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In this paper, we extend the interference channel with degraded message sets model by introducing multiple secondaries. The new model allows for multiple concurrent transmissions in a wireless network by employing dirty paper and superposition coding. We apply the proposed scheme to the communication between nodes in a wireless mesh network (WMN). The cases of different WMN topologies are analyzed, and numerical results show that considerable capacity gains are achieved when using the proposed model with multiple secondaries.

With the emergence of in-vehicle applications, providing the required computational capabilities is becoming a crucial problem. This paper proposes a framework named autonomous vehicular edge (AVE) for edge computing on the road, with the aim of increasing the computational capabilities of vehicles in a decentralized manner. By managing the idle computational resources on vehicles and using them efficiently, the proposed AVE framework can provide computation services in dynamic vehicular environments without requiring particular infrastructures to be deployed. Specifically, this paper introduces a workflow to support the autonomous organization of vehicular edges. Efficient job caching is proposed to better schedule jobs based on the information collected on neighboring vehicles, including GPS information. A scheduling algorithm based on ant colony optimization is designed to solve this job assignment problem. Extensive simulations are conducted, and the simulation results demonstrate the superiority of this approach over competing schemes in typical urban and highway scenarios.

Both caching and interference alignment (IA) are promising techniques for next-generation wireless networks. Nevertheless, most of the existing works on cache-enabled IA wireless networks assume that the channel is invariant, which is unrealistic considering the time-varying nature of practical wireless environments. In this paper, we consider realistic time-varying channels. Specifically, the channel is formulated as a finite-state Markov channel (FSMC). The complexity of the system is very high when we consider realistic FSMC models. Therefore, in this paper, we propose a novel deep reinforcement learning approach, which is an advanced reinforcement learning algorithm that uses a deep $Q$ network to approximate the $Q$ value-action function. We use Google TensorFlow to implement deep reinforcement learning in this paper to obtain the optimal IA user selection policy in cache-enabled opportunistic IA wireless networks. Simulation results are presented to show that the performance of cache-enabled opportunistic IA networks in terms of the network's sum rate and energy efficiency can be significantly improved by using the proposed approach.

This paper deals with the secure communication issues of wireless cooperative networks in the presence of multiple friendly but selfish intermediate nodes. On account of the broadcast nature of wireless communications, it is assailable to malicious eavesdropping. To tackle this challenge in the paper, we present a relay and jammer selection strategy that selects the jammer and relay nodes from intermediate nodes to improve the security of the eavesdropping attacks. The jammer is used to broadcast artificial interference noise on the eavesdropper. The relay acts as a traditional relay that retransmits source signal from the source to the intended destination. For achieving the maximum secrecy capacity by the selected nodes, we introduce a power allocation approach of intermediate nodes that is formulated as a Bertrand game based on price competition. We prove that an optimal pricing scheme can maximize the secrecy capacity and achieve the optimal profits for the selfish friendly nodes. Then, a new particle swarm with simulated anneal optimization algorithm is employed to obtain the solution of pricing and node selection. Finally, the simulation results verify our theoretical analysis.

The proposed solutions in the literature for integrating Device-to-Device (D2D) communication in cellular networks require added functionalities and consume valuable network resources, mainly in the discovery process. Unlike existing solutions, this paper mitigates the requirement of additional resources in the LTE-A network. This is achieved by proposing to offload a portion of the discovery traffic and processing of D2D communications that involve vehicular users (drivers and passengers) into Vehicular Ad-hoc Networks (VANETs) by using the inherent knowledge of the Road Side Units (RSUs) about users in their coverage areas. In addition, the paper develops an analytical model to analyze the duration of peer discovery in highway scenarios. The results are validated through simulation experiments using both the Network Simulator NS3 and Matlab. The analytical and numerical results demonstrate the effectiveness of the proposed scheme, and show that a low discovery latency is obtained.

With the ever-growing number of mobile users and the rapid growth of wireless data service requirement, quality of experience (QoE) has emerged as an essential indicator for users, service providers, and operators. Meanwhile, to improve coverage and serve users, a lot of small cell base stations (SBSs) must be installed, and a great amount of energy is consumed. However, as far as is known, there are few works that have studied the combinatorial problem of QoE and energy aware SBS management, which jointly implements power selection, load management (SU allocation), and channel allocation. This paper investigates the problem of QoE and energy aware SBS management, which consists of power selection, load management, and channel allocation. In this paper, we resort to cloud technologies to solve such a complicated combinatorial problem and employ an iterative approach in which two subproblems are alternatively assigned and optimized at each iteration, i.e., 1) transmission power and load joint management and 2) channel allocation. We propose a two-dimensional-action extended weakly acyclic game theoretical scheme to optimize the two subproblems distributedly and iteratively. We define a novel two-dimensional-action pure strategy Nash equilibrium (2D-NE) and prove that at least one 2D-NE exists in the proposed game. With the help of cloud, we propose two kinds of better response algorithms to achieve 2D-NE of the proposed game $G_w$ . Moreover, simulation results show that the proposed approach could achieve a good QoE-energy utility performance and a high QoE energy efficiency.

In cognitive radio (CR) networks, cooperative spectrum sensing is utilized to improve the sensing performance to avoid potential interference to primary users (PUs) and increase spectrum access opportunities for secondary users (SUs). A cooperative spectrum sensing process is divided into three phases: individual sensing/detection, reporting/fusion, and data transmission. In the reporting phase, one or more reporting channels are needed to transmit individual sensing results to a fusion center (FC), and global spectrum sensing results are determined at the FC. The number of required reporting channels depends on the number of spectrum sensors or SUs, which relates to reporting channel efficiency and channel scheduling complexity. That is to say, the reporting channel design can be a challenge, especially when fixed assignment scheduling is used. Therefore, in this paper, we design a reporting channel scheme based on random access protocols, including slotted Aloha and reservation-Aloha. Performance evaluations in terms of PU detection probabilities and false alarm probabilities considering the proposed reporting channels are presented. In addition, the impact of soft/unquantized spectrum sensors or detectors (SUs) and malicious SUs is considered in this paper. Analytical and simulation results illustrate the effectiveness of the proposed reporting channel scheduling methods in improving the cooperative spectrum sensing performance.

