink pilot power ensures more accurate channel estimation and better downlink performance, it incurs higher energy consumption of mobile users. This paper reveals the relationship and tradeoff among pilot power, channel estimation, and downlink link adaptation that achieves the highest energy efficiency for mobile users. We show that the energy efficiency of different users can be decoupled because the downlink average throughput of each user is independent of the pilot powers of other users and energy-efficient design can be done on a per-user basis. Based on the analysis, we propose an uplink pilot and downlink link adaptation algorithm to improve the EE of mobile users. Simulation results are finally provided to demonstrate the significant gain in energy efficiency for mobile users.

We study the problem of interference management for device-to-device (D2D) communications where multiple D2D users may coexist with one cellular user. The problem is to optimize the transmit power levels of D2D users to maximize the cell throughput while preserving the signal-to-noise-plus-interference ratio (SINR) performance for the cellular user. This is the so-called multi rate power control problem. We investigate the problem under two assumptions, the availability of the instantaneous or average channel state information (CSI) at the base station. In the first case, D2D transmit power levels adapt to fast fading, whereas in the second case, they only adapt to slow fading. In the latter assumption, the cellular user has a maximum outage probability requirement. With numerical results, we study the trade-off between the signaling overhead, that is frequent CSI feedbacks, and the overall system performance, that is the maximum achievable cell capacity, for D2D communications underlying cellular networks.

In this paper we discuss globally optimal energy-efficient communications in the wideband regime that is characterized by wide signal bandwidth and low spectral efficiency. An end-to-end multiple-hop system with one sender, one receiver, and multiple relays is considered. We discover the globally optimal link adaptation as well as relay deployment strategies such that the whole system can run with the highest energy efficiency. The technologies proposed can be used in various communication systems, such as the deployment and communication of wired core networks and wireless broadband relay backhauls, to improve their energy efficiency.

This paper addresses optimal energy-efficient design for uplink (UL) MU-MIMO in a single cell environment. The energy efficiency is measured by throughput per Joule, while both RF transmission power and device electronic circuit power are considered. We define the energy efficiency (EE) capacity for UL MU-MIMO and study the power allocation that achieves this capacity. First we assume all users consume a fixed amount of circuit power and show that user antennas should be used only when the corresponding spatial channels are sufficiently good and using them improves the overall network EE. Mobile devices may have improved circuit management capability and turn off circuit operations when some antennas are not used to reduce circuit power consumption. Therefore we further study energy-efficient UL MU-MIMO with improved circuit management and show that some antennas should not be used even when their channel states are good because turning them on consumes too much circuit power. Based on theoretical analysis, we further develop low-complexity yet globally optimal energy-efficient power allocation algorithms that converge to the optimum exponentially. Simulation results are provided to demonstrate the significant gain in network energy efficiency.

End-to-end communication is the fundamental building block of communication networks. In this paper, we discuss globally optimal energy efficient design for end-to-end communications. An end-to-end multiple-hop system with one sender, one receiver, and multiple relays is considered. We first study in detail energy-efficient designs in the wideband regime that is characterized by wide signal bandwidth and low spectral efficiency, and later briefly those in the narrowband regime. We will reveal the globally optimal link adaptation as well as relay deployment strategies such that the whole system can achieve the highest energy efficiency. The technologies proposed can be used in various communication systems, such as the deployment and communication of wired core networks and wireless relay networks, to improve their energy efficiency. While this paper focuses on a linear end-to-end network topology, the methodology can be easily extended to two-dimensional network topologies for energy-efficient designs of the whole network.

Energy efficiency is important for mobile devices because battery technology development has not kept up with the growing demand of ubiquitous broadband communications. This paper addresses optimal energy-efficient design for uplink (UL) MU-MIMO in a single cell environment. We assume mobile devices have dynamic antenna management capability and can turn off circuit operations when some antennas are not used to save power. We show that some antennas should not be used even when their channel states are good because turning them on consumes too much circuit power. This indicates a single antenna system could perform better than a multi-antenna system in terms of energy efficiency. Based on theoretical analysis, we further develop low-complexity yet globally optimal algorithms that converge to the optimum exponentially.

