The performance of visible light communication (VLC), as a key technology for next-generation wireless communication networks, can be significantly enhanced in terms of data rate, delay, and fairness, through the integration of optical reconfigurable intelligent surfaces (RISs). This paper introduces a novel channel model for a VLC system incorporating RIS-equipped transmitters, where the RIS is directly integrated with the VLC transmitter. This new design is shown to effectively provide beam steering (BS), enabling the concentration of optical power at desired directions with a typical 9.2dB power gain compared to a scenario without BS capability. To further illustrate the BS capability of the modeled RIS-equipped transmitter, a traffic-aware resource allocation scheme is formulated and efficiently solved using a tailored fractional programming (FP) approach with an affordable computation complexity. This approach allows to jointly optimize user association and power control by decoupling the interference interactions caused by BS. Simulation results reveal that BS-capable VLC through the proposed channel model and optimization scheme, can enhance data rate and fairness considerably while keeping delay within acceptable levels.

Mobile edge computing (MEC) is a promising technology that aims to reduce the total latency of user equipment (UE) by deploying computation resources at the edge of mobile networks. UE mobility is a challenging factor that causes the traditional MEC architecture to suffer from several issues, such as decreased efficiency and frequent service interruptions. One popular method to manage UE mobility is virtual machine (VM) migration, which requires high bandwidth and causes undesirable latency, rendering it impractical for real-time tasks with stringent latency requirements. This paper proposes a hierarchical architecture for MEC networks that facilitates mobility management and mitigates the need for VM migration. In order to utilize this architecture efficiently, a Markov chain-based predictive strategy is introduced to predict UE mobility. Afterward, an optimization problem is formulated to make the optimal long-term offloading decisions for UEs such that their expected cost is minimized subject to latency commitments and resource consumption constraints. Simulation results demonstrate that the proposed scheme reduces the cost of high-mobility UEs by up to 25% compared to traditional schemes. Furthermore, the measures of movement direction predictability and offloading decision popularity are introduced that provide insights into the behavior of the proposed and counterpart schemes.

Dynamic index coding is a practical generalization of conventional index coding that deals with real dynamic traffic streams. We identify the code-constrained capacity region of a dynamic index coding problem with a complete bi-directional side information graph and introduce the performance metric of dynamic index coding gain to measure how dynamic index coding reduces the required data transmissions. A greedy dynamic index coding scheme is proposed that achieves the maximum coding gain almost everywhere in the identified capacity region. Although the greedy scheme attains the maximum coding gain, its selfish nature may unacceptably increase transmission delay. To address this issue, a time-shared friendly dynamic index coding scheme is introduced that achieves the maximum coding gain over the entire capacity region and offers a lower delay than its greedy counterpart. To obtain the minimum delay, a constrained optimization problem is formulated to tune time-sharing weights in the friendly scheme. The closed-form solution of the optimization is derived for the special two-flow case. Furthermore, the results and analysis are extended to dynamic index coding problems with arbitrary side information graphs. We also use analytical and simulation results to provide graphical intuition for the obtained results.

Dynamic reconfigurability in optical and mobile networks can facilitate heterogeneous service provisioning while utilizing minimal resources. This allows cost-efficient service delivery resulting in high revenues for network operators. Deployment of elastic mobile and optical networks is a key driver for enabling reconfigurability in modern networks. Elastic optical networks can be exploited as the fronthaul portion of new generation of mobile networks. Such elastic optical fronthaul networks facilitate joint reconfiguration of flexible radio and optical elements and provide considerable performance improvements. In this paper, we focus on the joint dynamic selection of functional splits and configuration of optical transponders and illustrate that designing a converged network with optical and radio elements improves network power efficiency. A time-averaged stochastic optimization problem is formulated and its solution is derived using a modified version of the Lyapunov drift technique. Simulation results demonstrate that the proposed scheme can reduce the average power consumption by up to 70% compared to a cloud radio access network with a traditional optical fronthaul. Further, the results show that the modified Lyapunov technique can afford stringent fronthaul delays below 250$\mu \text{s}$. We also discuss how future technology upgrades such as increasing the number of radio antenna ports and decreasing the granularity of fiber spectrum grid may influence the results.

Slicing allows 5G networks to accommodate services with different needs over a unified physical network infrastructure. Particularly, in radio access networks (RANs), the baseband processing functions of different slices are treated as virtual applications running on shared compute nodes. Managing this cloud-native network in a cost-effective way requires tightly cou-pled control of connectivity and processing resources. This paper proposes an optimization problem to minimize the overall cost while guaranteeing distinct latency and reliability requirements of different network slices deployed over the infrastructure. This is achieved by choosing for each service, the functional split and transmission parameters that best adapt to the connectivity and processing resources available in the infrastructure. Results demonstrate that the proposed flexible resource allocation scheme provides considerable cost saving (up to 2.4 times) and reduced request blocking (up to 2 times) compared to conventional fixed deployment techniques. The reliability requirements can be guaranteed by packet duplication and/or virtualized forward error correction at the expense of consuming connectivity and/or processing resources, respectively. The flexible assurance of the reliability requirements in the proposed scheme contributes considerably to the achieved improvements on cost saving and request blocking.