In this paper, we consider a heterogenous network in which low-power indoor femtocells are deployed in the coverage area of the existing macrobase station (MBS). This paper proposes a novel coordinated random beamforming and user-scheduling strategy to improve the throughput of users served by the femtocell access point (FAP) while satisfying the quality-of-service (QoS) requirements of users served by both MBS and FAP. The strategy, termed as QoS-aware coordinated scheduling (QACS), requires limited coordination between the MBS and FAP, i.e., only the indexes of the qualified beams are shared. Exact statistical analysis for the ergodic achievable rate of both FAP and MBS with the proposed strategy are presented. Scheduling fairness is also addressed for the proposed QACS.

The ever-increasing demand for mobile Internet and high-data-rate applications poses unique challenging requirements for 5G mobile networks, including spectrum limitations and massive connectivity. Cognitive radio and carrier aggregation (CA) have recently been proposed as promising technologies to overcome these challenges. In this paper, we investigate joint relay selection and optimal power allocation in an underlay cooperative cognitive radio with CA, taking into account the availability of multiple carrier components in two frequency bands, subject to outage probability requirements for primary users (PUs). The secondary user network employs relay selection, where the relay that maximizes the end-to-end sum rate is selected, assuming both decode-and-forward and amplify-and-forward relaying. The resulting optimization problems are optimally solved using convex optimization tools, i.e., dual decomposition and an efficient iterative method, allowing their application in practical implementations. Simulation results illustrate that the proposed configuration exploits the available degrees of freedom efficiently to maximize the SU rate, while meeting the PU average outage probability constraints. 1 1967-2012 IEEE. Manuscript received May 27, 2016; revised October 2, 2016; accepted November 7, 2016. Date of publication December 2, 2016; date of current version July 14, 2017. The work of P. D. Diamantoulakis, G. K. Karagiannidis, and T. Khattab was supported by the NPRP under Grant NPRP 6-1326-2-532 from the Qatar National Research Fund (a member of Qatar Foundation). This work was presented in part at the IEEE Wireless Communications and Networking Conference (WCNC), Doha, Qatar, Apr. 2016. The review of this paper was coordinated by Prof. D. B. da Costa. Scopus

Fourth/Fifth Generation heterogeneous wireless networks (4G/5G HetNets) use or will use small cells (SCs) to extend network coverage and increase spectrum efficiency. However, the standard and technical specifications do not specify how to plan the locations of the SCs within the network. Several papers introduced strategies for planning the locations of SCs in the 4G HetNet architecture. However, SCs placement strategies to support the self-healing functionality of the 4G/5G self organizing networks framework has not been studied in the literature. The placement of SCs in 4G HetNets such that an SC failure will not interrupt service, hence making the network fault tolerant, is an important design and planning problem that is addressed in this paper. We present an integer linear program formulation for planning operators of managed SC locations with fault tolerance. We allow one SC to fail and by using self-healing, a fault-tolerance service is provided at designated fail-over levels (defined in terms of users throughput). We consider the problem of SC location planning by using offloading in both out-band and in-band modes, and an interference model is presented to consider the in-band mode and to address the effect of interference on SCs placement planning. A novel approach to provide a linear interference model by using an expanded state space to get rid of nonlinearity is introduced. We present numerical results that show how our model can be used to plan the positions of SCs. We also incorporate the existence of obstacles in the planning, such as large structures or natural formations, that might happen in real life. To the best of our knowledge, this is the first work that addresses the planning of SC locations in 4G/5G HetNets in a fault-tolerant manner.

In this paper, a new cooperative two-way cognitive relaying scheme is proposed. In this model, a primary user (PU) network consisting of two PU sources communicate with each other via a single amplify-and-forward (AF) relay. In addition, a secondary user (SU) source transmits its data to an SU destination via the same PU relay node. To mitigate the SU interference caused to the PU network, the PU network considers the SU network pairs as two additional relay nodes helping the original PU relay node in improving the PU network performance. As a reward for its cooperation, the PU network allows the SU network to communicate simultaneously via the PU relay node by using the decode-and-forward protocol. The proposed system allows the transmission of four PU symbols and one SU symbol in four/three time slots resulting in a bandwidth efficiency of $1.25/1.67$ based on the cooperative scheme, respectively. Two power allocation optimization problems are formulated: the first problem minimizes the weighted sum of the average symbol error probability of both PU and SU systems, whereas the second problem maximizes the total achievable sum rate of the PU and SU networks. Lagrangian multiplier method is used to find the optimal solutions for both problems under the constraint of maximum allowable power budget. In addition, the paper investigates how the proposed model improves the PU physical layer security performance against a single passive eavesdropper. The results show that the error performance of the proposed relay selection model outperforms the conventional two-way relaying networks with AF protocol. Moreover, findings illustrate that the total achievable sum rate of the proposed relay elimination model is higher than the total achievable rate of the conventional two-way relaying model. From secrecy point of view, the proposed model is shown to achieve a nonzero secrecy rate that improves the PU system security against eavesdropping attacks.

In this paper, we propose a novel distributed cooperative sensing algorithm for connected vehicles. The adaptive energy detection threshold, which is used to decide whether the channel is busy, is optimized in this paper by using a computationally efficient numerical approach. The proposed optimization approach minimizes the probability of an incorrect detection as a function of both the probability of false alarm and the probability of missed detection. By considering both probabilities when computing the probability of incorrect detection, to the best of the authors' knowledge, the proposed approach is novel. During the energy detection process, large-scale fading, multipath fading, Doppler effect, and transmission errors affecting the control messaging process are accounted for in order to provide a practical solution for connected vehicles. Once the available channels have been detected, the vehicles share this information using broadcast control messages. Each vehicle evaluates the available channels by voting on the information received from one-hop neighbors, where the credibility of each neighbor is weighted during the voting process. An interdisciplinary approach referred to as entropy-based weighting is used to define the neighbor, as well as the vehicle's own credibility. The voting mechanism is switched between the proposed voting mechanism and the traditional voting approach obtained from the current state of the art in order to maintain a balance between the computational cost/latency and robust spectrum sensing. Experimental results show that by using the proposed distributed cooperative spectrum sensing mechanism, spectrum detection error converges to zero.