Multi-user MIMO is the enabling technology for LTE-Advanced systems to meet IMT-Advanced targets. The gain of multi-user MIMO is achieved partially through advanced user-grouping, user-scheduling, and precoding. Traditionally, multiuser MIMO scheduling focuses solely on spectral-efficiency [1]. That is, the scheduler will strike to balance the cell-edge user spectral-efficiency as well as the cell-average spectral-efficiency. Similar to spectral-efficiency, energy-efficiency is becoming increasingly important for wireless communications. The energy efficiency is measured by a classical measure, “throughput per Joule”, while both RF transmit power and device electronic circuit power consumptions are considered. In this paper, an energy-efficient proportional-fair scheduling is proposed for downlink multi-user MIMO systems. To specific, the scheduling algorithm is proposed to balance cell-edge energy-efficiency and the cell-average energy-efficiency. The energy-efficient proportional-fair metric is defined and the optimal power allocation maximizing the performance measure is identified. System level evaluation suggests that multi-user MIMO could improve the energy-efficiency of a wireless communication system significantly.

Energy-efficient wireless communication is very important for battery-constrained mobile devices. For mobile devices in a cellular system, uplink power consumption dominates the wireless power budget because of RF power requirements for reliable transmission over long distances. Our previous work in this area focused on optimizing energy efficiency by maximizing the instantaneous bits-per-Joule metric through iterative approaches, which resulted in significant energy savings for uplink cellular OFDMA transmissions. In this paper, we develop energy efficient schemes with significantly lower complexity when compared to iterative approaches, by considering time-averaged bits-per-Joule metrics. We consider an uplink OFDMA system where multiple users communicate to a central scheduler over frequency-selective channels with high energy efficiency. The scheduler allocates the system bandwidth among all users to optimize energy efficiency across the whole network. Using time-averaged metrics, we derive energy optimal techniques in "closed forms" for per-user link adaptation and resource scheduling across users. Simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions obtained through exhaustive search.

In this paper, we solve a fundamental problem: how to use distributed random access to achieve the performance of centralized schedulers. We consider wireless networks with arbitrary topologies and spatial traffic distributions, where users can receive traffic from or send traffic to different users and different communication links may interfere with each other. The channels are assumed heterogeneous, and the random channel gains of different links may have different distributions. To resolve the network contention in a distributed way, each frame is divided into contention and transmission periods. The contention period is used to resolve conflicts, while the transmission period is used to send payload in collision-free scenarios. We design a multistage channel-aware Aloha scheme for the contention period to enable users with relatively better channel states to have higher probabilities of contention success while assuring fairness among all users. We show analytically that the proposed scheme completely resolves network contention and achieves throughput close to that of centralized schedulers. Furthermore, the proposed scheme is robust to any uncertainty in channel estimation. Simulation results demonstrate that it significantly improves network performance while maintaining fairness among different users. The proposed random access approach can be applied to different wireless networks, such as cellular, sensor, and mobile ad hoc networks, to improve quality of service.

Energy efficiency is becoming increasingly important for mobile devices because battery technology has not kept up with the growing demand of ubiquitous multimedia communications. Since multi-user multiple-input multiple-output (MU-MIMO) is a key technology in next-generation wireless communications, this paper addresses optimal energy-efficient design for MU-MIMO. The energy efficiency is measured by a classic metric, ``throughput per Joule'', while both RF transmit power and device electronic circuit power are considered. We define the energy efficiency (EE) capacity for MU-MIMO and study the power allocation that achieves this capacity. We show that user antennas should be used only when the corresponding subchannels are sufficiently good and using them improves the overall network EE. Based on theoretical analysis, we further develop low-complexity yet globally optimal energy-efficient power allocation algorithms that converge to the optimum exponentially. Finally comprehensive simulation results are provided to demonstrate the significant gain in network energy efficiency.

Power optimization techniques are becoming increasingly important in wireless system design since battery technology has not kept up with the demand of mobile devices. They are also critical to interference management in wireless systems because interference usually results from both aggressive spectral reuse and high power transmission and severely limits system performance. In this paper, we develop an energy-efficient power optimization scheme for interference-limited wireless communications. We consider both circuit and transmission powers and focus on energy efficiency over throughput. We first investigate a non-cooperative game for energy-efficient power optimization in frequency-selective channels and reveal the conditions of the existence and uniqueness of the equilibrium for this game. Most importantly, we discover a sufficient condition for generic multi-channel power control to have a unique equilibrium in frequency-selective channels. Then we study the tradeoff between energy efficiency and spectral efficiency and show by simulation results that the proposed scheme improves both energy efficiency and spectral efficiency in an interference-limited multi-cell cellular network.