In a wirelessly-powered communication network (WPCN), an energy access point (E-AP) supplies the energy needs of the network nodes through radio frequency wave transmission, and the nodes store their received energy in their batteries for possible data transmission. In this paper, we propose an online control policy for energy transfer from the E-AP to the wireless nodes and for data transfer among the nodes. With our proposed control policy, all data queues of the nodes are stable, while the average energy consumption of the network is shown to be within a bounded gap of the minimum energy required for stabilizing the network. Our proposed policy is designed using a quadratic Lyapunov function to capture the limitations on the energy consumption of the nodes imposed by their battery levels. We show that under the proposed control policy, the backlog level in the data queues and the stored energy level in the batteries fluctuate in small intervals around some constant levels. Consequently, by imposing a negligible average data drop rate, the data buffer size and the battery capacity of the nodes can be significantly reduced.

In this paper, we propose efficient wireless power transfer (WPT) policies for various practical scenarios in wirelessly powered communication networks (WPCNs). First, we consider WPT from an energy access point (E-AP) to multiple energy receivers (E-Rs). We formulate the problem of maximizing the total average received power of the E-Rs subject to power constraints of the E-AP, which is a non-convex stochastic optimization problem. Using eigenvalue decomposition techniques, we derive a closed-form expression for the optimal policy, which requires the distribution of the channel state information (CSI) in the network. We then propose a near-optimal policy that does not require this knowledge and prove that its optimality gap can be decreased at the cost of increment in its convergence time. Next, we consider fairness among the E-Rs and propose a quality of service (QoS) aware fair policy that provides fairness and guarantees the required QoS of each E-R. Finally, we study a WPCN where the E-Rs utilize their received energy to transmit information to the E-AP. We maximize a generic fair network utility under the E-Rs' QoS constraints and the E-AP's power constraints. Numerical results show a significant improvement of O(log N) in the total throughput compared to the state-of-theart baselines.

In this paper, we study the secrecy throughput in a massive Multiple-Input-Multiple-Output (MIMO) full-duplex wireless powered communication network (WPCN). The network consists of a massive MIMO base station (BS) and two groups of single-antenna sensor nodes which harvest energy from the BS. The first group, referred to as information transmitters (ITs), use the harvested energy to transmit information back to the BS; the second group, referred to as energy receivers (ERs), use the harvested energy for non-transmission related operations. We consider a two-slot protocol. In the first time slot, all nodes harvest energy from the BS. In the second slot, ITs transmit information to the BS, while BS use one set of its antennas to receive the signals and the other set of antennas to transmit artificial noise (AN) to the ERs. The AN serves two purposes: wireless power transfer to the ERs, and information security for the ITs with ERs, which are considered as potential eavesdroppers. We aim to maximize the total secrecy throughput of ITs subject to the ERs' received energy constraints. The problem is shown to be non-convex. To tackle the problem, we propose a twostage suboptimal approach, referred to as Maximizing Received AN aided Secrecy Throughput Maximization (MRAN-STM). In the first stage, the transmitted AN is optimized to maximize the minimum received AN of all the ERs. Then, in the second stage, the power allocation and time slot duration are optimized to maximize the total secrecy throughput. Numerical results show the improvement of the proposed algorithm.

In a wireless powered communication network, an energy access point (EAP) supplies the energy needs of the network nodes through radio frequency wave transmission, and the nodes store the received energy in their batteries for their future data transmission. In this paper, we propose an online stochastic policy that jointly controls energy transmission from the EAP to the nodes and data transfer among the nodes. Our proposed policy is designed using a quadratic Lyapunov function to capture the limitations on the energy consumption of the nodes imposed by their battery level. The proposed policy is adaptive to different channel statistics of the network. We provide theoretical analysis for the performance of the proposed policy and show that it stabilizes the network. Moreover, the average energy consumption of the network under this policy is within a bounded gap of the minimum energy level required for stabilizing the network.

In this paper, we investigate the secrecy throughput for a full-duplex wireless powered communication network. A multi-antenna base station (BS) transmits energy towards nodes all the time and each node harvests energy prior to its transmission time slot. Nodes sequentially transmit their confidential information to the BS in presence of other nodes which are considered as potential eavesdroppers. We derive the secrecy rate and formulate the sum secrecy throughput optimization of all nodes. The optimization variables are the time slot duration and the BS beamforming during different transmission phases. The problem is non-convex and non-trivial. We propose a suboptimal approach in which the BS focuses its beamforming to blind the potential eavesdroppers (other nodes) during the information transmission phase, with which we then obtain the optimum beamforming in each time slot and its duration. We compare our algorithm with uniform time slot and uniform beamforming in different settings and demonstrate its superior performance.

In this paper, we study the secrecy throughput of a full-duplex wireless powered communication network (WPCN) for Internet of Things (IoT). The WPCN consists of a full-duplex multiantenna base station (BS) and a number of sensor nodes. The BS transmits energy all the time, and each node harvests energy prior to its transmission time slot. The nodes sequentially transmit their confidential information to the BS, and the other nodes are considered as potential eavesdroppers. We first aim to optimize the sum secrecy throughput of the nodes. The optimization variables are the duration of the time slots and the BS beamforming vectors in different time slots. The optimization problem is shown to be nonconvex. To tackle the problem, we propose a suboptimal two stage approach, referred to as sum secrecy throughput maximization (SSTM). In the first stage, the BS focuses its beamforming to blind the potential eavesdroppers (other nodes) during information transmission time slots. Then, the optimal beamforming vector in the initial noninformation transmission time slot and the optimal time slots are derived. We then consider secrecy throughput fairness among the nodes and propose max-min fair (MMF) and proportional fair (PF) algorithms. The MMF algorithm maximizes the minimum secrecy throughput of the nodes, while the PF achieves a good tradeoff between the sum secrecy throughput and fairness among the nodes. Through the numerical simulations, we first demonstrate the superior performance of the SSTM to uniform time slotting and beamforming in different settings. Then, we show the effectiveness of MMF and PF algorithms.