Cellular heterogeneous networks (HetNets), which are realized through shared carrier deployments of macrocells and small cells, are widely seen as a potential solution to serve growing data capacity demands. While these networks pose significant challenges in interference management, much of the focus in earlier efforts has been limited only to small-cell range expansion in the downlink. In this paper, we provide a comprehensive analysis of interference management techniques applicable to the uplink of cellular HetNets, with the goal of characterizing and improving edge user (e.g., 5th percentile) performance. In particular, we propose and study virtual soft-handoff (VSHO), which offers a low-complexity and low-overhead solution that exploits the link asymmetry observed in the uplink geometry of HetNets. VSHO exploits the fact that, in the uplink, an edge macro user who suffers from very low throughput may be closer to a nearby small cell than its own macrocell. The intuition is that such macro users should have better decoding opportunity when their signals are processed at the nearby small cell with better channel conditions. We also study how interference cancelation (IC) and interference avoidance through resource blanking can be incorporated into our VSHO proposal for further throughput gains. In addition to the VSHO techniques outlined in this paper, we also analyze other candidate techniques available in the Third Generation Partnership Project Long-Term Evolution (3GPP-LTE), such as cell-range expansion (CRE) and joint processing, to present a unified view of interference management options available in HetNets.

With the increasing demand of spectrum and emergence of mobile devices, a cloud radio access network (C-RAN) is a promising technology to improve network capacity and coverage. The key concept of the C-RAN is to separate the radio function unit in remote radio heads (RRHs) from the digital function unit in baseband units (BBUs). This separation facilitates efficient spectrum and infrastructure sharing in the C-RAN. This paper considers the cooperative interference management among RRHs in the C-RAN. The RRHs can form coalitions to mitigate intra-interference and jointly serve their subscribers. To characterize RRH performance under the coalition, this paper develops two signal-to-interference-plus-noise-ratio (SINR)-based downlink throughput models of RRH, where one adopts tools from stochastic geometry to capture the interference from vehicular users (VUs) belonging to noncooperative RRHs, and another ignores the VU interference. In this paper, a coalition formation game is formulated to model the situation in which RRHs of C-RAN can make an individual decision to cooperatively serve their VUs if the throughput of the RRH can be improved. To obtain the solution of the proposed game, we develop a distributed coalition formation algorithm and analyze the stability of the coalition structure using a Markov chain model. Simulation results show that, as compared with the noncoalition and grand coalition, our distributed coalition formation can improve the C-RAN throughput by at least 20% and 80%, respectively. Furthermore, according to extensive simulation, we can define the conditions needed for RRHs to form a coalition and obtain higher throughput.

This work considers the problem of reliability and secrecy enhancement for wireless content sharing between a content source node and a content requester. By exploiting the social characteristics of multiple nodes in the presence of multiple independent eavesdroppers, this paper first investigates the impact of mobility for source node selection for transmission reliability, within a cooperative wireless network. Furthermore, trustworthiness and social-tie-based jammer node selections are explored for cooperative jamming to provide secrecy, while allocating power appropriately to the source node and the cooperative jammer node to maximize the worst-case ergodic secrecy rate. Specifically, the source transmitter is selected by first narrowing the potential link set to provide the desired transmission success rate while considering the physical channel and social characteristics jointly. Moreover, the effect of jammer dependability based on its social interactive behavior is also investigated. Instead of focusing on full channel state information (CSI), this paper also investigates the more practical case in which only statistical CSI knowledge is known. Our optimization is based on the upper and lower bounds to the secrecy rate to simplify the power optimization problem without noticeable performance loss. Additional performance analysis for the impact of social characteristics is given. Finally, a one-dimensional search is proposed to further reduce the computational complexity of the power optimization.

The Internet Protocol (IP) Multimedia Subsystem (IMS) is a framework for delivering all-IP-based services. Voice via IMS has been defined as a possible solution from Third-Generation Partnership Project (3GPP) Release 5, prior to long-term evolution (LTE). However, the cost and immediate need for IMS services prevented operators from migration to IMS-based services, particularly with the wide presence of circuit-switched (CS) services offered in Global System for Mobile Communications (GSM) and Universal Mobile Telecommunications System (UMTS) networks. CS fallback (CSFB), which was introduced in 3GPP Release 8, enables the support of voice service without IMS. This is the common deployed scenario for many exiting LTE networks. Voice over LTE (VoLTE) is compulsory to offer rich communication services (RCS) via IMS, in addition to improving the performance of the already deployed CSFB voice solution. However, CSFB and VoLTE are still deployed concurrently, where operators can gradually roll out an LTE/IMS system, while still supporting 2G/3G fallback mechanism. It is, therefore, important to benchmark the performance of both solutions, highlight the deployment challenges, and study the impacts on the end-user experience. This paper provides performance analysis, deployment challenges, and comparisons between these voice solutions. This paper presents practical performance analysis, including end-to-end assessment of call setup delay under different radio conditions, main challenges impacting the in-call performance, as well as performance aspects of Single Radio Voice Call Continuity (SRVCC) and its evolution releases.

This paper investigates collaborative spectrum sharing (CSS) for which a cognitive secondary transmitter acts as a decode-and-forward (DF) relay for two primary users (PUs) occupying an interfering multiple-access channel. PUs are assumed to send their signals simultaneously; hence, interference between the primary signals exists due to the multiple-access nature. The secondary user (SU) selects and forwards one of the PU's signals to a desired destination, and at the same time, the SU also transmits its own signal only if it is not harmful to PUs. The selection of a primary signal to relay is investigated, depending on SU's knowledge of two primary source–destination channels, for which closed-form outage probabilities for PUs and SU are provided accordingly. With the help of the closed-form PU's outage probability, an optimal selection strategy between the primary signals and an optimal power allocation between the primary and secondary signals are also obtained in closed form, which minimizes SU's outage probability while keeping the PU's outage performance at an SU-free level. Numerical investigation is used to verify and illustrate the analysis given in this paper. Numerical results also show that the SU's performance can vary significantly according to the amount of channel knowledge that the SU can have.

In this paper, we address the problem of securing information transmission in very adverse environments, i.e., no eavesdropper channel state information (CSI) and imperfect legitimate channel CSI, by introducing a massive multiple-input–multiple-output (M-MIMO) relay. The relay is powered through wireless power transfer from the source, such that it can flexibly adjust its position according to the secrecy requirement. The benefits of a M-MIMO relay are fully exploited to enhance both power transfer efficiency and information transmission security. In particular, the challenging issues incurred by short interception distance and long transfer distance are well addressed simultaneously. The focus of this paper is on investigating the secrecy performance of two classical relaying protocols, namely amplify-and-forward (AF) and decode-and-forward (DF), and obtaining explicit expressions of secrecy outage capacity in terms of transmit power, channel condition, and antenna number. Furthermore, we propose two effective performance optimization schemes, i.e., power control at the source, and relaying protocol switch at the relay. Finally, our theoretical claims are validated by simulation results.

