While there exists a great body of research on reflection optimization of a reconfigurable intelligent surface (RIS), these optimizations assume independent phase shift and amplitude for the RIS reflection coefficients. Moreover, the choice of phase is typically assumed to be continuous over the full range. In practice, the phase shift and the amplitude are coupled, and the phase choices are limited to a discrete set. In our work, we consider a practical RIS model with coupled phase shift and amplitude and limited phase choices. For the coupled RIS model, given a configuration set (which is a discrete set of coupled reflection coefficient choices that an RIS element can take), we develop an efficient method for capacity maximization by finding the optimal reflection coefficients of the RIS elements. Our method has a complexity linear with the number of RIS elements and the number of discrete reflection coefficient choices. We also develop a method that optimally selects the configuration set of the system.

Generative masked transformer have demonstrated remarkable success across various content generation tasks, primarily due to their ability to effectively model large-scale dataset distributions with high consistency. However, in the animation domain, large datasets are not always available. Applying generative masked modeling to generate diverse instances from a single MoCap reference may lead to overfitting, a challenge that remains unexplored. In this work, we present MotionDreamer, a localized masked modeling paradigm designed to learn motion internal patterns from a given motion with arbitrary topology and duration. By embedding the given motion into quantized tokens with a novel distribution regularization method, MotionDreamer constructs a robust and informative codebook for local motion patterns. Moreover, a sliding window local attention is introduced in our masked transformer, enabling the generation of natural yet diverse animations that closely resemble the reference motion patterns. As demonstrated through comprehensive experiments, MotionDreamer outperforms the state-of-the-art methods that are typically GAN or Diffusion-based in both faithfulness and diversity. Thanks to the consistency and robustness of quantization-based approach, MotionDreamer can also effectively perform downstream tasks such as temporal motion editing, crowd motion synthesis, and beat-aligned dance generation, all using a single reference motion. Our implementation, learned models and results are to be made publicly available upon paper acceptance.

For users requesting popular contents from content providers, edge caching can alleviate backhaul pressure and enhance the quality of experience of users. Recently there is also a growing concern about content freshness that is quantified by age of information (AoI). Therefore, AoI-aware online caching algorithms are required, which is challenging because the content popularity is usually unknown in advance and may vary over time. In this paper, we propose an online digital twin (DT) empowered content resale mechanism in AoI-aware edge caching networks. We aim to design an optimal two-timescale caching strategy to maximize the utility of an edge network service provider (ENSP). The formulated optimization problem is non-convex and NP-hard. To tackle this intractable problem, we propose a DT-assisted Online Caching Algorithm (DT-OCA). In specific, we first decompose our formulated problem into a series of subproblems, each handling a cache period. For each cache period, we use a DT-based prediction method to effectively capture future content popularity, and develop an online caching strategy. Competitive ratio analysis and extensive experimental results demonstrate that our algorithm has promising performance, and outperforms other benchmark algorithms. Insightful observations are also found and discussed.

Edge service caching can significantly mitigate latency and reduce communication and computing overhead by downloading and caching service (application) data from clouds. The freshness of cached service data is critical when providing satisfactory services to users, but has been overlooked in existing research efforts. In this paper, we study the online low-latency and fresh service provisioning in mobile edge computing (MEC) networks. Specifically, we jointly optimize the service caching, task offloading, and resource allocation. To solve the formulated joint online long-term optimization problem, we design a Lyapunov-based online framework that decouples the problem at temporal level into a series of per-time-slot subproblems. For each subproblem, we propose an online integrated optimization-deep reinforcement learning (OIODRL) method, which consists of an optimization stage and a learning stage. In the optimization stage of OIODRL, a quadratically constrained quadratic program (QCQP) transformation and a semidefinite relaxation (SDR) method are utilized; in the learning stage of OIODRL, a deep reinforcement learning (DRL) algorithm is applied. Extensive simulations show that the proposed OIODRL method achieves a near-optimal solution and outperforms benchmark methods.

Federated learning (FL) has emerged as an appealing machine learning approach to deal with massive raw data generated at multiple mobile devices, which needs to aggregate the training parameter of every mobile device at one base station (BS) iteratively. For parameter aggregating in FL, over-the-air computation is a spectrum-efficient solution, which allows all mobile devices to transmit their parameter-mapped signals concurrently to a BS. Due to heterogeneous channel fading and noise, there exists difference between the BS’s received signal and its desired signal, measured as the mean-squared error (MSE). To minimize the MSE, we propose to jointly optimize the signal amplification factors at the BS and the mobile devices as well as the data size (the number of data samples involved in local training) at every mobile device. The formulated problem is difficult to address due to its nonconvexity. To find the optimal solution, we perform cost function simplification and variable transformation, and solve the transformed problem in a two-level structure. Optimal solution of the lower level problem is found by analyzing every candidate solution from the Karush–Kuhn–Tucker (KKT) condition. Optimal solution of the upper level problem is found by exploring its piecewise convexity. Numerical results show that our proposed method can greatly reduce the MSE and can help to enhance the training performance of FL compared with benchmark methods.

We address the reflection optimization problem for a reconfigurable intelligent surface (RIS), where the RIS elements feature a set of non-uniformly spaced discrete phase shifts. This is motivated by the actual behavior of practical RIS elements, where it is shown that a uniform phase shift assumption is not realistic. A problem is formulated to find the optimal reflection amplitudes and reflection phase shifts of the RIS elements such that the channel capacity of the target user is maximized. We first prove that in the optimal configuration, each RIS element is either turned off or operates at maximum amplitude. We then develop a method that finds the optimal reflection amplitudes and phases with complexity linear with the number of RIS elements. An interesting insight into the reflection optimization problem is also provided.

This paper designs a helper-assisted offloading strategy in non-orthogonal multiple access enabled mobile edge computing systems, in order to guarantee the quality of service of the energy/delay-sensitive user equipments (UEs). To achieve a tradeoff between the energy consumption and the delay, we introduce a performance metric called energy-delay tradeoff. Aiming at the maximal energy-delay tradeoff minimization, the joint optimization of user association, resource block (RB) assignment, power allocation, task assignment, and computation resource allocation is formulated as a non-convex problem with coupled continuous and 0-1 variables. To tackle this challenging problem, we decompose it as a two-level problem. For the inner-level problem, an iterative parametric convex approximation (IPCA) algorithm is proposed. Then, based on the solution obtained from the inner-level problem, we model the outer-level problem as a four-sided matching problem, and then propose a low-complexity four-sided UE-RB-helper-server matching (FS-URHSM) algorithm. Theoretical analysis demonstrates that the IPCA algorithm can converge to a stationary Karush-Kuhn-Tucker (KKT) point and the FS-URHSM algorithm is guaranteed to converge to a stable matching with polynomial complexity. Simulation results demonstrate the superior performance of proposed algorithms in terms of the energy consumption and the delay.

This paper investigates a mobile edge computing (MEC) network assisted by an unmanned aerial vehicle (UAV), where the moving UAV and a fixed ground base station cooperatively provide MEC services for multiple ground users. To evaluate the quality of service under this architecture, we first derive the successful edge computing probability (SECP) to evaluate the service reliability. Given a target SECP requirement, we formulate a service coverage maximization problem by optimizing the UAV altitude and task offloading probability. The problem is hard to solve due to the coupled UAV altitude and task offloading probability in the derived SECP expression. To address this challenge, we first explore some interesting properties of the formulated problem, and then use these properties to develop a golden-section search based method to solve the formulated optimization problem. Numerical results are used to verify the theoretical analysis of our system and demonstrate the efficiency of the proposed scheme.

This paper investigates computing task offloading from an Internet-of-Thing (IoT) device with limited transmit power to a mobile-edge computing (MEC) server located beyond the communication range of the IoT device. We propose an opportunistic cooperative offloading (OCO) strategy that recruits the IoT device’s nearby spatially random idle-state users as helpers and opportunistically schedules one of them to partially execute the latency-critical task, and forwards the rest portion of the task to the MEC server. For the OCO strategy, we investigate the helper scheduling under three cases of system information availability, i.e., the global, partial, and distance information cases, and develop an offloading-outage optimal scheduling scheme for each case. For each scheduling scheme, an approximate expression is derived for the offloading-outage probability, with which the achieved diversity order is also theoretically evaluated. Simulation results verify our performance analysis for the OCO strategy using helper scheduling and show its achieved offloading-outage/energy consumption reduction over multi-helper cooperative offloading that fully uses all helpers for cooperation. In addition, the advantages of the proposed helper scheduling schemes over existing scheduling schemes are also demonstrated by simulations.

In mobile edge computing (MEC) supporting multiple mobile users (MUs), it is essential to optimize the offloading policy and communication and computation resource allocation. A main challenge is that the computation burden of a computation task may be random and even with uncertain probabilistic distribution. To address this challenge, we investigate a multiple-MU MEC system with random computation burden. For the random computation burden of an MU, only the mean and variance are known, but its distribution is unknown. Robustness is provided such that computation outage probabilities (due to uncertain distribution of computation burden) are bounded by a predefined threshold. We minimize the weighted sum of the MUs’ energy consumption. The formulated optimization problem is non-deterministic and non-convex, and thus, is hard to solve. To deal with the challenge, we transform the formulated problem into a deterministic and convex problem by applying the Chebyshev-Cantelli inequality and some mathematical manipulations. We further decompose the convex problem to a lower-level and an upper-level problem. Low-complexity algorithms are developed for the lower-level and upper-level problems. The overall complexity of our proposed method is linear with the number of MUs.