Radio frequency wireless power transfer (RF- WPT) is an emerging technology that enables transferring energy from a power source to wireless devices over the air. In this paper, we aim at finding {the optimal policy for wireless power transfer (WPT) from an energy access point} (E-AP) to multiple energy receivers (E-Rs) that maximizes the wireless power transfer efficiency. For this purpose, in the first part of the paper, we formulate the problem of maximizing the total average received power of the E-Rs subject to the average and peak power constraints of the E-AP. The formulated problem is a non-convex stochastic optimization problem, and is highly non-trivial. Using some stochastic optimization techniques, we tackle the aforementioned challenges to solve the problem and derive a closed-form expression for the optimal solution, which requires the CSI distribution. In addition, we propose a heuristic algorithm that does not require any explicit information on the CSI distribution. We prove that the proposed algorithm attains a near-optimal solution within a guaranteed gap to the optimal solution. In the second part of the paper, we focus on the problem of considering fairness among the E-Rs and propose two fair policies, namely Max- Min Fair (MMF) policy and Quality-of-service- aware Proportional Fair (QPF) policy. MMF policy maximizes the minimum received power among the E-Rs. Moreover, QPF policy balances the received power levels of different E-Rs as much as possible, while guaranteeing the required minimum QoS for each of them. Various numerical results demonstrate the significant performance of the proposed solutions.

Radio frequency wireless power transfer (RF-WPT) is an emerging technology that enables transferring energy from an energy access point (E-AP) to multiple energy receivers (E-Rs), in a wireless manner. In this paper, we focus on the problem of WPT from a battery-operated E-AP to multiple E-Rs. To save the battery life of the E-AP and at the same time, provide the required quality of service (QoS) for the E-Rs, we aim at finding a proper power transfer policy that minimizes the average transmitted power of the E-AP while providing the required received power of each E-R. We formulate this problem with a stochastic optimisation problem, which is non-convex and has no closed-form expression for the objective function. First, we focus on the special case of single E-R, and derived a closed-form expression for the optimal solution which requires the CSI distribution. Next, for the general case of multiple E-Rs, we propose a Min Drift Plus Penalty (MDPP) algorithm which does not require any information on the CSI distribution. We prove that the proposed algorithm attains a near-optimal solution within a guaranteed gap to the optimal solution. Numerical results demonstrate the significant performance of the proposed solutions.

Providing backhaul connectivity for macro and pico base stations (BSs) constitutes a significant share of infrastructure costs in future heterogeneous networks (HetNets). To address this issue, the emerging idea of flexible backhaul is proposed. Under this architecture, not all the pico BSs are connected to the backhaul, resulting in a significant reduction in the infrastructure costs. In this regard, pico BSs without backhaul connectivity need to communicate with their nearby BSs in order to have indirect accessibility to the backhaul. This makes the radio resource management (RRM) in such networks more complex and challenging. In this paper, we address the problem of cross-layer RRM in HetNets with flexible backhaul. We formulate this problem as a two-timescale non-convex stochastic optimization, which jointly optimizes flow control, routing, interference mitigation, and link scheduling in order to maximize a generic network utility. By exploiting a hidden convexity of this non-convex problem, we propose an iterative algorithm which converges to the global optimal solution. The proposed algorithm benefits from low complexity and low signaling, which makes it scalable. Moreover, due to the proposed two-timescale design, it is robust to the backhaul signaling latency as well. Simulation results demonstrate the significant performance gain of the proposed solution over various baselines.

In this paper, we consider the problem of cross-layer radio resource management in heterogeneous networks (HetNets) with flexible backhaul, which aims at minimizing the total transmit power of base stations (BSs) while guaranteeing the average end-to-end data rate requirement of each data flow. We formulate the problem as a two-time scale stochastic optimisation, where the long-timescale control variables are flow control, routing control and interference coordination, while the short-timescale control variable is instantaneous beamforming within each cell. Using a stochastic cutting plane (SCP) method, we propose a cross-layer queue-state information (QSI) aware radio resource management (RRM) solution in which the long-term controls are updated centrally at radio resource management server (RRMS) without needing to know the global statistical information of the network, and the short-term control variables are updated locally at each BS with only the local instantaneous QSI and channel-state information (CSI) available at each cell. Simulation results show the significant performance gain of our proposed algorithm compared to various baselines.