Traffic offloading among coexisting heterogeneous radio access technologies (RATs), i.e., inter-RAT offloading, is considered to be an effective strategy for enhancing the capacity of wireless networks and reducing the power consumption of both base stations (BSs) and mobile stations (MSs). To fully utilize inter-RAT offloading advantages, a mobility-aware evaluation is needed, which takes into account the combined effects of mobility and MS and BS spatial distributions on the performance gains. This paper proposes a novel analytical model that accurately describes MS mobility dynamics in heterogeneous wireless networks, while conveying detailed information on its location. In addition, this paper derives an analytical expression for calculating the packet loss probability for orthogonal-frequency-division-multiple-access (OFDMA)-based networks. Taking users' mobility and spatial distribution into account, this paper develops a Markovian-based framework for evaluating inter-RAT offloading performance. The accuracy of the proposed mobility model and the efficacy of the proposed performance evaluation framework are validated. Results show that MS mobility and vertical handover (VHO) cost significantly affect inter-RAT offloading performance, and ignoring their effects could lead to an inaccurate evaluation. When the effects of MS mobility and VHO cost on the performance are ignored, utilizing inter-RAT offloading decreases the packet loss probability by 9% and saves energy by 6%. However, accounting for these effects results in a 32% increase in the packet loss probability evaluation and a 64% increase in the energy consumption evaluation.

This paper studies the cooperative device-to-device (D2D) transmissions in cellular networks, where two D2D users communicate bidirectionally with each other and simultaneously serve as relays to assist the two-way transmissions between two cellular users. For this scenario, both cellular and D2D links share the same spectrum, thus creating mutual interference. In addition to that, a security problem also exists since the cellular users want to keep their messages secret from the D2D users and vice versa . To address these two issues, a security-embedded interference avoidance scheme is proposed in this paper. By exploiting the constellation rotation technique, the proposed scheme can create interference-free links for both D2D and cellular communications, thereby significantly improving the system error performance. Moreover, our scheme also provides an inherent secrecy protection at the physical layer, which makes the information exchange between cellular users and that between D2D users confidential from each other.

In this paper, we consider a cooperative simultaneous wireless information and power transfer (SWIPT) network with one source–destination pair and multiple energy harvesting relays. How to efficiently use these relays has been addressed in conventional cooperative networks, and this paper investigates the impact of SWIPT on the performance of such multirelay cooperative networks. In particular, the main contribution of this paper is that a closed-form expression of the outage probability achieved by the multirelay cooperative protocol is obtained, as well as its approximation at high SNR. In addition, the performance of the cooperative network with the SWIPT relays is compared with that in conventional systems with self-powered relays.

There is an ongoing debate in the research and industry communities as to whether IEEE 802.11p or Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) should be used for vehicular communications. In this paper, we argue that a hybrid vehicular network combining both technologies can increase the performance of the system. We first propose a mechanism to improve location-based routing in a hybrid vehicular network architecture by data and signaling traffic separation on independent wireless networks. We then develop analytical models to calculate the stochastic upper bound of the end-to-end delay (E2ED) for location-based routing in three different networking architecture alternatives based on a) short-range ad hoc only, b) cellular only, and c) the proposed hybrid ad hoc/cellular network. The analytical approach in this paper is based on the stochastic network calculus (SNC) theory, which provides a solid and uniform framework for analysis of the upper bound of the E2ED in communication networks. It is demonstrated that the proposed hybrid network provides a lower E2ED compared with the other two alternatives. Comparisons of realistic simulation results, carried out in NS-3, and analytical results show that the proposed delay bounds provide relatively tight approximations for the E2ED in the three alternative architectures for vehicular networks investigated in this paper.

Security and privacy have become increasingly critical demands in wireless networks, which, however, are particularly susceptible to eavesdropping attacks due to the broadcast nature of radio signals. This paper considers the problem of secure communication in the multiuser downlink with a passive eavesdropper (Eve), whose channel state information (CSI) is unavailable. The transmitter simultaneously transmits concurrent information signals to the users and artificial noise (AN) to Eve. We first assume that all users' CSI is perfectly known by the transmitter and derive a closed-form expression for the ergodic secrecy sum rate (SSR) in the large-system limit. We then use it as an objective function to optimize the power allocation between information signals and the AN. It shows that more power needs to be used for AN when Eve has more antennas and when the system serves fewer users. We also extend the analysis to the imperfect-CSI scenario, where the SSR saturates at high transmit power, and it is better to create more AN than to increase the signal strength when the channel estimation error is large. We derive a scale law of feedback bits (for frequency-division duplexing (FDD) systems) to maintain a constant rate offset compared with the perfect-CSI case and the optimal length of training sequence (for time-division duplexing (TDD) systems) to maximize the effective SSR. It shows that more feedback bits and longer training sequences are required to deal with the eavesdropping problem. Closed-form expressions derived in this paper can reduce the complexity of system analysis and design.