Bluetooth Low Energy (BLE) has become one of the enabling wireless technologies to facilitate the Internet of Things. Neighbor discovery is critical in BLE communications. BLE uses multiple (three) channels in neighbor discovery. It is challenging to achieve low-latency and low-energy-consumption BLE neighbor discovery due to the lack of analytical models for multichannel neighbor discovery. In this paper, we study BLE multichannel neighbor discovery for two advertising modes specified by BLE: periodic deterministic advertising (PDA) and pseudo-random delay advertising (RDA). We build two generic models, BLE 3-Circle model and BLE 1-Circle model, for characterizing BLE multichannel neighbor discovery. For PDA mode, we present a necessary and sufficient condition for BLE multichannel neighbor discovery, and provide a guideline for parameter setting. With the guideline, we derive the expected discovery latency in closed form, and demonstrate that the expected discovery latency is very close to a theoretical lower bound. For RDA mode, we build an analytical model based on Markov chain to accurately compute the expected discovery latency. Simulation and experimental results show accuracy of our analytical works. Interestingly, our parameter setting guideline works well for both PDA and RDA modes.

We study a wireless powered network, including a power beacon (PB), an energy-harvesting (EH)-based source, and multiple users. To improve the spectrum efficiency of the network as well as for practical implementation consideration, two users are paired to perform nonorthogonal multiple access (NOMA) transmission. Specifically, the NOMA-based transmission protocol consists of two phases, where the source harvests energy from the PB in the first phase, and then sends a superimposed signal to the paired users in the second phase. We derive exact and asymptotic closed-form expressions of the average throughput for each paired user. Then, the joint optimization problem for the time and power allocation is investigated to achieve the optimal fair performance of the paired users. To provide a benchmark, optimal resource allocation strategy for an orthogonal multiple access (OMA)-based transmission protocol is also studied. Simulation results confirm the validity of our analytical derivations and show that the considered network with NOMA transmissions is superior to that with OMA transmissions, especially when the transmit power of the PB is low and the paired users have significant differences in channel gain.

Deep neural networks (DNN) have gained considerable attention in the communication literature during the past few years. In particular, as a well-known DNN architecture, autoencoders (AE) are used to model the end-to-end communication systems achieving a reasonable performance in terms of block error rate (BLER). However, autoencoders significantly suffer from high peak-to-average-power-ratio (PAPR), resulting in power amplifier saturation. This paper proposes a novel DNN architecture for reducing PAPR in autoencoder-based communication systems. Simulation results verify that the proposed scheme outperforms the conventional PAPR reduction method, i.e., loss function-based PAPR reduction approach, in terms of both bit error rate (BER) and PAPR.

Internet of Things (IoT) networks are usually distributed in nature. Due to the possible mobility of IoT devices, it is common and critical for each IoT device to keep discovering who is in its neighborhood, referred to as neighbor discovery. Due to the limited battery capacity of IoT devices, it is challenging to design a neighbor discovery protocol (NDP) that can achieve both low duty cycle and low discovery latency. In this article, we build a model called Circle to characterize the process of neighbor discovery in IoT networks. Then, we give a necessary and sufficient condition for neighbor discovery and theoretically prove its correctness. This is the first time in the research community that a necessary and sufficient condition is given for neighbor discovery. According to the necessary and sufficient condition, we analytically derive a lower bound of the worst case discovery latency and demonstrate when the lower bound can be achieved. The analytical model is generic as it can be used to analyze existing NDPs. Based on the Circle model and the analysis, we propose an NDP, which is also called Circle. We compare Circle with the state-of-the-art NDPs in a real testbed, and experimental results show that Circle is superior to the existing state-of-the-art NDPs.

We investigate a secrecy-enhancing design for cooperative downlink and uplink non-orthogonal multiple access (NOMA) transmissions with an untrusted relay. A source uses the NOMA principle to have downlink and uplink transmissions with a near user and a far user, and the communications between the source and the far user are aided by an untrusted relay. To minimize information leakage at the untrusted relay and achieve secure NOMA communications, adaptive downlink and uplink cooperative jamming schemes are proposed, where the far user in downlink and the near user in uplink adaptively emit a jamming signal to the untrusted relay to impair its eavesdropping capability. Both downlink and uplink jamming power are optimized to fully exploit the benefits of the proposed schemes for security enhancement. Then, for each scheme, we quantify the secrecy performance by deriving the ergodic secrecy sum rate lower bound and its scaling law. Finally, computer simulation is used to demonstrate the effectiveness of the proposed adaptive downlink and uplink cooperative jamming schemes and verify the accuracy of the derived analytical results.

This paper designs a novel opportunistic adaptive non-orthogonal multiple access (OA-NOMA) strategy, where a base station (BS) employs NOMA to serve a near user (NU)-far user (FU) pair opportunistically scheduled from M NUs and K FUs. In particular, the NOMA transmission to the scheduled NU-FU pair adaptively operates in one of two modes: Direct NOMA mode, in which the BS directly serves the scheduled NU-FU pair with using NOMA; Cooperative NOMA mode, in which the scheduled NU receives the messages intended by both scheduled users from the BS, and then forwards the message intended by the scheduled FU. For the OA-NOMA strategy, a scheduling candidate acquisition method and a probabilistic user pair scheduling scheme are proposed to guarantee the transmission reliability and improve the scheduling fairness, respectively. To evaluate the scheduling fairness, we develop a max-min fairness criterion and show that the OA-NOMA strategy approximately achieves max-min fairness. The reliability of the OA-NOMA strategy is also evaluated in terms of outage probability and diversity order. For the outage probability, we derive an approximate expression and numerically verify its tightness. For the diversity order, we show that the proposed OA-NOMA strategy achieves a diversity order of M.

By allowing a mobile device to offload computation- intensive tasks to a base station, mobile edge computing (MEC) is a promising solution for saving the mobile device's energy. In real applications, the offloading may span multiple fading blocks. In this paper, we investigate energy-efficient offloading over multiple fading blocks with random channel gains. An optimization problem is formulated, to find out how much data should be offloaded such that the mobile device's energy consumption is minimal. Although the formulated optimization problem is non-convex, we prove that the objective function of the problem is piecewise convex, and accordingly develop an optimal solution for the problem. Numerical results verify the correctness of our findings and the effectiveness of our proposed method.

We study secure communications with an untrusted relay for a cooperative non-orthogonal multiple access (NOMA) system, where a base station (BS) serves a near user (NU) and a far user (FU) by the NOMA principle, and transmission between BS and FU is aided by an untrusted relay. We propose an adaptive jamming scheme to enhance transmission security, in which FU is asked to adaptively emit a jamming signal to confuse the untrusted relay. The transmission rate for jamming is designed to ensure that only NU can decode the jamming signal correctly, and the jamming power is optimized for maximizing the secrecy sum rate. We analyze the security performance of the proposed scheme and derive the ergodic secrecy sum rate and its scaling law. Simulation results are presented to validate the effectiveness of the proposed adaptive jamming scheme.

We investigate the optimal transmission policy for an energy-harvesting wireless sensor node. The node must decide whether an arrived packet should be transmitted or dropped, based on the packet's priority, wireless channel gain, and the energy status of the node. The problem is formulated under the Markov decision process (MDP) framework. For such a problem, the conventional method to get the optimal policy is by using a state value function, which is three-dimensional in the considered problem, leading to high complexity. Fortunately, to reduce complexity, we derive an equivalent solution for the optimal policy via a one-dimensional after-state value function. We show that the after-state value function is differentiable and nondecreasing. We also discover a threshold structure of the optimal policy that is derived by the after-state value function. Furthermore, to approximate the after-state value function, we propose a learning algorithm to train a three-layer monotone neural network. The trained network thus finds a near-optimal selective transmission policy of the node. Finally, through simulation, we demonstrate the learning efficiency of the algorithm and the performance of the learned policy.

This paper proposes a novel design of cooperative non-orthogonal layered multicast multiple access in a heterogeneous network, where the information is encoded into the messages of high priority (HP) and low priority (LP). Two types of multicast users coexist in the network: 1) regular users (RUs), which are located far away from the base station (BS) and expect to decode only the HP message (due to the weak channels), and 2) advanced users (AUs), which are located close to the BS and expect to decode both HP and LP messages. To improve the reliability of layered multicast, we consider that the successful AUs (those AUs who successfully decode the HP and LP messages) serve as potential relays to assist other AUs/RUs. Based on this idea, two novel cooperation strategies are proposed for different cases of channel information availability. For each proposed strategy, we derive closed-form exact outage probabilities of AUs and RUs and then further analyze their diversity orders. Moreover, considering that the layered multicast is outage-constrained, we theoretically evaluate the energy consumption of both strategies and demonstrate their energy saving gains over the direct non-orthogonal multiple access for layered multicast. Finally, our theoretical analysis is verified by numerical results, and the advantages of the proposed strategies are also demonstrated.

This paper proposes a novel design of cooperative non-orthogonal multiple access (NOMA) for layered multicast, where the information is encoded into the messages of high-priority (HP) and low-priority (LP). Two types of multicast users coexist in the system: 1) regular users (RUs), which locate far away from the base-station (BS) and demand only the HP message; 2) advanced users (AUs), which locate close to the BS and demand both HP and LP messages. To improve the reliability of layered multicast, an opportunistic cooperative NOMA multicast strategy is proposed, in which one successful AU is selected to forward both HP and LP messages. For the proposed strategy, we derive closed-form exact outage probabilities of AUs and RUs. By further carrying out the asymptotic analysis, the achieved diversity orders are shown to be not less than the number of AUs, i.e., full diversity is achieved. Finally, numerical results verify the theoretical analysis and demonstrate the superiority of the proposed strategy.

In this paper, we demonstrate the coverage probability improvement of a millimeter wave (mmWave) network due to the deployment of spatially random decode-and-forward (DF) relays. We assume the transmitter and receiver are located at a fixed distance and that the potential relay nodes are spatially distributed as a two dimensional homogeneous Poisson point process (PPP). We first derive the spatial distribution of decoding set of relays that meet the required signal-to-noise ratio (SNR) threshold. From this set, we select a relay that has minimum path- loss from the receiver and derive the coverage probability achievable due to this selection. The analysis is based on stochastic geometry and is verified via Monte-Carlo simulation. The coverage probabilities of (a) direct link without relaying and (b) relayed link are compared to show that relaying provides significant coverage improvements.