In this paper, we focus on the problem of hierarchical cross-layer dynamic resource allocation for heterogeneous networks with flexible backhaul. We formulate the radio resource management problem as a two timescale non-convex stochastic optimisation problem which jointly optimizes flow control, routing control, interference mitigation and link scheduling in order to maximize a generic network utility. We propose an iterative hierarchical control structure where the long-term controls are adaptive to large scale fading and the short-term control is adaptive to the local CSI within a pico or macro BS, to find the optimal solution. The proposed solution benefits from low complexity and requires low signalling and message passing among different nodes, which makes it scalable. Moreover, due to the proposed two-timescale hierarchical design, it is robust to the backhaul signalling latency as well. Simulation results demonstrate the significant performance gain of the proposed solution over various baselines.

Device-to-Device communication (D2D) integrated in cellular networks emerges as a new trend in response to notable rise in traffic demand. Resource allocation is one of the important challenges in deployment of D2D networks. In this paper, we formulate an optimization problem for optimal resource allocation and then propose a novel algorithm namely maximum clique based resource allocation (MCRA) for improving the spectral reuse based on graph theoretic concept of maximum clique. Practical application of D2D communications requires each node to receive and transmit signals during the communication process. We have considered this issue in constructing the interference graph and mathematical formulations in our system model. We have proposed an efficient algorithm called binary code-based maximum clique detector (BCMD) to find the maximum clique solution with reduced complexity in interference graphs. Finally, to mitigate the overall interference and complexity of the problem, a two level resource allocation algorithm (TLRA) is suggested. The results demonstrate that substantial gains are achieved in terms of sum rate, time and computational complexity compared to the existing approaches in literature.

One of the main advantages of utilizing flexible backhaul in future HetNets is that it can provide better user experience through flexible resource allocation. For this purpose, it is important to provide the required quality of service (QoS) in such networks. In this paper, we consider the problem of cross-layer radio resource management in HetNets with flexible backhaul which guarantees minimum total transmit power of BSs as well as the average end-to-end data rate requirement of each data flow. The problem is formulated as a two-timescale stochastic optimisation, where the long-timescale control variables are flow control, routing control and interference mitigation, while the short-timescale control variable is instantaneous beamforming within each cell. Using stochastic cutting plane, we propose an online cross-layer hierarchical algorithm in which the long-term controls are updated centrally at radio resource management server (RRMS) without needing to know the global statistical information of the network, and the short-term control variables are updated locally at each BS with only the local instantaneous CSI available at each cell. The proposed algorithm has low complexity and signalling overhead. Moreover, simulation results show the significant gains of our proposed algorithm over various baselines.

Wireless Sensor Networks (WSNs) have been weaved into the fabric of our daily lives. The foremost impediment in the rapid development of these networks is the energy limitation which inhibits them from meeting specific application requirements. Recently, the advances in energy harvesting technology have made it possible to replenish the energy of sensors via external sources. Energy Harvesting-Wireless Sensor Networks (EH-WSNs) are being transformed from a visionary concept into reality. However, this concept is still in its infancy and calls for extensive research to cater to the needs of WSNs. For future progress of EH-WSNs, Medium Access Control (MAC) layer has undoubtedly a decisive role to play. A well-designed MAC protocol can manage the channel access in such a way that the harvested energy is utilized efficiently and the performance is maximized. Due to the importance of medium access control in EH-WSNs, in this paper, we concentrate on the design aspects of MAC protocols for energy harvesting sensor networks. We introduce the characteristics of a properly-designed MAC protocol for EH-WSNs and provide a survey on MAC protocols which have been explicitly designed for energy harvesting sensor networks. We elaborate the advantages and disadvantages of each protocol, wishing to help future designers to learn from the merits and demerits of the existing ideas and propose a more robust solution which can be seamlessly integrated into WSNs.

In order to respond to drastically increased traffic demands in mobile networks such as cellulars, opportunistic communication has been introduced as a data offloading strategy. Delivering the contents using peer-to-peer data dissemination is more preferable compared to epidemic diffusion schemes. To implement peer-to-peer dissemination, one needs to define the peer selection and content dissemination policies. Efficient content dissemination relies on the selection of suitable peers. Besides that, the peers require to choose what contents to be transmitted between them. In this paper, we propose multi-level master/slave peer selection algorithm (MMSA) and variance-based multi-metric chunk selection algorithm (VMMA) which ensure efficient content dissemination with reduced signaling overhead. VMMA can use the local and global features of the contents to prioritize the contents. A mathematical analysis that considers the time varying nature of the network and traces the evolution of distribution process is provided. The simulation results demonstrate the advantages provided by these algorithms. The simulation results match the mathematical analysis.

Energy-aware routing is a promising technique for reducing energy consumption in future networks. Under this scheme, traffic loads are aggregated over a subset of the network links, allowing other links to be turned off to save energy. Since the capacity of links is the main limiting constraint in this problem, to further improve energy saving, the idea of using redundancy elimination (RE) in energy-aware routing has been proposed. As performing RE in routers consumes some energy, it should be specified, which routers should perform RE and which links should be deactivated so that the total energy consumption of the network is minimized. As a result, the problem of energy-aware routing with redundancy elimination, which is known to be NP-hard, arises. In this paper, we first model the problem as a mixed integer linear program (MILP). Since this problem is NP-hard, we propose an efficient heuristic solution. For this purpose, we apply Lagrangian relaxation to the problem and then prove that the obtained formulation is totally unimodular. Under this property, we can relax the integer variables to efficiently determine the solution in polynomial time. Simulation results show the advantages of our proposed heuristic solution over previous ones in terms of approximately twice the energy saving, as well as a lower number of active RE-routers. Furthermore, we show that our method can be applied to the generic energy-aware routing problem (i.e., without RE) as well.