In a cellular network, the network coverage is partitioned into nonoverlapping areas called registration areas to facilitate location management (LM) that keeps track of the location of a user equipment (UE) unit. In the second-generation Global System for Mobile Communications (GSM) and the third-generation Universal Mobile Telecommunications System (UMTS), a registration area is called a location area (LA) in the circuit-switched domain or a routing area (RA) in the packet-switched domain. In the fourth-generation Long-Term Evolution (LTE), a registration area is called a tracking area (TA). To tackle the drawbacks of the LA/RA-based LM scheme used in GSM and UMTS, which is intrinsically a static scheme, LTE adopts a dynamic LM scheme called a TA list (TAL)-based scheme. Under the TAL-based scheme, the network allocates to a UE unit a group of TAs referred to as a TAL instead of only a single TA. The UE can move freely within the allocated TAL without performing any location updates that are called TA updates (TAUs) in LTE. Only when moving into a TA that is not included in the allocated TAL does the UE need to perform a TAU, and afterward, the network will allocate, to the UE, a new TAL. The performance of the TAL-based scheme relies on the allocated TAL. If the allocated TAL is inappropriate with respect to the UE's mobility and traffic characteristics, the TAL-based scheme may produce adverse effects. To find an optimal TAL allocation method for global UE units that exhibit weak regularity in their mobility, this paper develops an embedded Markov chain approach to analyze the signaling cost of the TAL-based scheme. This paper distinguishes itself from existing studies in the following aspects. First, this paper follows LTE technical specifications, that is, the number of TAs in a TAL can vary and, furthermore, is upper bounded, whereas existing studies partially or completely ignore this stipulation. Second, this paper emphasizes the impact of a call handling model that dictates whether a TAU occurs after the completion of a call by considering two call handling models, i.e., a call plus location update and a call without location update. Third, as for the dependence among the cell residence time, the TA residence time, and the TAL residence time, this paper proposes the use of a fluid flow model to describe this dependence, which is simple but does not compromise accuracy. Analytical formulas for the total signaling cost of the TAL-based scheme due to TAU and paging operations, as well as formulas that are useful in designing an optimal paging scheme, are derived, and their accuracy is validated through Mont Carlo simulation. Then, numerical studies are carried out to investigate the impact of diverse parameters on the signaling cost, revealing that the network can allocate, to a UE unit, an optimal TAL that is consistent with the UE's mobility and traffic characteristics to minimize the signaling cost of the TAL-based scheme.

In this paper, we focus on enhancing the energy efficiency in open-access femtocell networks where many femto base stations (BSs) are deployed in a large public area such as airports, shopping malls, etc. In those areas, the femtocells are overlapped and underutilized during most of the operation time because femto BSs are densely deployed to support the peak traffic load. Therefore, if we properly coordinate the user association (UA) with BSs and put the femto BSs having no associated users to sleep, the energy consumption can be saved remarkably. In this paper, we propose a scheme that jointly decides the operation modes (e.g., active or sleep) of femto BSs and the association between users and the active BSs to minimize the energy consumption in the network. Simulation results show that the proposed scheme can significantly reduce the total energy consumption in the open-access femtocell networks.

With the unprecedented new capabilities introduced by modern broadband wireless networks, public safety (PS) agencies are increasingly depending on such networks for their mission-critical communications. One of the key enablers for this adoption is the device-to-device (D2D) communications, where mobile devices can connect directly between each other, without the need for a base station (BS) nor a switching core to handle and route the traffic. This feature is a vital communication backup in case of a network infrastructure failure or a natural disaster. In this paper, we analytically quantify the cellular network performance during massive infrastructure failure, where some terminals can play the role of low-power relay nodes forming multihop communication links to assist farther terminals outside the reach of the healthy network coverage. Namely, we analytically determine the D2D effect in alleviating the damage caused by the disaster. This paper is based on stochastic geometry analysis and presents a novel analytical methodology that is applicable to wide scenarios of network conditions and parameters. This methodology is verified through Monte Carlo simulations for practical network parameters based on the latest Third-Generation Partnership Project (3GPP) recommendations.

In cloud radio access networks (C-RANs), the baseband processing of the radio units (RUs) is migrated to remote control units (CUs). This is made possible by a network of backhaul links that connects RUs and CUs and that carries compressed baseband signals. While prior work has focused mostly on single-hop backhaul networks, this paper investigates efficient backhaul compression strategies for the uplink of C-RANs with a general multihop backhaul topology. A baseline multiplex-and-forward (MF) scheme is first studied in which each RU forwards the bit streams received from the connected RUs without any processing. It is observed that this strategy may cause significant performance degradation in the presence of a dense deployment of RUs with a well connected backhaul network. To obviate this problem, a scheme is proposed in which each RU decompresses the received bit streams and performs linear in-network processing of the decompressed signals. For both the MF and the decompress-process-and-recompress (DPR) backhaul schemes, the optimal design is addressed with the aim of maximizing the sum-rate under the backhaul capacity constraints. Recognizing the significant demands of the optimal solution of the DPR scheme in terms of channel state information (CSI) at the RUs, decentralized optimization algorithms are proposed under the assumption of limited CSI at the RUs. Numerical results are provided to compare the performance of the MF and DPR schemes, highlighting the potential advantage of in-network processing and the impact of CSI limitations., A shorter version of the paper has been submitted to ISIT 2014

In this paper, we study an uplink network configuration in a two-tier macro–femto heterogeneous system with hybrid access control. We consider a system where one macro base station (MBS) and a cluster of adjacent femto base stations (FBSs) together serve a number of mobile users. In this system, base stations and users make decisions in various network configuration processes with different optimization objectives. Such decision-making processesz are usually correlated, and an efficient mechanism is needed to coordinate the decision makers. In this paper, we propose a five-stage network configuration mechanism where access control, resource allocation, and power management are sequentially performed at the base stations and users, respectively. We show that this mechanism provides incentive for the FBSs to operate at the hybrid access mode. We model the configuration mechanism as a multistage decision-making process and formulate a multilevel optimization problem. We analyze the problem in a bottom-up manner and propose efficient algorithms to solve the optimization problem in each level sequentially. Simulation results show that the proposed network configuration mechanism achieves a higher system utility than configuration mechanisms with topology-based hybrid access or closed access.

The downlink power allocation in a two-tier cellular network that consists of a macrocell network underlaid by multiple femtocell networks is addressed in this paper. This paper aims to maximize the transmission capacity of the femtocell networks while guaranteeing that the interference experienced at the macro base station does not exceed an interference constraint. We formulate a Bayesian Stackelberg game to model and analyze behaviors of macrocell and femtocell base stations (MBS and FBSs, respectively). In this game, the MBS is the leader, whereas the FBSs are the followers. The channel information between an FBS and its associated femtocell user is private information and is considered the type of the follower. The leader issues the price of interference charged to the followers first to maximize its own profit. Based on the price, the followers decide the strategies to maximize their payoffs defined as the difference between the transmission capacity and the cost of interference (CoI) paid to the leader. Using backward induction, we first analyze the follower game. The existence and uniqueness of the Bayesian Nash equilibrium (BNE) are examined, and the methods to obtain the BNE for a symmetric case are provided. Then, the leader game is analyzed. Finally, the numerical analysis is provided.