With the increasing use of smart objects, such as wearable health gadgets, household automation devices, and personal electronics, there is a growing demand for a globally interconnected information network, known as the Internet of Things (IoT). IoT is featured with low-power communications among a massive number of ubiquitously-deployed and energy-constrained electronics, like sensors and actuators. In this context, wireless-powered cooperative relaying emerges as a promising solution to extend coverage and solve energy scarcity problems for IoT devices. In this paper, we propose a novel hybrid relay by combining wireless-powered communications and ambient backscattering functions for improved applicability and performance. To well adapt the hybrid relay to the network environments, we design a mode selection protocol to coordinate between the two functions. Moreover, we analyze the successful transmission probability of a dual-hop relaying system with the hybrid relay. Through numerical results, we demonstrate the performance gain of the hybrid relay and the impact of the system parameters.

Due to the fading and broadcast nature of wireless medium, it is challenging to provide full wireless coverage and secure the transmitted signals from unintended users in cellular networks. As a result, cyber risks, such as service outage and secrecy outage, would inevitably occur and cause loss/damage to the users. To transfer the cyber risks and mitigate the impact of loss, cyber insurance appears to be a promising solution for the economics of wireless services. In this paper, we introduce a cyber insurance framework for wireless users to relieve loss from the cyber risks. In this framework, each user pays a premium to an insurer. If the user experiences an outage, he/she will claim the loss, and the insurer will pay the corresponding %claim or indemnity to the user. Under the network model of a large-scale massive multiple-input multiple- output (MIMO) cellular networks and cyber insurance, we first characterize the user performance in terms of both service outage probability and secrecy outage probability using stochastic geometry analysis. Based on these performance results, we quantify the ruin probability of the cyber insurer, which indicates the chance that the insurer does not have enough capital reserve to afford the claims from the outage users. Through numerical evaluation, we show that the ruin probability of the insurer can be efficiently reduced by equipping a larger number of antennas at base stations or increasing network frequency reuse.

The fifth-generation (5G) wireless networks are expected to provision value-added services with ubiquitous coverage, which makes data security unprecedentedly critical. In this context, physical layer security has emerged as a promising solution to safeguard data transmission by exploiting characteristics of the wireless medium. Despite the recent technological advance in physical layer security and wireless transmission, secrecy outages (i.e., data breaches) and service outages (i.e., connection failures) will inevitably happen and incur financial losses. This economical consequence is a fact that is mostly overlooked by the existing literature. To provide financial protection against secrecy outage and service outage, we introduce a cyber-insurance framework for wireless users in cellular networks, where each user pays a premium to an insurer for a future financial compensation if an outage occurs to him/her. In particular, we derive the network risks of the cellular users in terms of secrecy outage probability and service outage probability as well as the financial risk of the cyber insurer in terms of the ruin probability that indicates the chance that the insurer experiences a deficit in affording the losses of outage users. Through numerical evaluation, we demonstrate the impact of network performance on the financial risk of the insurer. The numerical results also show that the ruin probability of the insurer can be effectively reduced by equipping a larger number of antennas at the base stations or increasing network frequency reuse.

In this paper, we consider roadside infrastructure-to-roadside infrastructure communications in a vehicular ad hoc network. A remote roadside unit (RSU), which does not have connection to the backbone network, needs to send its data traffic to a central RSU (which has backbone connection) by using help from vehicles passing by. Cost is assigned to information transmission energy consumption, as well as possible violation of a soft delay bound. For each passing vehicle, the remote RSU needs to decide whether or not to ask for help from the vehicle, with a target at a minimal rate of cost. We derive an optimal decision strategy of the remote RSU, which is shown to have a conditional pure-threshold structure, i.e., when a vehicle arrives at the remote RSU, if the queuing delay of the data traffic at the remote RSU is above a threshold, it is optimal for the remote RSU to ask for help from the vehicle, with a condition that the vehicle's speed satisfies a requirement. We also provide a method that can theoretically derive the threshold. The conditional pure-threshold structure makes our derived strategy very easy to implement with very low computation complexity.

The recent advanced wireless energy harvesting technology has enabled wireless-powered communications to accommodate wireless data services in a self-sustainable manner. However, wireless-powered communications rely on active RF signals to communicate and result in high power consumption. On the other hand, ambient backscatter technology that passively reflects existing RF signal sources in the air to communicate has the potential to facilitate an implementation with ultra-low power consumption. In this paper, we introduce a hybrid device-to-device (D2D) communication paradigm by integrating ambient backscattering with wireless-powered communications. The hybrid D2D communications are self-sustainable, as no dedicated external power supply is required. However, since the radio signals for energy harvesting and for backscattering come from the ambient, the performance of the hybrid D2D communications depends largely on environment factors, e.g., distribution, spatial density, and transmission load of ambient energy sources. Therefore, we design two mode selection protocols for the hybrid D2D transmitter, allowing a more flexible adaptation to the environment. We then introduce analytical models to characterize the impacts of the considered environment factors on the hybrid D2D communication performance. Together with extensive simulations, our analysis shows that the communication performance benefits from larger repulsion, transmission load, and density of ambient energy sources. Furthermore, we investigate how different mode selection mechanisms affect the communication performance.

We consider a single channel energy harvesting cognitive radio system, where the joint optimization of spectrum sensing, channel probing and transmission power control is considered with the goal to maximize the throughput. We model this control problem as a two-stage continuous-state Markov decision process with one stage for sensing and probing control, and the other for transmission power control. By utilizing the stochastic structure of the two-stage Markov decision process, we simplify the model via the notion of after-state, which reduces the state space and facilitates decision makings. Finally, the performance of the generated strategy is investigated via simulation.

We consider an energy harvesting wireless communication link, where arriving data packets have different importance values. The wireless transmitter needs to decide whether each arriving data packet should be transmitted or not, based on the packet's importance value, channel condition, and energy status. Under certain conditions, we show this high dimensional control problem can be transformed to a one dimensional continuous value function estimation problem using the notion of after-state. Then, by analyzing the structure of the value function, we propose a polynomial approximation to effectively compress the continuous function space into a finite weight space. Furthermore, we develop a reinforcement learning algorithm for our after-state setting. Finally, the proposed function approximation and learning algorithm are investigated under various system parameter settings via simulation.

We consider a cognitive radio system, in which a secondary transmitter harvests energy from a primary transmitter's wireless signals. If the achievable rate of the primary transmitter's direct link to the primary receiver is smaller than a target rate, the secondary transmitter can provide decode-and-forward relaying service for the primary system and transmit its own data as well, in which the secondary transmitter uses a time-switching protocol to harvest energy and decode primary transmitter's information. Our target is to achieve maximal secondary throughput by selecting the time portion used for energy harvesting and the percentage of the secondary transmitter's power used for relaying. The formulated problem is nonconvex. To solve the problem, we show that, after some math manipulations, the initial problem can be converted to a problem with the objective function being theoretically proved to be quasiconcave. Then we propose a two-level bisection search algorithm to find the maximal objective function. The efficiency of our proposed method is demonstrated by computer simulation.

Self-sustainable communications based on advanced energy harvesting technologies have been under rapid development, which facilitate autonomous operation and energy-efficient transmission. Recently, ambient backscattering that leverages existing RF signal resources in the air has been invented to empower data communication among low-power devices. In this paper, we introduce hybrid device-to-device (D2D) communications by integrating ambient backscattering and wireless-powered communications. The hybrid D2D communications are self-sustainable, as no dedicated external power supply is required. However, since the radio signals for energy harvesting and backscattering come from external RF sources, the performance of the hybrid D2D communications needs to be optimized efficiently. As such, we design two mode selection protocols for the hybrid D2D transmitter, allowing a more flexible adaptation to the environment. We then introduce analytical models to characterize the impacts of the considered environment factors, e.g., distribution, spatial density, and transmission load of the ambient transmitters, on the hybrid D2D communications performance. Extensive simulations show that the repulsion factor among the ambient transmitters has a non-trivial impact on the communication performance. Additionally, we reveal how different mode selection protocols affect the performance metrics.

Optimal relay selection is investigated for secure cooperative communications against an adaptive eavesdropper that can perform eavesdropping if the eavesdropping link has good channel quality or perform jamming otherwise. A number of decode-and-forward relays are available for legitimate communications, among which one relay can be selected to help. For legitimate communications, three cases for availability of the eavesdropping channel information are considered: full channel knowledge, partial channel knowledge, and statistical channel knowledge. An optimal relay selection scheme is proposed for each case. For the first and third cases, exact secrecy outage probability expressions in closed form are derived, and for the second case, an approximate secrecy outage probability is derived, which is tight in the high main-to-eavesdropper ratio regime. Moreover, secrecy diversity order for the proposed relay selection scheme in each case is also derived, which is shown to be a full secrecy diversity. Finally, numerical results are given to verify the theoretical analysis derived in this paper.

Abstract This paper investigates the channel selection and slot time configuration in a cognitive radio network with a number of potential channels. Each channel alternates between ON state (i.e., the primary user is using the channel) and OFF state (i.e., the primary user does not use the channel), and the state evolution process is modeled as a continuous‐time Markov process. The traffic parameters (the transition rates) of the Markov process also evolve with time, modeled as a discrete‐time Markov process. A secondary user adopts a slotted structure with dynamic slot length. At each slot, the secondary user needs to determine which channel to sense and, if the channel is sensed idle, how long the slot length should be. Considering both the amount of data that the secondary user can transmit and the duration when the secondary user interferes with primary activities, a reward definition is given. Based on the reward definition, an adaptive channel selection and slot length configuration method is proposed, which includes a reward maximization procedure to maximize the achieved reward and an update procedure for the channel state belief vector and traffic parameter state belief vector. Numerical results are given to demonstrate the effectiveness and features of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.

We consider a wireless energy harvesting (EH) relay network. Relays without embedded energy supply harvest energy from the source node. Considering a time switching protocol, performance measures such as average signal-to-noise ratio (SNR), outage and throughput are analyzed. Subsequently, optimal EH time is selected in order to maximize the throughput. Then, a multiple-relay network is considered with relay selection, which can achieve full diversity at any EH time. All theoretical results are validated by numerical simulations.