There has been an increasing demand for interactive video transmission over the Internet for applications such as video conferencing, video calls, and telepresence applications. These applications are increasingly moving towards providing High Definition (HD) video quality to users. A key challenge in these applications is to preserve the quality of video when it is transported over best-effort networks that do not guarantee lossless transport of video packets. In such conditions, it is important to protect the transmitted video by using intelligent and adaptive protection schemes. Applications such as HD video conferencing require live interaction among participants, which limits the overall delay the system can tolerate. Therefore, the protection scheme should add little or no extra delay to video transport. We propose a novel Adaptive Loss Protection (ALP) scheme for interactive HD video applications such as video conferencing and video chats. This scheme adds negligible delay to the transmission process and is shown to achieve better quality than other schemes in lossy networks. The proposed ALP scheme adaptively applies four different protection modes to cope with the dynamic network conditions, which results in high video quality in all network conditions. Our ALP scheme consists of four protection modes ; each of these modes utilizes a protection method . Two of the modes rely on the state-of-the-art protection methods, and we propose a new Integrated Loss Protection (ILP) method for the other two modes. In the ILP method we integrate three factors for distributing the protection among packets. These three factors are error propagation, region of interest and header information. In order to decide when to switch between the protection modes, a new metric is proposed based on the effectiveness of each mode in performing protection, rather than just considering network statistics such as packet loss rate. Results show that by using this metric not only the overall quality will be improved but also the variance of quality will decrease. One of the main advantages of the proposed ALP scheme is that it does not increase the bit rate overhead in poor network conditions. Our results show a significant gain in video quality, up to 3dB PSNR improvement is achieved using our scheme, compared to protecting all packets equally with the same amount of overhead.

In this work, first, a Region of Interest (ROI)-based Unequal Loss Protection (ULP) scheme with no delay is proposed for High Definition (HD) interactive video applications such as video calls. The proposed scheme uses Data Partitioning and Flexible Macro block Ordering (FMO) tools of H.264/AVC and reduces error propagation. The obtained data demonstrates that this scheme achieves better ROI quality than others in high Packet Loss Rates (PLR). Second, it is also shown that the efficient scheme for protecting ROI-based interactive video applications in wide PLR ranges is switching both the Forward Error Correction (FEC) distribution pattern and the codec configuration between various scenarios depending on network conditions. This is shown by using both PSNR and SSIM metrics for quality measurement.

In this study, the authors optimise the outage probability of amplify and forward incremental relaying (IR) scheme using two different power allocation methods in the presence of channel estimation errors. The authors find the outage probability of IR scheme and minimise it subject to traditional power (TP) constraint in which the sum of nodes' powers is fixed and outage-dependent power (ODP) constraint which is compatible with the physical concept of IR and takes into account the quality of the direct path in the optimisation problem. The authors provide closed-form expressions to allocate power to pilot and data symbols of both the source and the relay. Although, their analysis uses high signal-to-noise-ratio (SNR) approximation, the analytical solutions perform very close to optimal ones obtained through global numerical search. The authors show that ODP constraint has substantial superiority over TP constraint, especially when the relay is placed close to the source. Moreover, the authors compare power-optimised IR subject to the mentioned power constraints with equal power allocation scheme and show the impact of power optimisation on the outage performance of IR system.

Performance of routing is severely degraded when misbehaving nodes drop packets instead of properly forwarding them. In this paper, we propose a Game-Theoretic Adaptive Multipath Routing (GTAMR) protocol to detect and punish selfish or malicious nodes which try to drop information packets in routing phase and defend against collaborative attacks in which nodes try to disrupt communication or save their power. Our proposed algorithm outranks previous schemes because it is resilient against attacks in which more than one node coordinate their misbehavior and can be used in networks which wireless nodes use directional antennas. We then propose a game theoretic strategy, ERTFT, for nodes to promote cooperation. In comparison with other proposed TFT-like strategies, ours is resilient to systematic errors in detection of selfish nodes and does not lead to unending death spirals.

Security techniques have been designed to obtain certain objectives. One of the most important objectives all security mechanisms try to achieve is the availability, which insures that network services are available to various entities in the network when required. But there has not been any certain parameter to measure this objective in network. In this paper we consider availability as a security parameter in ad-hoc networks. However this parameter can be used in other networks as well. We also present the connectivity coefficient of nodes in a network which shows how important is a node in a network and how much damage is caused if a certain node is compromised.

One of the most challenging problems in Opportunistic Spectrum Access (OSA) is to design channel sensing-based protocol in multi secondary users (SUs) network. Quality of Service (QoS) requirements for SUs have significant implications on this protocol design. In this paper, we propose a new method to find joint policies for SUs which not only tries to guarantee QoS requirements but also maximize network throughput. We use Decentralized Partially Observable Markov Decision Process (Dec-POMDP) to formulate interactions between SUs. Meanwhile, a tractable approach for Dec-POMDP is utilized to extract sub-optimum joint policies for large horizons. Among these policies, the QoS-aware joint policy is selected as the joint sensing strategy for SUs. To show the efficiency of the proposed method, we consider two SUs trying to access two-channel primary users (PUs) network modeled by discrete Markov chains. Simulations demonstrate two interesting findings: 1- Optimum joint policies for large horizons can be obtained using the proposed method. 2- Our method outperforms other related works in terms of network throughput.