Deployment of small cells into existing mobile networks can improve throughput and users' quality of service. However, the new tier composed of small cells raises problems related to management of user mobility. Moving users must be able to discover cells in their neighborhood. For this purpose, the users perform neighborhood scanning. The scanning process should be frequent enough to avoid situations where the user is not aware of a close cell that has not been scanned. However, the frequent scanning of a high number of neighboring cells leads to wasting battery power for the user equipment and reducing the throughput of users. On the contrary, rare scanning can lead to a situation where a small cell is missing in the list of scanned cells, and thus, handover is not performed. This results in underutilization of the small cells and consequent overloading of macrocells. In this paper, we propose an efficient scanning algorithm suitable for future mobile networks. The objective of the proposed scheme is to maximize utilization of the small cells and to minimize energy consumption due to scanning. The proposal exploits graph theory to represent a principle of obstructed paths in combination with knowledge of the previously visited cell and the estimated distance between cells. As the results presented in this paper show, our algorithm reduces energy consumption due to scanning and enables higher exploitation of small cells by offloading macrocells.

A Sensor Equipped Aquatic (SEA) swarm is a sensor cloud that drifts with water currents and enables 4-D (space and time) monitoring of local underwater events such as contaminants, marine life, and intruders. The swarm is escorted on the surface by drifting sonobuoys that collect data from the underwater sensors via acoustic modems and report it in real time via radio to a monitoring center. The goal of this study is to design an efficient anycast routing algorithm for reliable underwater sensor event reporting to any surface sonobuoy. Major challenges are the ocean current and limited resources (bandwidth and energy). In this paper, these challenges are addressed, and HydroCast, which is a hydraulic-pressure-based anycast routing protocol that exploits the measured pressure levels to route data to the surface sonobuoys, is proposed. This paper makes the following contributions: a novel opportunistic routing mechanism to select the subset of forwarders that maximizes the greedy progress yet limits cochannel interference and an efficient underwater dead end recovery method that outperforms the recently proposed approaches. The proposed routing protocols are validated through extensive simulations.

Traffic volume measurement is critical in vehicular networks. Existing research on traffic volume measurement mainly focuses on single-point traffic statistics. In this paper, we switch our view from single-point to multi-point and study the important problem of privacy-preserving multi-point traffic volume measurement in vehicular cyber-physical systems (VCPSs), which complements the state of the art. While embracing automatic traffic data collection, which the VCPS provides through vehicle-to-infrastructure communications, we also need to accept the accompanying challenges: First, the privacy of all participating vehicles should be preserved as an inherent requirement of a VCPS; second, the measurement scheme should be efficient enough to fit today's large-scale vehicular networks. In this paper, we start from a novel scheme that measures traffic volume between two arbitrary points (locations) through variable-length bit array masking. Then, we extend the idea of variable-length bit array masking to address the more challenging problem of three-point traffic measurement and present a general framework to measure traffic among three or more locations. We also perform extensive simulations to demonstrate the superior performance, applicability, and scalability of our schemes.

End users increasingly expect ubiquitous connectivity while on the move. With a variety of wireless access technologies available, we expect to always be connected to the technology that best matches our performance goals and price points. Meanwhile, sophisticated onboard units (OBUs) enable geolocation and complex computation in support of handover. In this paper, we present an overview of vertical handover techniques and propose an algorithm empowered by the IEEE 802.21 standard, which considers the particularities of the vehicular networks (VNs), the surrounding context, the application requirements, the user preferences, and the different available wireless networks [i.e., Wireless Fidelity (Wi-Fi), Worldwide Interoperability for Microwave Access (WiMAX), and Universal Mobile Telecommunications System (UMTS)] to improve users' quality of experience (QoE). Our results demonstrate that our approach, under the considered scenario, is able to meet application requirements while ensuring user preferences are also met., This work was supported in part by the Spanish Ministry of Economy and Competitiveness under Grant TIN2011-27543-C03-01 and Grant BES-2012-052673, by Universitat Politecnica de Valencia through the ABATIS Project (PAID-05-12), and by the Science Foundation Ireland under Grant 10/IN.1/I3007 and Grant 10/CE/I1853. The review of this paper was coordinated by Dr. Y. Ji.

In wireless sensor networks (WSNs), target surveillance has been an important application, particularly in harsh environments. With limited energy of battery-driven sensors, a challenging problem is how to schedule each sensor between active and sleep modes to maximize the network lifetime while meeting surveillance requirements. This problem is often referred to as the wake-up scheduling problem. In this paper, we consider the wake-up scheduling problem for a roadside sensor network that is deployed along a road to monitor the activities on it, such as car accidents, traffic loads and patterns, or enemy activities on battle fields. Previous research has studied a simple case of this problem in which sensors were scheduled so that the entire road could be covered by just one set of active sensors. However, to ensure the reliability of the surveillance tasks, multiple sets of active sensors are often required so that each set can independently cover the entire road. The number of such sets is referred as survivability. This paper studies the wake-up scheduling with survivability $k$ for the road coverage problem. When $k >\mbox{1}$ , the scheduling problem becomes more practical and interesting. We present efficient polynomial algorithms that produce an optimal schedule to satisfy the survivability requirement with the maximum lifetime for both cases $k=\mbox{1}$ and $k >\mbox{1}$ . Theoretical proof for the optimality of our algorithms is given, and simulation results further validate the correctness of our algorithms.

Energy conservation is a central issue in the design of a wireless mesh network powered by solar cells. Since traffic uncertainty is always present, in this paper, we study how to design an energy-conservation routing scheme in face of traffic uncertainty. We present a new approach that is immune from the two problems prevalent in conventional approaches: performance degradation caused by inaccuracy of a simplified interference model and the instability caused by the assumption of unbounded transmission power and data rate. The analytical and simulation results presented in this paper show that the proposed approach can achieve significant performance gains, in terms of throughput and energy consumption, over the conventional approach.