Spectrum sensing performance of a cognitive radio (CR) deploying the traditional energy detector (ED) degrades in the presence of random network interference where both the number and locations of the interferers are random, thus preventing correct detection of primary user (PU) in the band of interest. However, it is not clear how the ED performance in such random network interference can be improved. Moreover, the previous studies do not consider complete modeling of the wireless environment including the cumulative effects of path-loss, fading and random network interference. We thus take these effects into account and investigate the performance of the p-norm detector, which offers the flexibility of adapting p to the operating conditions (as against fixed p = 2 for ED). Such adaptability yields remarkable performance gains over ED (say, 15% gain even at 10 dB lower (than that for ED) PU signal powers). Further, cooperative spectrum sensing with multiple CRs yields additional performance gains (say, 30% better performance at optimal cooperative detection threshold) compared to single CR based sensing even under the cumulative effects of path-loss, fading and random network interference.

Missed-detection probability expressions for energy detectors often involve infinite series and do not provide quick insights into the effects of operating conditions. To overcome these limitations, we develop novel asymptotic analyses by proposing an approximate probability density function (PDF) of a random variable β, which, in general, can characterize fading channels in diverse operating conditions. The coefficients of the proposed approximate PDF of β are obtained by matching the coefficients of the approximate PDF's series expansion (or coefficients of the approximate PDF's moment generating function (MGF)) with those of the exact PDF (or MGF) of β. By using the proposed approximation, a unified closed-form asymptotic missed-detection probability is derived. Its usefulness is then demonstrated for fading channels without and with antenna diversity, for cooperative detection, and in co-channel interference. For each case, the sensing gain, which reveals the effect of the operating conditions on the detection performance, is determined explicitly. Furthermore, the asymptotic complementary area under the receiver operating characteristic curve, an alternative performance metric, is derived, and found to reveal the sensing gain. Numerical results verify the accuracy of our derived asymptotic expressions over a wider signal-to-noise ratio (SNR) range compared to the existing asymptotic solution, which is accurate only for high SNRs.

Performance analysis of the energy detector (ED) in fading channels has received enormous attention recently. However, averaging the generalized Marcum-Q function over fading statistics often results in complicated special functions and/or infinite series based expressions. Motivated by the need for simple expressions without compromising the accuracy, we propose a new representation for the probability density function (PDF) of the fading channel gain. This representation is then used to derive simple, unified expression for asymptotic miss-detection probability in closed-form. The derived expression is evaluated for several fading channels and antenna diversity schemes. Numerical results reveal its high accuracy over a wide range of signal-to-noise-ratio (SNR) (as low as 0 dB) unlike the existing asymptotic expression which is accurate only for high SNR regime (say, SNR ≥ 20 dB).

The problem of jamming on a multiple-input multiple-output (MIMO) Gaussian channel is investigated. We show that the existing result based on the simplification of the system model by neglecting the jamming channel leads to losing important insights regarding the effect of jamming power and jamming channel on the jamming strategy. We find a closed-form optimal solution for the problem under some positive semidefinite condition without considering simplifications in the model. If the condition is not satisfied and the optimal solution may not exist in closed-form, we find a suboptimal solution in closed-form as a close approximation of the optimal solution. Simulation results verify the effectiveness of the proposed solutions.

This paper investigates the relay selection (RS) problem in networks with multiple users and multiple common amplify-and-forward (AF) relays. We first give an optimality measure for RS in multiple-user relay networks. An optimal RS (ORS) algorithm is then provided, which is an extension of an RS scheme in the literature that maximizes the minimum end-to-end receive signal-to-noise ratio (SNR) of all users. The complexity of the ORS is quadratic in both the number of users and the number of relays. A suboptimal RS (SRS) scheme is also proposed, which has linear complexity in the number of relays and quadratic complexity in the number of users. Furthermore, diversity orders of both the ORS and the proposed SRS are derived and compared with those of a naive RS scheme and the single-user case. The ORS is shown to achieve full diversity, while the diversity order of the SRS decreases with the number of users. For two-user networks, the closed-form outage probabilities and array gains corresponding to the minimum SNR of the users in the RS schemes are derived. It is proved that the advantage of the SRS over the naive RS scheme increases as the number of relays in the network increases. Simulation results are provided to corroborate the analytical results.

In this paper, the problem of opportunistic channel sensing and access in cognitive radio networks when the sensing is imperfect and a secondary user can access up to a limited number of channels at a time is investigated. Primary users' statistical information is assumed to be unknown, and therefore, a secondary user needs to learn the information online during channel sensing and access process, which means learning loss, also referred to as regret, is inevitable. For each channel, the busy/idle state is independent from one slot to another. In this research, the case when all potential channels can be sensed simultaneously is investigated first. The channel access process is modeled as a multi-armed bandit problem with side observation. And channel access rules are derived and theoretically proved to have asymptotically finite regret. Then the case when the secondary user can sense only a limited number of channels at a time is investigated. The channel sensing and access process is modeled as a bi-level multi-armed bandit problem. It is shown that any adaptive rule has at least logarithmic regret. Then we derive channel sensing and access rules and theoretically prove that they have logarithmic regret asymptotically and with finite time. The case when the busy/idle states of a channel are correlated over slots is also investigated. And a channel sensing and access rule with logarithmic regret is derived. The effectiveness of the derived rules is validated by simulation.

This paper studies relay selection schemes for two-way amplify-and-forward (AF) relay networks. For a network with two users that exchange information via multiple AF relays, we first consider a single-relay selection (SRS) scheme based on the maximization of the worse signal-to-noise ratio (SNR) of the two end users. The cumulative distribution function (CDF) of the worse SNR of the two users and its approximations are obtained, based on which the block error rate (BLER), the diversity order, the outage probability, and the sum-rate of the two-way network are derived. Then, with the help of a relay ordering, a multiple-relay selection (MRS) scheme is developed. The training overhead and feedback requirement for the implementation of the relay selection schemes are discussed. Numerical and simulation results are provided to corroborate the analytical results.

ABSTRACT For a wireless ad hoc network to achieve fault‐tolerance, it is desired that the network is bi‐connected. This means that each pair of nodes in the network have at least two node‐disjoint paths between them, and thus, failure at any single node does not partition the network. In other words, in a bi‐connected network, there is nocut‐node(defined as a node such that the removal of it partitions the network). To make a connected but not bi‐connected network become bi‐connected, actions should be taken such that all cut‐nodes become non‐cut‐nodes. In this research, we propose to deal with cut‐nodes from a new perspective. Specifically, we first introduce a new concept ofremovable node, defined as a non‐cut‐node such that the removal of it does not generate any new cut‐node in the network. Then, we propose to move a removable node to a new location around a cut‐node. In this way, the cut‐node becomes a non‐cut‐node, that is, the failure of it does not partition the network anymore. Algorithms are provided (i) to identify removable nodes; (ii) to match cut‐nodes with a feasible set of removable nodes, in which all nodes can be simultaneously removed from the network without generating any new cut‐node in the network; and (iii) to derive the final location of a removable node such that its movement distance is the shortest and the associated cut‐node becomes a non‐cut‐node. The proposed algorithms do not guarantee the final bi‐connectivity but have the merits of a large success rate (almost 100% in the simulation), a small number of moved nodes, and a short total movement distance. In addition, the proposed algorithms are shown to be effective even when there are a large portion of fixed nodes in the network. Copyright © 2011 John Wiley & Sons, Ltd.

The problem of sum-rate maximization with minimum power consumption is studied for a decode-and-forward (DF) multiple-input multiple-output (MIMO) two-way relaying system consisting of two sources and one relay. Two scenarios are investigated. In the first scenario, the relay optimizes its own power allocation/beamforming strategy given that the strategies of the sources maximize the sum-rate of the multiple-access channel (MAC) phase. In the second scenario, the relay and the sources jointly optimize their power allocation/beamforming strategies over both the MAC and broadcasting (BC) phases. The considered problem of sum-rate maximization with minimum power consumption is shown to be nonconvex in both scenarios. For the first scenario, an algorithm is proposed to find the optimal strategy of the relay. For the second scenario, the sources and the relay find their strategies either through transferring the original nonconvex problem into corresponding convex problems or using a proposed low-complexity algorithm. Simulation results demonstrate the performance of proposed algorithms.

In this paper, a new robust routing formulation in a wireless mesh network (WMN) is proposed, which enables the routing strategy to be robust to random traffic fluctuation. Together with resource allocation in link layer, an optimization problem aiming at minimizing the total transmission power in the WMN is formulated and solved optimally. The research assumes only limited knowledge of the traffic distribution, in particular, arbitrary distribution with known mean and variance. Numerical results are presented to illustrate the features of the proposed strategy.

In this paper, the problem of distributed opportunistic channel access in wireless relaying is investigated. A relay network with multiple source-destination pairs and multiple relays is considered. All source nodes contend through a random access procedure. A winner source may give up its transmission opportunity if its link quality is poor. In this research, we apply the optimal stopping theory to analyze when a winner source should give up its transmission opportunity. By assuming the winner source has channel state information (CSI) of links from itself to relays and from relays to its destination, the existence of an optimal stopping strategy is rigorously proved. The optimal stopping strategy has a pure-threshold structure. The case when a winner source does not have CSI of links from relays to its destination is also studied. Two stopping problems exist, one in the main layer (for channel access of sources), and the other in the sub-layer (for channel access of relays). An intuitive stopping strategy, where the main layer (for the first hop) and sub-layer (for the second hop) maximize their throughput respectively, is derived. The intuitive stopping strategy is shown to be non-optimal. An optimal stopping strategy is then derived theoretically. In either the intuitive stopping strategy or the optimal stopping strategy, the main-layer stopping rule has a pure-threshold structure, while the sub-layer stopping rule has a threshold determined by the channel realization in the preceding first-hop transmission. Our research reveals that multi-user (including multi-source and multi-relay) diversity and time diversity can be utilized in a relay network by our proposed strategies. The effectiveness of the strategies is validated by numerical and simulation results.