This paper studies the statistical properties of the signal-to-noise ratio (SNR) of the dual-hop relaying link in a cooperative wireless communication system in the presence of channel estimation errors for fixed-gain (FG) and variable-gain (VG) relays. The SNR expression is derived and three different analytical approaches with different simplifying assumptions are proposed to obtain the probability distribution function of the SNR and the outage probability in each mode. All but one approach result in closed-form expressions for the outage probability. The simplest approach in each mode has been used to find an optimum power allocation scheme for pilot and data symbols transmission at the source and the relay that results in minimizing the outage probability. Numerical analysis is used to confirm the accuracy of the derived theory and to show that the analytical approaches have a good outage performance, especially as the relay-destination distance increases. It is shown that significant power savings (e.g. 6 dB in VG mode) can be obtained by using the proposed power optimization method.

Cooperative communication exploits wireless broadcast advantage to confront the severe fading effect on wireless communications. Proper allocation of power can play an important role in the performance of cooperative communication. In this paper, we propose a distributed game-theoretical method for power allocation in bidirectional cooperative communication networks. In this work, we consider two nodes as data sources who want to cooperate in sending data to the destination. In addition to being data source, each source node has to relay the other's data. We answer the question: How much power each node contributes for relaying other node's data? We use Stackelberg game which is an extensive-form game to find a solution to this problem. The proposed method reaches equilibrium in only one stage. It is shown that there are more benefits when bidirectional cooperation is done between node pairs who are closer to each other. Simulation results show that the proposed method leads to fair solution and the nodes farther to the destination should contribute more power to cooperate with others.

Wireless infrared optical code-division multiple access (W-OCDMA) is a new developing technique with many useful applications. Noting the limitation on power consumption and eye-safety requirements, wireless optical systems are power limited. Therefore control and efficient use of optical power is a key issue in analysis and design of these systems. Also, multi-user interference is the major source of impairment in these systems and power control is required to control and reduce this interference. Power control and the inevitable errors in its algorithms play an important role in design and implementation of these systems. In this article the authors study the uplink performance of W-OCDMA networks employing on–off keying (OOK) and binary pulse position modulation (BPPM) schemes without any power control algorithm. The performance improvement as a result of using perfect power control is calculated. Then, the impact of imperfect power control that is the result of channel estimation error is analysed. The results clearly illustrate that deploying a proper and accurate power control algorithm can increase network capacity and reduce network average power consumption. The authors show that systems with non-ideal power control still perform considerably better than no-power controlled systems.

Although flooding and its variants are widely deployed for broadcasting by different applications, there are limited results on a complete and comprehensive analytical framework describing their behavior in general cases. We have previously published results which provide an upper bound for the performance of flooding when flooded packets have the highest serving priority. In this paper, using a different and simpler approach, we develop an analytical framework for analysis of flooding in general cases where flooding packets do not receive any special priority treatment in the network. The analysis is performed for a static multi-hop ad hoc wireless network using CSMA as its MAC layer. The framework provides an upper bound on the network coverage and energy consumption of flooding and its popular variant, probabilistic flooding for any service time and queuing delay that flooded packets experience. The analytical upper bound is verified by extensive simulations which give evidence of its tightness in real scenarios.

Counter-based broadcasting improves the performance of flooding by preventing the network from being swamped by a large number of rebroadcast messages. In such approach, the rebroadcast decision is made based on counting duplicated packets in order to restrict the number of extra retransmissions. In this article, using a rigorous theoretic analysis, an upper bound on the performance of counter-based broadcasting for saturated networks is derived. Our model assumes a CSMA-based static multi-hop ad-hoc network. The derived analytical model can be used to predict the behavior of counter-based broadcasting schemes. It especially provides the required insight on the impact of different network parameters on the overall system performance. Simulation results are also provided to validate the proposed models and demonstrate the tightness of the achieved upper bound.

In this paper we propose and analyze the application of generalized optical orthogonal codes (GOOC) in the optical wireless local area networks (OWLAN). A system deploying GOOC can support more users and achieve better BER performance. We evaluate the system performance of GOOC noting practical constraints of OWLAN applications. We consider average and peak power limitations of free space infrared sources, arising from eye safety and device non-linearity restriction. We include the impact of various noises including background-light induced noise in system evaluation. Proper system design requires appropriate selection of GOOC code parameters. We analyze the influence of code parameters on key system variables such as BER, required bandwidth and power consumption. Using the results, we provide guidelines for proper selection of key GOOC code parameters for OWLAN applications.

In this paper, we propose a novel algorithm for rate allocation in multiple-source media streaming peer to peer networks. Our algorithm is based on ant-colony optimization and capable of handling network changes which occur quite often in unstructured P2P networks. The suggested algorithm does not need any information about the topology of the network. Moreover, it could get over uncertainties in network state information, particularly the rate of media provider nodes that could happen due to lack of accurate measurements. We show that our algorithm will reach the maximum achievable rate of the network quite fast and with relatively little overhead. In our simulations, we have demonstrated that in cases where network state information is inaccurate, the suggested ant-based rate allocation method will lead to the same results that other optimization-based rate allocation algorithms yield. Moreover, we have shown that the proposed algorithm has an intrinsic low pass filter which discriminate between transient network changes from permanent ones. If the changes in the network is transient, the algorithm compensate the temporary losses quite fast and without much effort. In cases where the network changes last longer, the algorithm overcomes losses by employing other nodes that have the media stream available. The rate of adaptation is adjustable and must be carefully determined according to network conditions.