The ease of acquiring hardware-based link quality indicators (LQIs) is an alluring property for fast channel estimation in time- and safety-critical wireless sensor network (WSN) applications, such as closed-loop control and interlocking. The two rudimentary hardware-based channel quality metrics, i.e., received signal strength (RSS) and LQI, are the key constituents of channel estimation and a plethora of other WSN functionalities, from routing to transmit power control. Nevertheless, this paper highlights three deficient aspects of these two indicators: 1) Overall deceptiveness, i.e., the inability to reveal the presence of interference, falsely indicating excellent channel conditions in an unacceptably high fraction of cases; 2) the burstiness of missed detection which compromises the attempts to eliminate the deceptiveness by averaging; and 3) high mutual discrepancy of the two indicators, which is observed in 39%–73% of packets, throughout different scenarios. The ability of RSS and LQI to indicate IEEE 802.11 interference is scrutinized in a variety of scenarios in typical industrial environments using commercial-off-the-shelf hardware and realistic network topologies, giving the findings of this paper high general validity and practical relevance.

Research on the broadcasting of signal countdown messages (SCMs) to vehicles via vehicular ad hoc network (VANET) technology has shown that it can reduce $\hbox{CO}_{2} $ emissions and energy consumption; however, past studies have lacked consideration of car following and vehicle gliding mode. In this paper, two green driving suggestion models, namely, the Maximize Throughput Model (MaxTM) and the Minimize Acceleration and Deceleration Model (MinADM), are proposed to minimize the $\hbox{CO}_{2} $ emissions by considering real-time traffic information nearby the intersection. The two proposed strategies are compared with an open traffic light control model (OTLCM) . The main facts this paper demonstrate are that traffic models lack consideration of car following, which would make the simulation result unrealistic, that the proposed MaxTM can reduce more $\hbox{CO}_{2} $ emissions than the MinADM and the OTLCM, and the total travel time in the MaxTM is also better than the other two models so that the general traffic performance can be improved. Simulation results show that the performance of $\hbox{CO}_{2} $ emissions of the MaxTM is 5%–102% better than the MinADM and 13%–209% better than the OTLCM in the simulation cases, and the performance of $\hbox{CO}_{2} $ emissions of the MaxTM is 8%–14% better than the MinADM and 15%–231% better than the OTLCM in the real traffic cases.

This paper investigates the problem of traffic scheduling between roadside units (RSUs) in a vehicular delay-tolerant network. A source RSU needs the help of passing-by vehicles to forward its traffic to a destination RSU. Costs are associated with energy consumption and information loss. When a vehicle arrives, the source RSU needs to decide whether to stop, i.e., transmit its traffic to the vehicle, or skip this vehicle and continue to wait for other vehicles. The source RSU's objective is to achieve the minimal rate of cost. In this paper, we theoretically derive an optimal stopping strategy of the source RSU. Simulation results are presented to show the effectiveness of the derived strategy.

Being a promising technology for fifth-generation (5G) communication systems, a novel railway communication system based on control/user (C/U) plane split heterogeneous networks can provide a high-quality broadband wireless service for passengers in high-speed railways with higher system capacity, better transmission reliability, and less cochannel interference. However, due to its special architecture where the C-plane and the U-plane must be split and supported by a macro Evolved Node B (eNB) and a phantom eNB, respectively, it would suffer more serious handover problem, particularly in intermacrocell handover, which directly degrades its applicability and availability in high-speed railways. Moreover, no technical specification has been released about this network architecture. Therefore, this paper focuses on redesigning and analyzing technical details and handover procedures based on Long-Term Evolution (LTE) specifications to guarantee the proposed system's practicability and generality and its analytical tractability. To resolve the handover problem, this paper proposes a handover trigger decision scheme based on GM(1, $n$) model of the grey system theory. By this scheme, the received signal quality from the $(N + hbox{1})$th measurement report can be predicted from the $N$th measurement period, and the predicted values can be then utilized to make the handover trigger decision. The simulation results show that the proposed scheme is capable of triggering handover in advance effectively and of enhancing handover success probability remarkably.

In an infrastructure-based wireless network, including mobile users and vehicles, many crucial and important services are provisioned by a centralized server. However, due to damaged infrastructure and increased mobility caused by an emergency, maintaining continuous service coverage in such a network can be challenging. Although several prediction-based replication methods have been proposed to achieve service coverage through replication of the central server, they are unable to accurately predict future topological changes and thus maintain service coverage in a post-emergency network. These topological changes are, in fact, directly related to user mobility. Nevertheless, existing mobility models are unable to realistically represent post-emergency user movements. Consequently, at first, this paper proposes a realistic mobility model that includes users' post-emergency complex behavioral changes. Subsequently, this paper proposes a machine-to-machine (M2M) networking-based service coverage framework for post-emergency environments. The proposed framework performs not only accurate prediction of the proposed user mobility but also optimal replication, utilizing these predictions, of the central server to achieve continuous service coverage. In addition, the framework requires no supervision and fewer resources to perform these functions due to use of the M2M networking. Simulation results are further used to verify the effectiveness of proposals presented in this paper.

A communication-based train control (CBTC) system is an automated train control system using bidirectional train–ground communications to ensure the safe operation of rail vehicles. CBTC systems have stringent requirements for communication availability and latency. Most existing CBTC train–ground communication systems work in the infrastructure mode without train–train communications. Due to unreliable wireless communications and frequent handoffs, existing CBTC systems can severely affect train control performance, train operation efficiency, and the utility of the railway. In this paper, we use recent advances in cooperative relaying to enable train–train communications and, consequently, enhance the train control performance of CBTC systems. Trains act not only as end communication points but as relays for other trains as well. Unlike existing works on cooperative relaying, in this paper, linear quadratic cost for the train control performance in CBTC systems is considered as the performance measure. We jointly consider cooperative relaying and handoff decision issues in CBTC systems. Moreover, to mitigate the impacts of handoff latency on the train control performance, we propose an optimal guidance trajectory calculation scheme in the train control procedure that takes full consideration of the tracking error caused by handoff latency. Simulation results show that the train control performance can be substantially improved in our proposed CBTC system with cooperative relaying.

This paper studies the problem of joint allocation of subchannel, transmission power, and phase duration in relay-enhanced bidirectional multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) networks. The goal of resource allocation is to minimize transmission energy consumption in networks with multiple decode-and-forward relay stations (RSs) under the data rate constraints of user equipment (UE). The challenges of this resource allocation problem arise from the complication of multiple-phase assignments within a subchannel since the RS can provide an additional transmission path from the base station to the UE. Existing research does not fully take into account all of the influential factors to achieve feasible resource allocation for relay-enhanced MIMO-OFDM networks. Green resource allocation (GRA) schemes with reduced computational complexity are proposed in this paper to develop joint allocation of subchannel, power, and phase duration for the UE with the consideration of direct and two-hop communications. Both the separate-downlink (DL)-and-uplink (UL) and mixed-DL-and-UL relaying assignments and the linear block diagonalization (LBD) technique are adopted to obtain the solutions for the proposed GRA schemes. Simulation results show that the proposed GRA schemes can provide comparably better energy conservation with the consideration of quality-of-service (QoS) support.