In wireless multicast systems, cooperative multicast has been shown to be effective in dealing with heterogeneous channel conditions and improving the system performance. However, this mechanism requires users' voluntary contributions, which cannot be guaranteed since users are selfish and care only about their own performance. To stimulate user cooperation, in this work, we model the interaction among users in the wireless multicast system as a multi-buyer multi-seller price-based game, where users pay to receive relay service and get paid if they forward packets to others. It is a Stackelberg game, and backward induction is used to find the perfect Nash Equilibrium. We formulate the buyers' game as an evolutionary game and derive the evolutionarily stable strategy. Our simulation results demonstrate the effectiveness of our proposed incentive mechanism.

As required in the IEEE 802.22 proposal, spectrum sensing techniques should be capable enough to sense the primary signal with very low receiver sensitivity such as at -116 dBm. In this paper, the detection performance of an energy detector used for spectrum sensing in cognitive radio networks is investigated under such very low signal-to-noise ratio (SNR) levels. The analysis focuses on the derivation of a closed-form expression for the average missed-detection probability over Rayleigh fading and Nakagami-m fading channels. Subsequently, the detection threshold is optimized for minimizing the total error rate. The analysis is validated by numerical and simulation results. The sensing requirements defined in IEEE 802.22 are also discussed with numerical examples.

The problem of power allocation/channel selection in two-user games is considered. Unlike most of the game theoretic studies on resource allocation problems which consider pure strategies, this work investigates mixed strategies and mixed strategy Nash equilibrium (MSNE) that enables users to adopt more subtle strategies to improve their utilities. The necessary and sufficient conditions for the existence/uniqueness of MSNE are derived, first in a two-channel case and then in a more practical N channel case. In the two-channel game, the MSNE which maximizes the utilities of both users is found. In the N-channel game, a channel selection algorithm for the users, the outputs of which can be used to check the existence/uniqueness of MSNE, is proposed.

This paper considers the design of efficient strategies that allow cognitive users to choose frequency bands to sense and access among multiple bands with unknown parameters. First, the scenario in which a single cognitive user wishes to opportunistically exploit the availability of frequency bands is considered. By adopting tools from the classical bandit problem, optimal as well as low complexity asymptotically optimal solutions are developed. Next, the multiple cognitive user scenario is considered. The situation in which the availability probability of each channel is known is first considered. An optimal symmetric strategy that maximizes the total throughput of the cognitive users is developed. To avoid the possible selfish behavior of the cognitive users, a game-theoretic model is then developed. The performance of both models is characterized analytically. Then, the situation in which the availability probability of each channel is unknown a priori is considered. Low-complexity medium access protocols, which strike an optimal balance between exploration and exploitation in such competitive environments, are developed. The operating points of these low-complexity protocols are shown to converge to those of the scenario in which the availability probabilities are known. Finally, numerical results are provided to illustrate the impact of sensing errors and other practical considerations.

Detection performance of an energy detector used for cooperative spectrum sensing in a cognitive radio network is investigated over channels with both multipath fading and shadowing. The analysis focuses on two fusion strategies: data fusion and decision fusion. Under data fusion, upper bounds for average detection probabilities are derived for four scenarios: 1) single cognitive relay; 2) multiple cognitive relays; 3) multiple cognitive relays with direct link; and 4) multi-hop cognitive relays. Under decision fusion, the exact detection and false alarm probabilities are derived under the generalized "k-out-of-n" fusion rule at the fusion center with consideration of errors in the reporting channel due to fading. The results are extended to a multi-hop network as well. Our analysis is validated by numerical and simulation results. Although this research focuses on Rayleigh multipath fading and lognormal shadowing, the analytical framework can be extended to channels with Nakagami-m multipath fading and lognormal shadowing as well.

Composite fading (i.e., multipath fading and shadowing together) has increasingly been analyzed by means of the K channel and related models. Nevertheless, these models do have computational and analytical difficulties. Motivated by this context, we propose a mixture gamma (MG) distribution for the signal-to-noise ratio (SNR) of wireless channels. Not only is it a more accurate model for composite fading, but is also a versatile approximation for any fading SNR. As this distribution consists of N (≥ 1) component gamma distributions, we show how its parameters can be determined by using probability density function (PDF) or moment generating function (MGF) matching. We demonstrate the accuracy of the MG model by computing the mean square error (MSE) or the Kullback-Leibler (KL) divergence or by comparing the moments. With this model, performance metrics such as the average channel capacity, the outage probability, the symbol error rate (SER), and the detection capability of an energy detector are readily derived.

This paper investigates detection capability of energy detectors. With the help of receiver operating characteristics (ROC) curve and area under the ROC curve (AUC), a new measure, Complementary AUC (CAUC), is introduced as a proxy for the overall detection capability. When relays are available to help forward the target signal, the upper bound of the CAUC under Rayleigh fading channels is derived without and with a direct path. In addition, the average CAUC is discussed for Nakagami-m fading channels without and with diversity combining. The analytical results are validated by numerical examples.

The problem of resource allocation among multiple users with total power and spectral mask constraints is studied based on cooperative game-theoretic approach. The problem is non-convex, and finding the optimal solution requires joint power and bandwidth allocation that renders high-complexity algorithms. Therefore, we first categorize the systems to bandwidth-dominant and power-dominant according to their bottleneck resources. Then, different manners of cooperation are adopted for each type of systems, and a two-user algorithm is developed for each case. Such categorization guarantees that the solution obtained in each case is Pareto-optimal, while the complexity is significantly reduced.

The Nakagami-lognormal distribution is the commonly used composite distribution for modeling multipath fading and shadowing. In this paper, simple and new form of distribution which can accurately represent both the mutlipath fading and shadowing effects is introduced. The signal-to-noise ratio (SNR) of the Nakagami-lognormal distribution follows the gamma-lognormal distribution, which is accurately approximated by a weighted mixture of gamma distributions. We show how the weights and other parameters of the summands are obtained. Further, accuracy of the mixture distribution is compared with the KGdistribution - a popular approximation of the Nakagami-lognormal distribution.

A simple figure of merit to describe the performance of an energy detector is desirable. The area under the receiver operating characteristic (ROC) curve, denoted (AUC), is such a measure, which varies between 1/2 and 1. If the detector's performance is no better than flipping a coin, then the AUC is 1/2 , and it increases to one as the detector performance improves. However, in the wireless literature, the AUC measure has gone unnoticed. In this paper, to address this gap, we comprehensively analyze the AUC of an energy detector with no-diversity reception and with several popular diversity schemes. The channel model is assumed to be Nakagami-m fading. First, the average AUC is derived for the case of no-diversity reception. Second, the average AUC is derived for diversity reception cases including maximal ratio combining (MRC), square-law combining (SLC) and selection combining (SC). Further, for Rayleigh fading channels, the impacts of channel estimation errors and fading correlations are analyzed. High SNR (signal-to-noise ratio) approximations and the detection diversity gain are also derived. The analytical results are verified by numerical computations and by Monte-Carlo simulations.

This paper analyzes the performance of an energy detector over wireless channels with composite multipath fading and shadowing effects. These effects are modeled by using the K and K_G channel models. Closed-form average detection probabilities are derived for both K and K_G channel models for the no-diversity reception case. A simple approximation is also derived for large values of energy threshold in the energy detector. The analysis is then extended to cases with diversity receptions including maximal ratio combining (MRC) and selection combining (SC). Analytical results are verified by Monte Carlo simulation and by numerical methods. Receiver operating characteristic (ROC) curves are presented for different degrees of multipath fading and shadowing. Finally, the Rayleigh-lognormal distribution and the K distribution are numerically compared, and the validity of the K channel model for representing the impact of shadowing on the performance of energy detection is affirmed.

In this paper, optimal multi-channel cooperative sensing strategies in cognitive radio networks are investigated. A cognitive radio network with multiple potential channels is considered. Secondary users cooperatively sense the channels and send the sensing results to a coordinator, in which energy detection with a soft decision rule is employed to estimate whether there are primary activities in the channels. An optimization problem is formulated, which maximizes the throughput of secondary users while keeping detection probability for each channel above a pre-defined threshold. In particular, two sensing modes are investigated: slotted-time sensing mode and continuous-time sensing mode. With a slotted-time sensing mode, the sensing time of each secondary user consists of a number of mini-slots, each of which can be used to sense one channel. The initial optimization problem is shown to be a nonconvex mixed-integer problem. A polynomial-complexity algorithm is proposed to solve the problem optimally. With a continuous-time sensing mode, the sensing time of each secondary user for a channel can be any arbitrary continuous value. The initial nonconvex problem is converted into a convex bilevel problem, which can be successfully solved by existing methods. Numerical results are presented to demonstrate the effectiveness of our proposed algorithms.

Abstract Future mobilead hocnetworks are expected to support voice traffic. The requirement for small delay and jitter of voice traffic poses a significant challenge for medium access control (MAC) in such networks. User mobility presents unique difficulties in this context due to the associated dynamic path attenuation. In this paper, a MAC scheme for mobilead hocnetworks supporting voice traffic is proposed. With the aid of a low‐power probe prior to DATA transmissions, resource reservation is achieved in a distributed manner, thus leading to small packet transmission delay and jitter. The proposed scheme can automatically adapt to dynamic path attenuation in a mobile environment. Statistical multiplexing of on/off voice traffic can also be achieved by partial resource reservation for off voice flows. Simulation results demonstrate the effectiveness of the proposed scheme. Copyright © 2009 John Wiley & Sons, Ltd.

In this paper, we exploit cooperative spectrum sensing technique for applications in a relay based cognitive radio network. Relays are assigned in cognitive radio networks to transmit the primary user's signal to a cognitive coordinator. This research is focused on the detection of primary user in single or multiple cognitive relay scenarios. The performance of energy detector is analyzed for independent Rayleigh fading channels. False alarm and detection probabilities are derived theoretically with or without direct communication between the primary user and the cognitive coordinator. An upper bound is also given for detection probability. Our analysis is validated by numerical and simulation results.