In this paper, we present a novel algorithm for partner selection and power allocation in the amplify-and-forward cooperative diversity that minimizes the required total transmit power by given outage probability constraint. We represent the problem with new formulation and solve the optimal power allocation by KKT method for a fixed set of partners. For optimal partner selection, we use a novel algorithm with low complexity to find the best set with minimum required power. We present simulation results to demonstrate that the outcomes of the proposed algorithm are very close to results of full search for optimal set.

Flooding and its variants are the simplest and most widely used broadcasting methods. Therefore, analysis of its performance in an ad-hoc environment using realistic assumptions is an important research topic. In this article, deploying a rigorous theoretic analysis, an upper bound on the performance of probabilistic flooding running over CSMA as a real and suitable MAC layer protocol for broadcasting scenarios is derived in a static multi-hop ad-hoc network in saturated condition. This model reveals the relation between network parameters and the performance of flooding and thus, helps the designer to have a better understanding of the effect of different design parameters. Using this model, an upper bound on total network coverage and energy consumed to achieve this coverage level can be determined. Simulation results are also brought to validate the derived upper bound model, and give evidence of its tightness in real scenarios.

Although collaborative distributed simulations and virtual environments (VE) have been an active area of research in the past few years, they have recently gained even more attention due to the emergence of online gaming, emergency simulation and planning systems, and disaster management applications. Such environments combine graphics, haptics, animations and networking to create interactive multimodal worlds that allows participants to collaborate in realtime. Massively Multiplayer Online Gaming (MMOG), perhaps the most widely deployed practical application of distributed virtual environments, allows players to act together concurrently in a virtual world over the Internet. IP Multicasting would be an optimal solution for the dissemination of updates among participants, but IP multicasting is not available to home users on the Internet, due to a number of technological, practical, and business reasons. In light of the lack availability of IP Multicasting on the global Internet, researchers have recently tended to shift multicasting from the networking layer to the application layer, known as Application Layer Multicasting, effectively constructing an overlay network among participants of the distributed simulation where end hosts themselves participate in the dissemination of update messages. In this paper, we propose a topology control architecture to support P2P based collaborative distributed simulations over the Internet by using AIM. We present our networking model and its rationale, theoretical proof, and simulation measurements in comparison with other methods as proof of concept.

Resilient packet ring (RPR) that has been standardized as IEEE 802.17 is a MAC layer protocol designed for data centric metropolitan area network applications. A well-designed RPR network would be able to offer QoS guarantee for throughput and delay sensitive data classes in addition to providing other types of low cost best effort services. Careful network planning would be required to allow successful provisioning of classA services with strict delay and jitter requirements over RPR networks. This would require the knowledge of the dependency of delay and jitter for classA traffic on the load that is added to the ring. In this article, we propose an algorithm to estimate the dependency of delay and jitter for classA traffic in RPR networks on the total traffic added to the ring by nodes. We will follow an analytical approach based on queuing theory to find the probability density function of the delay for classA packets and try to find a closed-form solution to the problem using some simplifying assumptions. Simulations are used to verify the results of analytical derivations.

In a SEnsor Network with Mobile Agents (SENMA) is an architecture proposed for large scale sensor networks. In sensor networks, a fraction of the packets generated by only part of the sensors is sufficient to provide a good estimation of all network information. SENMA uses this inherent redundancy. However, the performance of such system is limited by estimation errors and packet errors due to collision. Estimation error is a major problem in applications such as habitat monitoring in which information is a function of node position. In this paper, we first derive the equations of distortion in a general scenario and use this model to compare the estimation error for regular networks. Then by obtaining four best node positions for estimation error reduction, minmax distortion for estimation in a square area is achieved. In addition, an opportunistic MAC is proposed that considers both collision effects and estimation error based on Channel State Information (CSI). As the simulation results show the proposed scheme achieves an optimum estimation with minimum collision and energy consumption.

We study the uplink performance of wireless infrared code-division multiple access (CDMA) networks using OOK with optical orthogonal codes (OOC's). The analysis is performed in two cases assuming a cellular network architecture, in which all users are uniformly distributed in the cell's area. The first case is when all users transmit with the same power and no power control mechanism is used. Then, the system that deploys power control mechanism is analyzed and the performance improvements are demonstrated. The impact of imperfect power control which is caused by errors in channel estimation is also analyzed and the analytical and numerical results for all cases are included. The results clearly demonstrate the advantages of using power control algorithms for indoor infrared wireless systems that use OOC modulation techniques

Adaptive modulation with the goal of minimizing the average transmit power is investigated. This is the dual problem of the well-known problem of maximizing the average spectral efficiency. This is desirable in power limited systems such as mobile and sensor networks. Two main cases are considered: adapting only transmit power and adapting only rate. Appropriate expressions for rate or power control policies are derived for different cases. For rate adaptation, we consider both continuous and discrete rate policies. Then, we will apply these methods to a special case of M-QAM modulation over Rayleigh fading channel. We will show that by using rate or power adaptation schemes, between 7 dB and 18 dB power gain can be saved over nonadaptive methods for typical values of spectral efficiency