Energy efficiency is becoming increasingly important for small form factor mobile devices, as battery technology has not kept up with the growing requirements stemming from ubiquitous multimedia applications. This paper addresses link adaptive transmission for maximizing energy efficiency, as measured by the "throughput per Joule" metric. In contrast to the existing water-filling power allocation schemes that maximize throughput subject to a fixed overall transmit power constraint, our scheme maximizes energy efficiency by adapting both overall transmit power and its allocation, according to the channel states and the circuit power consumed. We demonstrate the existence of a unique globally optimal link adaptation solution and develop iterative algorithms to obtain it. We further consider the special case of flat-fading channels to develop an upper bound on energy efficiency and to characterize its variation with bandwidth, channel gain and circuit power. Our results for OFDM systems demonstrate improved energy savings with energy optimal link adaptation as well as illustrate the fundamental tradeoff between energy-efficient and spectrum-efficient transmission.

We investigate distributed channel-aware random access for networks with arbitrary topologies and traffic distributions, where users can receive traffic from or send traffic to different users and different communication links may interfere with others. We consider heterogeneous channels, where the random channel gains of different links may have different distributions. To resolve the network contention in a distributed way, each frame is divided into contention and transmission periods. The contention period is used to resolve conflicts near optimally and to schedule users with better channel states with higher probabilities while assuring fairness among all users. The proposed scheme completely resolves contention of networks with arbitrary topologies and is robust to any channel uncertainty. Besides, it performs close to central schedulers.

In this paper, we consider joint end-to-end congestion control and multiuser scheduling in multi-hop wireless networks, where orthogonal frequency-division multiple access (OFDMA) is the air interface. Compared to its single-channel counterpart, this problem is significantly more challenging because subchannel assignment and power allocation for all nodes and network traffic need to be jointly optimized. To avoid cochannel inference, we first consider an OFDMA subchannel separation problem in multi-hop communication scenarios. Then, we address this cross-layer optimization problem by decomposing it into two subproblems: a TCP layer congestion control for traffic allocation and a weighted scheduling for OFDMA subchannel assignment and power control. Observing that the scheduling for multiuser OFDMA in multi-hop wireless networks is inherently NP-hard, we propose a low-complexity algorithm that ensures a solution converging to the optimum. The performance of the algorithm is demonstrated through simulations.

While the demand for battery capacity on mobile devices has grown with the increase in high-bandwidth multimedia rich applications, battery technology has not kept up with this demand. Therefore power optimization techniques are becoming increasingly important in wireless system design. Power optimization schemes are also important for interference management in wireless systems as interference resulting from aggressive spectral reuse and high power transmission severely limits system performance. Although power optimization plays a pivotal role in both interference management and energy utilization, little research addresses their joint interaction. In this paper, we develop energy-efficient power optimization schemes for interference-limited communications. Both circuit and transmit powers are considered and energy efficiency is emphasized over throughput. We note that the general power optimization problem in the presence of interference is intractable even when ideal user cooperation is assumed. We first study this problem for a simple two-user network with ideal user cooperation and then develop a practical non-cooperative power optimization scheme. Simulation results show that the proposed scheme improves not only energy efficiency but also spectral efficiency in an interference-limited cellular network.

Energy efficient communications in wireless communications is very important as mobile devices are battery- constrained. For mobile devices in a cellular system, uplink power consumption dominates the wireless power budget, due to the RF power requirements for reliable communications over long distances. Our previous work in this area demonstrated significant energy savings in uplink cellular OFDMA transmissions, with iterative approaches maximizing the instantaneous bits-per- Joule energy efficiency. In this paper, we use a time-averaged bits-per-Joule metric to develop low-complexity schemes. Specifically, we obtain closed-form solutions for energy-efficient link adaptation in frequency-selective channels. We also derive closed- form approaches for the maximum arithmetic and geometric mean energy-efficient schedulers. Simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions.

Severe cochannel interference in wireless cellular networks significantly affects users at cell edges. We propose a cost-effective cochannel interference avoidance (CIA) medium access control (MAC) scheme to improve network performance. For CIA-MAC, base stations judged as severe interferers transmit randomly and the transmission is controlled by wireless channel states to optimize the overall network performance while maintaining proportional fairness among users. Conditions for triggering CIA-MAC are derived and two simple trigger mechanisms are obtained. The CIA-MAC scheme requires low signaling overhead and only minor changes to the existing mobile systems. Simulation results show that the proposed scheme, CIAMAC, significantly outperforms traditional approaches through the avoidance of severe cochannel interference as well as the exploitation of multiuser diversity through cross-layer design.