A precoding strategy for multi-user spectrum sharing over an interference channel is proposed and analyzed from a game-theoretic perspective. The proposed strategy is based on finding the Nash bargaining solution for precoding matrices in a cooperative scenario over frequency selective channels under a spectrum mask constraint. An in-time update of the precoding matrices is enabled by using time slots to guarantee the effectiveness of the bargaining solution when the number of users varies. A dual decomposition approach is exploited to construct a distributed structure for solving the bargaining problem. The proposed distributed algorithm realizes the physical process of bargaining, which is not present in the Nash bargaining theory.

In this paper, quality of service (QoS) provisioning for voice service over cognitive radio networks is considered. As voice traffic is sensitive to delay, the presence of primary users and the requirement that secondary users should not interfere with them pose many challenges for QoS support for secondary voice users. Two cognitive medium access schemes are proposed in this paper for the secondary voice users to access the available channel. An analytical model is developed to obtain the voice service capacity (i.e., the maximum number of voice users that can be supported with QoS guarantee) for the secondary users, taking the impact of primary users' activities into consideration. The analytical model is validated by the simulation. The analytical results will be useful to support voice service in cognitive radio networks.

Two major challenges exist in the development and deployment of cognitive radio networks: spectrum sensing and hidden terminal problem. In this research, we consider a network structure where the spectrum sensing task is separated from the unlicensed users (secondary users). The service provider for the secondary users needs to place sensing devices within the networks of licensed users (primary users). These sensing devices sense the primary users' activity. The sensing devices also decide whether to admit a secondary user's transmission. A new cognitive cycle is proposed accordingly. The proposed protocol is analyzed using the theory of Lamé curve. The problem of optimally locating sensing devices and the properties of the proposed system are studied for single-user case and multi-user case. For the case without a separate control channel, a lowtemperature handshake technique is proposed for handshakes between the secondary users and the sensing devices. The other advantage of the proposed scheme is from the business model point of view: the expensive sensing devices will be implemented by the cognitive radio service provider, instead of being built in the secondary user devices which are usually consumer products demanding low cost.

This paper investigates the optimal sensing order problem in multi-channel cognitive medium access control with opportunistic transmissions. The scenario in which the availability probability of each channel is known is considered first. In this case, when the potential channels are identical (except for the availability probabilities) and independent, it is shown that, although the intuitive sensing order (i.e., descending order of the channel availability probabilities) is optimal when adaptive modulation is not used, it does not lead to optimality in general with adaptive modulation. Thus, a dynamic programming approach to the search for an optimal sensing order with adaptive modulation is presented. For some special cases, it is proved that a simple optimal sensing order does exist. More complex scenarios are then considered, e.g., in which the availability probability of each channel is unknown. Optimal strategies are developed to address the challenges created by this additional uncertainty. Finally, a scheme is developed to address the issue of sensing errors.

Abstract Localization is essential for wireless sensor networks (WSNs). It is to determine the positions of sensor nodes based on incomplete mutual distance measurements. In this paper, to measure the accuracy of localization algorithms, a ranging error model for time of arrival (TOA) estimation is given, and the Cramer—Rao Bound (CRB) for the model is derived. Then an algorithm is proposed to deal with the case where (1) ranging error accumulation exists, and (2) some anchor nodes broadcast inaccurate/wrong location information. Specifically, we first present a ranging error‐tolerable topology reconstruction method without knowledge of anchor node locations. Then we propose a method to detect anchor nodes whose location information is inaccurate/wrong. Simulations demonstrate the effectiveness of our algorithm. Copyright © 2008 John Wiley & Sons, Ltd.

In this paper, preceding strategies over interference channels are analyzed from a game-theoretic perspective. The Nash equilibrium and Nash bargaining solutions of preceding matrices, as the optimal precoding strategies in non-cooperative and cooperative cases, respectively, are derived for a two-player game over both flat fading and frequency selective channels. It is shown that the non-cooperative and cooperative solutions of precoding matrices are the same over multiple-input single- output(MISO) flat fading interference channels under a total power constraint. The solution in flat fading channel case is also extended to an M-player case.

This paper investigates the problem of maximally utilizing the spectrum opportunities in cognitive radio networks with multiple potential channels. In particular, the optimal sensing order problem in multi-channel cognitive medium access control with opportunistic transmissions is studied. It is first shown that, when the potential channels are identical (except for the availability probabilities) and independent, the intuitive sensing order (i.e., descending order of the channel availability probabilities) does not lead to optimality in general. A dynamic programming approach for the search of optimal sensing order is then presented. Finally, for some special cases, it is proved that a simple optimal sensing order does exist.

The design of medium access control protocols for a cognitive user wishing to opportunistically exploit frequency bands within parts of the radio spectrum having multiple bands is considered. In the scenario under consideration, the availability probability of each channel is unknown a priori to the cognitive user. Hence efficient medium access strategies must strike a balance between exploring the availability of channels and exploiting the opportunities identified thus far. Using a sequential design approach, an optimal medium access strategy is derived. To avoid the prohibitive computational complexity of this optimal strategy, a low complexity asymptotically optimal strategy is also developed. The proposed strategy does not require any prior statistical knowledge about the traffic pattern on the different channels.

Localization is essential for wireless sensor networks (WSNs). It is to determine the positions of sensor nodes based on incomplete mutual distance measurements. In this paper, to measure the accuracy of localization algorithms, a ranging error model for time of arrival (TOA) estimation is given, and the Cramer-Rao bound (CRB) for the model is derived. Then an algorithm is proposed to deal with the case where 1) ranging error accumulation exists, and 2) some anchor nodes broadcast inaccurate/wrong location information. Specifically, we first present a ranging error-tolerable topology reconstruction method without knowledge of anchor node locations. Then we propose a method to detect anchor nodes that have inaccurate/wrong position information. Simulations demonstrate the improvement of our algorithm compared to others.

Cognitive radio technique has been recently proposed as a novel approach for improving the utilization of the precious limited radio resources, by letting secondary users access primary users' spectrum if not used. There are two major challenges for cognitive radio: spectrum sensing and hidden terminal problem. In this paper, a novel network structure is proposed to separate the spectrum sensing task from the secondary users. The service providers for the secondary users need to place sensing devices within the primary users' networks. These sensing devices sense the primary users' activity. The sensing devices also decide whether to admit a secondary user's transmission. A low-temperature handshake technique is proposed for communications between the secondary users and the sensing devices. A new cognitive cycle is proposed, and the detailed protocol is constructed. The proposed protocol is analyzed using the theory of Lame curve. The problems of optimally locating a sensing device and minimizing the number of sensing devices under the constraint of the maximal collision probability are studied and solved. A performance upper bound is also derived for a special case. From simulation results, the effectiveness of the proposed scheme is demonstrated.

In wireless ad hoc networks, in addition to the well-known hidden terminal and exposed terminal problems, the location-dependent contention may cause serious unfairness and priority reversal problems. These problems can severely degrade network performance. To the best of our knowledge, so far there is no comprehensive study to fully address all these problems. In this paper, a new busy-tone based medium access control (MAC) scheme supporting voice/data traffic is proposed to address these problems. Via two separated narrow-band busy-tone channels with different carrier sense ranges, the proposed scheme completely resolves the hidden terminal and exposed terminal problems. Furthermore, with the use of transmitter busy-tones in the node backoff procedure, the proposed scheme ensures guaranteed priority access for delay-sensitive voice traffic over data traffic. The priority is also independent of the user locations, thus solving the priority reversal problem. The fairness performance for data traffic in a non-fully-connected environment is also greatly improved (as compared with the popular IEEE 802.11e MAC scheme) without the need for extra information exchanges among the nodes.

Distributed medium access control (MAC) is essential for a wireless network without a central controller. In previous work of the authors, a distributed MAC scheme has been proposed to achieve guaranteed priority and enhanced fairness performance. For a wireless network, the service time distribution at the MAC sub-layer is important for performance analysis (e.g., in terms of packet delay, packet dropping rate, and admission region) at the network layer, because the network layer performance is largely dependent on the high-order time- domain statistics of the service provided by the MAC sub-layer. This paper presents a service time distribution analysis of the previously proposed distributed MAC scheme. Specifically, the respective distributions of the node service time and the system service time are derived. Simulation results verify the accuracy of this analysis.

It is a challenging task for multi-hop wireless networks to support multimedia applications with quality-ofservice (QoS) requirements. This letter presents a joint crosslayer optimization approach, i.e., joint medium access control, routing, and energy distribution. User satisfaction represented by user utility is maximized within the required network lifetime, given the constraints on the total available energy in the network and the minimum user rates. Although the resulting optimization problem is nonlinear and nonconvex, we prove that it is approximately equivalent to a two-step convex problem. Furthermore, we prove that the problem of maximizing network utility within achievable network lifetime is quasiconvex

In this paper, it is shown that it is challenging to evaluate service fairness in multi-hop wireless networks due to intra-flow contention and unequal channel capacity. The conventional fairness criterion in wireline networks in terms of flow rate is not appropriate in the wireless environment. Thus, the channel time in the maximal clique is proposed here as an alternative criterion. Based on this criterion, a new definition of max-min fairness for wireless networks is given. This definition is shown to be general for both wireless and wireline networks. Under certain conditions, it is seen to be equivalent to the proportional fairness definition.