In recent years, cooperative diversity techniques have gained increased attention as a new way to combat degrading effects of fading. Cooperation among two or more single antenna users generates a virtual diverse multiple-antenna transmission system in the wireless network. In this paper, we investigate the application of adaptive modulation concept to the performance of cooperative techniques. We consider the adaptation of rate and power allocation with M-QAM modulation, and study the performance of amplify & forward scenarios in Rayleigh fading channels. We compare these systems with their comparable adaptive non-cooperative scenario and evaluate the energy saving achieved through cooperation

Most of the energy efficient routing algorithms proposed for sensor networks are reactive routing algorithms. By definition, reactive algorithms are those in which routes are constructed whenever there is data transmission. In such algorithms, to transmit data packets from a certain transmitter to the corresponding receiver, efficient route is constructed using RREQ delivery. This delivery is performed via flooding and modified flooding algorithms. One of the most important criteria of such flooding algorithm is not to miss the best final route during RREQ delivery. Most of major algorithms ignored this fact and instead tried to minimize energy consumption during flooding algorithm. But constructing an energy efficient final route is more important than minimizing energy consumption during RREQ delivery especially for static networks. In this paper, first analytical expressions for expected transmission time in exponential backoff system are derived. Afterwards using the mentioned analytical expressions, an efficient RREQ delivery flooding strategy is proposed to improve the optimality of the final route. The proposed algorithm concommited with our previous power control algorithm results in an efficient routing algorithm with improvement in all parameters from state of the art routing algorithms for sensor networks. Simulation results corroborate the claim

In this paper a combination of routing and power management within the context of wireless ad-hoc sensor networks is considered. Using lower layer information (e.g. collision that is considered in MAC layer) is another novel concern which is used in routing decisions. More specifically in this paper we introduce a cross-layer design in which each node dynamically chooses the number of its neighbors and adjusts its power just enough to reach its farthest determined neighbor. In this algorithm the power of transmission and collision are used as metrics for routing and the number of neighbors in which the total energy consumption in data transmission will be the minimum is selected.

Flooding algorithm is one of the most significant algorithms used in sensor networks. Although simple, this algorithm causes a large amount of energy and bandwidth to be wasted. The most important application of flooding is RREQ flooding in initial step of most routing algorithms. Although simple, this algorithm causes a large amount of energy and bandwidth to be wasted. Most previous efficient flooding algorithms use location information, which is impossible for simple node in sensor network. Some others are not suitable for RREQ flooding due to eliminating redundant retransmissions. We present a modified flooding that simultaneously decreases energy consumption as well as network delay. This flooding algorithm is a form of cross layer algorithm which uses physical layer information to be more efficient in time and energy. It is shown that the proposed algorithm can save a significant amount of energy while reducing the settling time delay

Adaptive transmission is an effective way to improve the performance of communication links in time-varying channel environments. Former works use this technique to maximize the throughput; but we exploit it to minimize BER in a system with diversity reception. We do so by adapting power in response to the channel variations. We use analytical methods to derive our results. These expressions can be used for any type of channel fading and any modulation scheme. We then apply this method to a special case of 4-QAM over Rayleigh channel with MRC reception.

A set of measurements for indoor infrared channel are reported. These measurements have been performed to investigate the effects of rotation on the parameters of the indoor infrared channel. A large database containing more than 5000 frequency responses has been created. The measurements have been performed in rooms with different shapes and physical properties to address all kinds of operating environments. This paper addresses parts of the results obtained from these measurements. The channel path loss and its delay spread are two important channel parameters for indoor infrared channel. The effects of receiver rotation on these two parameters have been studied. It is shown that the delay spread of the channel and its path loss are linearly correlated on the log scale when the receiver is rotated. The correlation between these two variables in different rooms and also different transceiver configurations remains an almost constant value close to unity. Therefore, we conclude that in general, when the receiver rotates, the logarithm of the delay spread of the channel changes linearly with the log of the channel path loss.

The indoor infrared channel is modeled as a linear baseband channel. The parameters of this channel are used for the design of communication systems using infrared light as the carrier of information for indoor wireless communications. For many applications, we need to know the spatial distribution of channel parameters such as the received optical power and the delay spread. The simulation process that yields those results is a very time consuming process. We propose using the simulation software to train a neural network using a fraction of the required points and then use the neural network to generate the desired parameters. The results presented show the excellent capability of the neural networks to mimic the simulation software for the purpose of generating the desired set of parameters for an indoor infrared channel. The process is much faster than the simulation software and proper use of sampling set selection yields highly accurate results from the neural network.

There has been a growing interest in using infrared light for broadband indoor wireless communications. There are two major limitations for establishing a wideband infrared communications link. The first and most important limit is the power requirements of such a link. The second important impairment is the intersymbol interference caused by multipath dispersion. We address the issue of designing an optimized transmission system to provide the best power efficiency for an infrared link. Important parameters that should be considered for this design and some examples of efficient link designs are discussed. The suggested designs can improve the power efficiency of an indoor infrared link up to 4 to 8 dBo while providing a smaller RMS delay spread, more robustness to shadowing and more uniform distribution of power.