We consider schemes for decentralized cross-layer optimization of multichannel random access by exploiting local channel state and traffic information. In the network we are considering, users are not necessarily within the transmission ranges of all others; therefore, when a user is transmitting, it may only interfere with some users, which is different from most existing channel aware Aloha schemes. Besides, we also consider complicated traffic distribution, e.g. each user may choose to send packets to or receive packets from different users simultaneously. We develop decentralized optimization for multichannel random access (DOMRA). DOMRA consists of three steps: neighborhood information collection, transmission control of the MAC layer based on the instantaneous channel state information, and power allocation for each traffic flow on each subchannel. Simulation results demonstrated that DOMRA significantly outperforms existing channel aware Aloha schemes due to its exploitation of both multiuser diversity through cross-layer design and the inhomogeneous characteristics of traffic spatial distribution in the network. Besides, DOMRA performs closely to the globally optimum solution, which requires full network knowledge to be obtained. DOMRA can be applied to different types of wireless networks, such as wireless sensor networks and mobile ad hoc networks, to improve quality of service.

Abstract Since battery technology has not progressed as rapidly as semiconductor technology, power efficiency has become increasingly important in wireless networking, in addition to the traditional quality and performance measures, such as bandwidth, throughput, and fairness. Energy‐efficient design requires a cross layer approach as power consumption is affected by all aspects of system design, ranging from silicon to applications. This article presents a comprehensive overview of recent advances in cross‐layer design for energy‐efficient wireless communications. We particularly focus on a system‐based approaches toward energy optimal transmission and resource management across time, frequency, and spatial domains. Details related to energy‐efficient hardware implementations are also covered. Copyright © 2008 John Wiley & Sons, Ltd.

Energy efficiency is becoming increasingly important for small form factor mobile devices, as battery technology has not kept up with the growing requirements stemming from ubiquitous multimedia applications. This paper addresses link adaptive transmission for maximization of energy efficiency rather than throughput. We extend our previous results for flat fading OFDMA to frequency-selective channels. Different from existing water-filling power allocation schemes that maximize throughput subject to overall transmit power constraints, our scheme adapts both overall transmit power and its allocation according to the states of all subchannels and circuit power consumption to maximize energy efficiency. We demonstrate the existence of a unique globally optimal link adaptation solution and provide iterative algorithms to obtain this optimum. Simulation results show at least a 15% improvement in energy utilization when frequency selectivity is exploited.

Energy-efficient transmission is an important aspect of wireless system design due to limited battery power in mobile devices. We consider uplink energy-efficient transmission in OFDMA systems since mobile stations are battery powered. We account for both circuit and transmit power when designing energy-efficient communication mechanisms and emphasize energy efficiency over peak rates or throughput. Both link adaptation and resource allocation schemes are developed to optimize the overall bits transmitted per Joule of energy, which allows for maximum energy savings in a network. Our simulation results show that the proposed schemes significantly improve energy efficiency.

A utility based resource allocation scheme is investigated for improving system performance of 802.16 OFDMA systems supporting a mix of multi-media traffic types. We show that a utility based approach can improve system capacity over conventional proportional-fair resource allocation schemes through more efficient allocation of only the required resources demanded by the QoS profile of each traffic class. It is also shown that using average channel- aware metrics for resource allocation allows for local linearization of the utility function, which results in linear complexity OFDMA resource allocation schemes. Further, performance with the reduced complexity scheme is similar to a previously known near-optimal algorithm with cubic complexity.

This paper considers decentralized cross-layer optimization for multichannel random access with partial-local knowledge. In the network scenario considered, users are not necessarily within the transmission ranges of all other users, and each user may choose to send packets to or receive packets from different users simultaneously. A criterion for cross-layer optimization is provided leading to a decentralized optimization for multichannel random access (DOMRA) scheme. DOMRA can be applied to different types of wireless networks, such as wireless sensor networks and mobile ad hoc networks, to improve quality of service. Furthermore, DOMRA can be applied to optimize downlink transmissions in cellular networks for proposed cochannel interference avoidance (CIA) medium access control (MAC). CIA-MAC requires low signalling overhead and minor changes to existing mobile systems. The conditions for triggering CIA-MAC are investigated and a simple trigger mechanism is obtained. Simulation results confirm the significant performance improvement by the proposed schemes.