In this paper, based on a cross-layer design prin- ciple, we propose an interference aware distributed medium access control (MAC) scheme for a code-division multiple access (CDMA)-based wireless mesh backbone. Specifically, benefiting from the fixed location of wireless routers, the power allocation is based on the length of the transmission path, so as to ensure some level of fairness in resource allocation among the routers. For call admission and slot/rate allocation, based on the maximum sustainable interference concept, we propose to estimate the interference from the viewpoint of the receiver (rather than the transmitter). Each receiver estimates its experienced interference level for the hypothesis that one or more new calls are admitted. If the interference is not tolerable, the receiver rejects the new call(s). The main advantages of our proposed scheme are the low control message overhead for easy implementation, and the accurate interference estimation. Simulation results are presented to evaluate the performance of our scheme. router. In such a backbone, fine-granularity QoS provisioning is desired or required. Carrier sense multiple access (CSMA)- based random access schemes, the major stream for traditional ad hoc networks, may not be a choice, due to their limited QoS provisioning capability. Thus reservation-based MAC schemes should be more suitable for the wireless mesh backbone. When resources are reserved for each active flow, fine-granularity QoS can be achieved. This paper presents an effective distributed MAC scheme for the wireless mesh backbone, taking into account the unique networking characteristics. Specifically, we consider a wireless mesh backbone based on code-division multiple access (CDMA) technology, and propose a MAC scheme based on the cross-layer design principle. The merits of our proposed scheme are four-fold: 1) it is fully distributed; 2) each link does not need to have the dynamic information of other links in terms of transmission power, tolerable interference, etc., thus requiring a low information exchange overhead and increasing the robustness and scalability of the MAC scheme; 3) accurate interference estimation can be achieved for each receiver; and 4) fine-granularity QoS can be achieved by burst- based resource reservation. If a traffic burst is admitted into the network, it can use the reserved resources until the completion of the burst.

Mobile ad hoc networks are expected to support voice traffic. The requirement for small delay and jitter of voice traffic poses a significant challenge for medium access control (MAC) in such networks. User mobility makes it more complex due to the associated dynamic path attenuation. In this paper, a MAC scheme for mobile ad hoc networks supporting voice traffic is proposed. With the aid of a low-power probe prior to DATA transmissions, resource reservation is achieved in a distributed manner, thus leading to small delay and jitter. The proposed scheme can automatically adapt to dynamic path attenuation in a mobile environment. Simulation results demonstrate the effectiveness of the proposed scheme.

Distributed channel access is essential for a wireless network without a central controller. In our previous research, we have proposed a distributed channel access scheme to achieve guaranteed priority and enhanced fairness performance. To better understand the properties of the scheme, and also for the sake of the network design, it is important to investigate the time domain statistics of the scheme. In this paper, we derive the distributions of node service time and system service time, respectively, for the distributed channel access scheme in the saturated case. Simulation results verify the accuracy of our analysis.

This paper aims at an effective resource management scheme for ultra-wideband (UWB) networks where the inherent spread spectrum supports simultaneous transmissions. In specific, we present a transmission frame structure tailoring to the UWB characteristics, and develop a novel control message exchange procedure. Furthermore, we propose effective admission control and resource allocation algorithms to achieve high efficiency. The resource management scheme can solve the near-sender-blocking problem and alleviate the negative effect of long acquisition time in UWB transmissions. Extensive simulations demonstrate the superior performance of our proposed scheme.

Although the IEEE 802.11e enhanced distributed channel access (EDCA) can differentiate high priority traffic such as real-time voice from low priority traffic such as delay- tolerant data, it can only provide statistical priority, and is characterized by inherent short-term unfairness. In this paper, we propose a new distributed channel access scheme through minor modifications to EDCA. Guaranteed priority is provided to real time voice traffic over data traffic, while a certain service time and short-term fairness enhancement are provided to data traffic. We also present analytical models to calculate the percentage of time to serve voice traffic and the achieved data throughput. Both analysis and simulation demonstrate the effectiveness of our proposed scheme.

In this paper, with a cross-layer design principle, we propose an interference aware distributed resource management scheme for a code-division multiple access (CDMA)-based wireless mesh backbone (consisting of a number of wireless routers at fixed sites). Specifically, benefiting from the fixed location of wireless routers, the power allocation is based on the length of the transmission path, so as to ensure a certain level of fairness among the routers. For a new call arrival, based on the maximum sustainable interference concept, each existing receiver (rather than the potential sender) estimates its experienced interference level under the hypothesis that the new call is admitted. If the interference is not tolerable, the existing receiver rejects the new call by sending a blocking-signal. The main advantages of our proposed scheme are the low control message overhead for easy implementation, and the accurate interference estimation. Simulation results are presented to evaluate the performance of our scheme.

Ultra-wideband (UWB) transmission is an emerging wireless technology, and medium access control (MAC) with quality of service (QoS) provisioning is essential to coordinate the access among competing devices in UWB-based wireless networks. In this paper, we study the exclusive region concept (which was previously proposed) to determine the active set of senders at a time. We find out that, different from the previous work, the exclusive region for a specific link should be a system-level concept, and should depend on system factors such as interference from/to other active links. Based on the findings, two MAC packet scheduling schemes are proposed to exploit the system capacity and, at the same time, to achieve a certain level of fairness in UWB wireless networks. As the long acquisition time in UWB transmission can significantly reduce the system efficiency, the proposed schemes can be modified to alleviate the negative effect of a long acquisition time. Computer simulations demonstrate the effectiveness and efficiency of our proposed schemes

In the interworking between a cellular network and wireless local area networks (WLANs), a two-tier overlaying structure exists in the WLAN-covered areas. Due to the heterogeneous underlying quality-of-service (QoS) support, the admission of traffic in these areas has a significant impact on QoS satisfaction and overall resource utilization, especially when multiple services are considered. In this paper, we analyze the performance of a simple admission strategy, referred to as WLAN-first scheme, in which incoming voice and data service requests always first try to get admission to the WLAN whenever it is available. It is observed that the overall resource utilization can be maximized when the admission regions for voice and data services in a cell and a WLAN are properly configured

Voice over wireless local area network (VoWLAN) is an emerging application taking advantage of the promising voice over Internet Protocol (VoIP) technology and the wide deployment of WLANs all over the world. The real-time nature of voice traffic determines that controlled access rather than random access should be adopted. Further, to fully exploit the capacity of the WLAN supporting voice traffic, it is essential to explore statistical multiplexing and to suppress the large overhead. In this paper, we propose mechanisms to enhance the WLAN with voice quality of service (QoS) provisioning capability when supporting hybrid voice/data traffic. Voice multiplexing is achieved by a polling mechanism in the contention-free period and a deterministic priority access for voice traffic in the contention period. Header overhead for voice traffic is also reduced significantly. Delay-tolerant data traffic is guaranteed an average portion of service time in the long run. A session admission control algorithm is presented to admit voice traffic into the system with QoS guarantee. Analytical and simulation results demonstrate the effectiveness and efficiency of our proposed solutions.

This paper investigates distributed medium access control (MAC) to achieve rate guarantee in pulse-based time- hopping ultra-wideband (UWB) wireless networks, where the inherent spread spectrum supports simultaneous transmissions. In specific, we propose a transmission frame structure for the distributed MAC tailoring to the UWB characteristics, and develop a novel control message exchange procedure. Furthermore, we propose an effective distributed resource allocation algorithm to achieve high efficiency. The proposed distributed MAC can solve thenear-sender-blockingproblemand alleviate the negative effect of long acquisition time in UWB transmissions. Extensive simulations demonstrate the superior performance of the distributed MAC.

In wireless ad hoc networks, in addition to the well-known hidden terminal and exposed terminal problems, the location-dependent contention may cause serious unfairness and priority reversal problems. These problems can severely degrade network performance. In this paper, a new busy- tone based medium access control (MAC) scheme supporting voice/data traffic is proposed to address these problems. Via two separated narrow band busy-tone channels with different carrier sense ranges, the proposed scheme completely resolves the hidden terminal and exposed terminal problems. Furthermore, by extending busy-tones in the transmitter busy-tone channel, the proposed scheme ensures guaranteed priority access for delay-sensitive voice traffic independent of the user locations. The long- term and short-term fairness performance for data traffic in a multi-hop environment is also greatly improved as compared with the popular IEEE 802.11e MAC scheme.

Although the IEEE 802.11e enhanced distributed channel access (EDCA) can differentiate high priority traffic such as real-time voice from low priority traffic such as delay-tolerant data, it can only provide statistical priority, and is characterized by inherent short-term unfairness. In this paper, we propose a new distributed channel access scheme through minor modifications to the EDCA. Guaranteed priority is provided to real-time voice traffic over data traffic, while a certain service time and short-term fairness enhancement are provided to data traffic. We also present analytical models to calculate the percentage of time to serve voice traffic and the achieved data throughput. Both analysis and simulation demonstrate the effectiveness of our proposed scheme.

Call admission control plays an important role in quality of service (QoS) provisioning in the interworking between the cellular network and wireless local area network (WLAN). Within the WLAN coverage, a service request can be admitted into the cellular network or the WLAN. Due to the heterogeneous underlying QoS support of the cellular network and WLANs, the admission of traffic in the WLAN coverage has a significant impact on QoS satisfaction and overall resource utilization, especially when multiple services are considered. A popular admission strategy (referred to as WLAN-first scheme) is to admit the incoming service requests into the WLAN whenever it is available so as to take advantage of the low cost and large bandwidth of the WLAN. In this paper, we investigate the performance of the WLAN-first scheme. It is observed that the overall resource utilization can be maximized when the admission regions for voice and data services in a cell and a WLAN are properly configured.

Voice over wireless local area network (VoWLAN) is an emerging application taking advantage of the promising voice over Internet Protocol (VoIP) technology and the wide deployment of WLANs all over the world. To fully exploit the capacity of WLAN supporting voice traffic, it is essential to explore statistical multiplexing and to suppress the large overhead. In this paper, we propose mechanisms to enhance the WLAN with voice quality of service (QoS) provisioning capability in supporting hybrid voice/data traffic. Voice multiplexing is achieved by a polling mechanism in the contention-free period and a deterministic priority access for voice traffic in the contention period. Header overhead for voice traffic is also reduced significantly. Delaytolerant data traffic is guaranteed an average portion of service time in the long run. A session admission control algorithm is presented to admit voice traffic into the system with QoS guarantee. Analytical and simulation results demonstrate the effectiveness and efficiency of our proposed solutions.