While most existing channel aware Aloha schemes focus on wireless networks where each user intends to send only one traffic flow, and interferes with all the other users, some wireless networks may have more complicated traffic distribution and the transmissions of different users may interfere with different groups of users. In this paper, we consider schemes for the decentralized cross-layer optimization of multichannel random access, in which users are not necessarily within the transmission ranges of all other users, and each user may choose to send packets to or receive packets from different users simultaneously. With cross-layer design, users are configured according to local neighborhood information to adapt to inhomogeneous network characteristics. It is demonstrated by simulation that the proposed scheme significantly outperforms existing channel aware Aloha schemes due to its exploitation of both multiuser diversity and the inhomogeneous characteristics of traffic distribution in the network.

Efficient bandwidth allocation is among the most important open issues in network traffic control aiming to offer a QoS assurance, especially when unicast and multicast multimedia flows coexist. With new QoS concepts: user/flow satisfaction, this paper presents a user perception oriented QoS model, and a generalized bandwidth allocation method which can actively adapt to the dynamics of the network and has global convergence capability for an optimal solution of bandwidth allocation. Our method effectively exploits all available bandwidth resources, and can provide effective QoS differentiated services when different types of unicast and multicast multimedia streams coexist. The proposed method has great flexibility that QoS differentiation can be guaranteed in both heavy and light load conditions. For heavy load cases, the allocation results will satisfy all users as much as possible. And for light load cases, all redundant bandwidth will be fully exploited while distinct QoS differentiation is kept. Based on our approach, a soft system capacity similar to the one in CDMA networks will be provided.

In ideal OFDM adaptive transmissions, each sub-carrier can get an independent adaptive mode according to the Channel State Information (CSI). The awfully large amount of CSI feedback and signalling transmissions will be a serious problem in adaptive OFDM systems. This paper focuses on the practical feedback and adaptive signalling designs of adaptive OFDM systems. Based on the characteristics of frequency selective channels, a Dynamic Neighboring Subcarrier Grouping Scheme (DNSGS) is proposed to cut down the feedback and adaptive signalling overhead, and to simplify the implementation of adaptive OFDM systems. Then the capacity of DNSGS based OFDM systems is also given. The simulation results powerfully show that the scheme designed in this paper is flexible enough for different kinds of communication environments, and can effectively cut down the feedback and signalling overhead with rather limited performance penalty. Besides, DNSGS outperforms the existing grouping schemes greatly.

Digital video broadcasting-terrestrial (DVB-T) is an ideal carrier for services requiring both high data rate and high mobility. Combined with other media as a return channel for user requests and acknowledgement signaling, DVB-T can supply interactive data services. With the exploitation of all available DVB channels, huge Internet access bandwidth can be provided, and it can be a highly recommendable candidate of future 4G/5G communications. In order to fully employ all channels, the profit oriented bandwidth allocation method (POBAM) with linear complexity is given for real-time joint channel bandwidth management. Simulation results powerfully show that POBAM can effectively exploit the multichannel resources for near global maximization of profit, and can effectively provide QoS differentiation. Besides, the joint channel bandwidth management outperforms the separate channel bandwidth management greatly. The complexity of POBAM is low enough for real time multichannel bandwidth management even when there're dozens of joint channels and hundreds of active users.

Digital terrestrial video broadcasting (DVB-T) provides an ideal means for providing services with both high data rate and high mobility, which exceeds the ability of current existing access technologies like UMTS, WLAN, and so forth. Combined with other media for the uplink as a return channel for user requests and acknowledgement signaling, DVB-T can supply interactive data services. In this paper, we show the architecture of integrated Internet and DVB-T network to provide interactive broadband Internet access services for users with high mobility. In order to fully exploit the valuable broadcast resources and provide services with effective QoS differentiation, we present a bandwidth allocation algorithm SOBAM (satisfaction oriented bandwidth allocation method) based on a new concept: user satisfaction. Simulation results prove the good performance of SOBAM, and show that with SOBAM, the integrated Internet and DVB-T network can provide a soft system capacity which is similar to the one in CDMA networks.