Ultra-wideband (UWB) transmission is an emerging wireless technology, and medium access control (MAC) with quality of service (QoS) provisioning is essential to coordinate the access among competing devices in UWB-based wireless networks. In this paper, we study the exclusive region concept (which was previously proposed) to determine the active set of senders at a time. We find out that, different from the previous work, the exclusive region for a specific link should be a system-level concept, and should depend on system factors such as interference from/to other active links. Based on the findings, two MAC packet scheduling schemes are proposed to exploit the system capacity and, at the same time, to achieve a certain level of fairness in UWB wireless networks. As the long acquisition time in UWB transmission can significantly reduce the system efficiency, the proposed schemes can be modified to alleviate the negative effect of a long acquisition time. Computer simulations demonstrate the effectiveness and efficiency of our proposed schemes

One of the major challenges in supporting multimedia services over Internet protocol (IP)-based code-division multiple-access (CDMA) wireless networks is the quality-of-service (QoS) provisioning with efficient resource utilization. Compared with the circuit-switched voice service in the second-generation CDMA systems (i.e., IS-95), heterogeneous multimedia applications in future IP-based CDMA networks require more complex QoS provisioning and more sophisticated management of the scarce radio resources. This paper provides an overview of the CDMA-related QoS provisioning techniques in the avenues of packet scheduling, power allocation, and network coordination, summarizes state-of-the-art research results, and identifies further research issues.

Ultra-wideband (UWB) transmission is an emerging wireless technology for future short-range indoor and outdoor multimedia applications. To coordinate the access to the wireless medium among the competing devices, the IEEE 802.15.3 medium access control (MAC) is proposed for short-range high-speed wireless personal area networks (WPANs) in the IEEE 802.15.3a task group. In the MAC, three acknowledgment (ACK) mechanisms are adopted during channel time allocation for error control over the error-prone wireless channel: No-ACK, Immediate-ACK (Imm-ACK), and Delayed-ACK (Dly-ACK). Frames received with errors can be retransmitted in the Imm-ACK and Dly-ACK mechanisms. However, how to optimally use these ACK mechanisms during channel time allocation is still an open issue. In this paper, we investigate how to configure the ACK mechanism parameters in order to achieve optimal throughput performance. We first formulate the throughput optimization problem for a contention-free channel time allocation under error channel condition. We then apply the three ACK mechanisms in the contention access period, to optimize the channel throughput. Simulation results demonstrate the effectiveness of our investigation.

A major task in next-generation wireless cellular networks is provisioning of quality of service (QoS) over the bandwidth limited and error-prone wireless link. In this paper, we propose a cross-layer design scheme to provide QoS for voice and data traffic in wireless cellular networks with differentiated services (DiffServ) backbone. The scheme combines the transport layer protocols and link layer resource allocation to both guarantee the QoS requirements in the transport layer and achieve efficient resource utilization in the link layer. Optimal resource allocation problems for voice and data flows are formulated to guarantee pre-specified QoS with minimal required resources. For integrated voice/data traffic in a cell, a hybrid time-division/code-division medium access control (MAC) scheme is presented to achieve efficient multiplexing. Theoretical analysis and simulation results demonstrate the effectiveness of the proposed cross-layer approach.

The next generation wireless networks need to support video traffic. A major challenge in video services over wireless networks is quality of service (QoS) provisioning. Service differentiation is a good approach for QoS provisioning to video traffic. In this paper, we propose cross-layer protocol stack architecture for wireless video transmission with service differentiation. In the cross-layer architecture, the application layer provides the lower link layer with the video compression information. Using the information, a dynamic-weight generalized processor sharing (DWGPS) discipline is proposed for the link layer resource allocation. The link layer tries to provide the application layer with a stringent delay bound and strong protection to high priority traffic in the case of resource shortage. Acceptable level of fairness can be achieved by DWGPS. A scheduling procedure for DWGPS is presented, which avoids complex per-packet virtual time calculation. It is shown that DWGPS can automatically adapt to multiuser diversity without many modifications. Simulation results demonstrate the effectiveness and efficiency of the link-layer DWGPS resource allocation.

Abstract Wireless mesh networking is an emerging technology for future broadband wireless access. The ad hoc manner of wireless mesh networks (WMNs) determines that distributed medium access control (MAC) protocols are desired. Multimedia traffic with heterogeneous quality of service (QoS) requirements is expected to be supported in small‐, medium‐, and large‐scale WMNs. Wireless mesh routers in WMNs are located in fixed sites with low (or no) mobility and no power constraints, thus comprising a robust and reliable wireless mesh backbone. Different networking characteristics between the mesh backbone and various mesh client networks give rise to the demand of heterogeneous MAC design. Due to new design purposes and new networking structures, existing MAC protocols designed for mobile ad hoc networks may not be effective or efficient for multi‐purpose WMNs. This paper provides an overview of distributed MAC protocols based on their underlying design objectives and methodology, discusses their features and suitability for WMNs, and identifies potential challenges and open research issues. Copyright © 2006 John Wiley & Sons, Ltd.

The future IP (Internet protocol)-based code-division multiple access (CDMA) wireless cellular networks require realtime service support. One major challenge in realtime service is quality-of-service (QoS) provisioning over the wireless link. In this paper, we propose two cross-layer resource allocation schemes for voice and video realtime services over IP-based CDMA cellular networks. For voice traffic, the transport layer model and the link layer resource allocation are combined to guarantee the high layer QoS requirements and achieve efficient resource utilization in the low layer. For video traffic, with the aid of video compression information, in-flow service differentiation can be provided to each video sequence. Simulation results demonstrate the effectiveness of our proposed schemes.

The next generation wireless networks need to support video traffic. A major challenge in video services over wireless networks is quality of service (QoS) provisioning. We propose a cross-layer protocol stack architecture for wireless video transmission. In the architecture, the application layer provides the link layer with video compression information. Using this information, a dynamic-weight generalized processor sharing (DWGPS) discipline is proposed for the link layer resource allocation, which is aimed at providing the application layer with strong protection to high priority traffic. The weights in DWGPS are selected based on an optimization problem. Over time-varying wireless channels, a multiuser diversity gain can be achieved without much modification to DWGPS. Simulation results demonstrate the effectiveness and efficiency of DWGPS.

Previous research examining coverage expansion due to soft handoff in code division multiple access (CDMA) cellular networks did not address the relationship between the coverage expansion and the amount of carried traffic in the cell. In this paper, we first present a method to estimate reverse-link multicell coverage using a duration-outage approach. Using this, we then proceed to quantitatively analyze reverse-link coverage expansion from soft handoff as a function of the carried traffic in the cell under different propagation environments. Our results show that for modest values of carried traffic, the coverage expansion is almost constant. However, when the amount of carried traffic is large, the coverage expansion can increase dramatically. Next, we examine the dependence of the soft-handoff coverage expansion on key characteristics of the large-scale shadowing environment. Results are presented that quantify the coverage-expansion dependence on the large-scale shadowing's correlation distance (d/sub c/), variability (/spl sigma//sub Z/), path-loss exponent (K/sub 2/), and the correlation between the two-cell large-scale shadowing environments (C/sub Z/). The results indicate that realistic variations in these propagation conditions have a significant, and sometimes dramatic, effect on the coverage expansion provided by soft handoff. Finally, we analyze the capacity improvement from soft handoff and the tradeoff between capacity improvement versus coverage expansion. Understanding and managing the capacity improvement versus coverage expansion tradeoff is critical for achieving optimal CDMA cell-network performance.

Abstract This paper proposes a distributed multimedia delivery mobile network for video streaming in 3rd generation (3G) mobile communications. The joint design of layered coding (LC) and multiple description coding (MDC) is employed to address the bandwidth fluctuations and packet loss problems in the wireless network and to further enhance the error resilience tools in MPEG‐4. A new Internet protocol (IP) differentiated services (DiffServ) video marking algorithm is presented to support an unequal error protection of the LC components. Both intra‐RAN (radio access network) handoff and inter‐RAN handoff procedures are discussed, which provide path diversity to combat streaming video outage due to handoff in the universal mobile telecommunications system (UMTS). Computer simulation results demonstrate that: (1) the newly proposed IP DiffServ video marking algorithm is more suitable for video streaming in an IP mobile network as compared with the previously proposed algorithm, and (2) the proposed handoff procedures have better performance in terms of handoff latency, end‐to‐end delay and handoff scalability than that in UMTS. Copyright © 2005 John Wiley & Sons, Ltd.

The next generation wireless networks need to support video traffic. A major challenge in video services over wireless networks is quality of service (QoS) provisioning. We propose a cross-layer protocol stack architecture for wireless video transmission. In the cross-layer architecture, the MPEG4 compression layer provides the lower link layer with the video compression information. Using this information, a dynamic-weight generalized processor sharing (DWGPS) discipline is proposed for the link layer resource allocation which tries to provide the video compression layer with an acceptable video quality. The proposed DWGPS can achieve lower computational complexity and smaller signaling overhead than previous packet-based GPS implementations. Simulations demonstrate that DWGPS can improve the received video quality as compared with previous work.

A major challenge in establishing the wireless Internet is provisioning of quality of service (QoS) to different Internet applications. In this paper, we propose a vertically layered scheme to provide QoS for the assured service with a committed information rate (CIR). By controlling the delay and packet loss performance seen from the transport layer, we can achieve the required CIR. Based on the proposed scheme, the resources needed to meet the rate requirement of the assured service can be determined. The resource allocation problem is also formulated as an optimization problem. Numerical results demonstrate that efficient resource utilization can be achieved.

The spatial variability of elevation errors in high-resolution digital elevation models (DEMs) derived from stereo-image processing is examined. Error models are developed and evaluated by examining the correlation between various DEM parameters and the magnitude of the observed DEM vertical error. DEM vertical errors were estimated using a dataset of more than 51000 points of known elevation obtained from a kinematic Global Positioning Satellite (GPS) ground survey. Elevation variability and the quality of the stereo-correlation match over small spatial scales were the dominant factors that determined the magnitude of the DEM error at any given location. The error models are strongly correlated with the magnitude of the DEM vertical error and are shown to adequately represent the full range of the observed error. The error models are used to estimate the magnitude of the vertical error for every point in the DEMs. The models are then used to predict the overall error in the DEMs. The results demonstrate that the error models can accurately quantify and predict the spatial variability of the DEM error.