In this paper, we investigate novel soft mutual information forwarding (MIF) protocols in a two-way relay channel (TWRC), where two sources exchange information with the help of an intermediate relay. Based on the estimated signals from the two sources, the relay calculates the soft mutual information and then broadcasts it to the two sources. In particular, we propose two MIF protocols, namely, network-coded MIF (NC-MIF) and superposition-coded MIF (SC-MIF), which is suitable for different channel conditions. The expressions derived for the received signal-to-noise ratio (SNR) at the receivers reveal that, if both source-to-relay channels are in good condition, the NC-MIF outperforms the SC-MIF. Otherwise, the SC-MIF is superior to the NC-MIF. For the TWRC with varying channels, we further develop an adaptive scheme, which enables the dynamic switch between the two protocols, depending on the received SNR at the sources. Furthermore, the threshold that determines the switch of the protocols is developed as a close-form expression. Simulation results show that our adaptive scheme outperforms other protocols discussed in this paper over fading channels.

Next-generation cellular networks will provide users with better experience employing smaller cells, which results in high dynamics and strong interference. Conventional intercell interference coordination (ICIC) approaches are based on fixed or dynamic frequency reuse, which more or less underutilize frequency resources or reduce network-wide performance. As a result, the benefit brought by ICIC is questionable in practical networks. In this paper, we tackle this problem from the self-organizing network (SON) viewpoint by optimizing fractional frequency reuse (FFR) and adapting to dynamic traffic maps. The approach proposed by this paper formulates this problem as an optimization problem with multiple key performance indicators (Multi-KPIs), and a traffic-based dynamic spectrum management (DSM) algorithm is proposed to reduce the call drop and block ratio (CDBR) and to also improve the network throughput. To reduce further the cost of spectrum partition and assignment, we conduct data mining for the traffic maps from realistic networks and then obtain traffic stable states for a longer specific period of time. DSM based on the stable states (DSM-SS) approach brings further benefits for Long Term Evolution networks in terms of operational costs. Simulation results show that the proposed schemes significantly outperform the traditional schemes.

With macro and micro base stations (BSs) of different transmission and processing capabilities jointly deployed, heterogeneous networks effectively extend the coverage and capacity of wireless networks and have been adopted as one of the key technologies in Fourth-Generation-Long-Term Evolution (4G-LTE). To fully exploit the benefits of heterogeneous networks, proper mobile association, interference management, and radio resource management schemes need to be developed. In this paper, we investigate radio resource allocation for heterogeneous networks with cooperative relays, where the relay nodes (RNs) with in-band backhaul act as micro BSs and are able to serve user equipment (UE) either independently or cooperatively with the BSs. In such a network, radio resource-allocation schemes need to decide for each resource block: 1) whether a UE is served by a BS or an RN, and 2) whether a UE should be cooperatively served or not. In making these decisions, radio resource consumption on RN's in-band backhaul links and fairness among the UEs should be taken into consideration, which further complicates the resource-allocation problem. In this paper, we propose a radio resource-allocation framework and derive a resource-allocation strategy that is asymptotically optimal on the proportional fairness metric. The derived resource-allocation scheme gives insights on the optimal radio resource allocation for the heterogeneous networks with cooperative RNs using in-band backhauls.

This paper considers the problem of network-based mobile-phone positioning when multiple providers are available. This paper proposes two cross-provider localization algorithms via a cooperative approach, which are called linear regression (LR) and locally cooperative embedding (LCE), to efficiently exploit the complementary information from each network provider. The former chooses the provider weights that minimize the mean-square positioning errors. The latter dynamically embeds the cooperation and iteratively refines the positioning process according to each provider's local accuracy surrounding the user. This paper applies the proposed cross-provider positioning algorithms to actual Global System for Mobile Communications (GSM) networks, using a dual-subscriber-identity-module (SIM) mobile phone connecting to multiple providers simultaneously. On-site experiments clearly demonstrated that the proposed cross-provider approaches provide better positioning accuracy than any individual provider, where LCE achieves the best performance.

This paper provides a cross-layer analysis of uplink (UL) performance in femtocell (FC) networks. It characterizes the UL physical interference in FC networks and studies its impact on the delay and the data loss rate of constant-bit-rate (CBR) traffic and on the maximum achievable femto user (FU) throughput. This paper derives data-link layer quality-of-service (QoS) performances as a function of physical layer parameters, thereby establishing key cross-layer relationships that can be useful for designing efficient resource-allocation techniques for FC networks.

WiFi-enabled buses and stops may form the backbone of a metropolitan delay tolerant network, that exploits nearby communications, temporary storage at stops, and predictable bus mobility to deliver non-real time information. This paper studies the problem of how to route data from its source to its destination in order to maximize the delivery probability by a given deadline. We assume to know the bus schedule, but we take into account that randomness, due to road traffic conditions or passengers boarding and alighting, affects bus mobility. In this sense, this paper is one of the first to tackle quasi-deterministic mobility scenarios. We propose a simple stochastic model for bus arrivals at stops, supported by a study of real-life traces collected in a large urban network with 250 bus lines and about 7500 bus-stops. A succinct graph representation of this model allows us to devise an optimal (under our model) single-copy routing algorithm and then extend it to cases where several copies of the same data are permitted. Through an extensive simulation study, we compare the optimal routing algorithm with three other approaches: minimizing the expected traversal time over our graph, maximizing the delivery probability over an infinite time-horizon, and a recently-proposed heuristic based on bus frequencies. We show that, in general, our optimal algorithm outperforms the three, but it essentially reduces to either minimizing the expected traversal time when transmissions are always successful, or maximizing the delivery probability over an infinite time-horizon when transmissions fail frequently. For reliable transmissions and “reasonable” values of deadlines, the multi-copy extension requires only 10 copies to reach almost the performance of costly flooding approaches.; Bus et arrêts avec capacités de transmission WiFi peuvent constituer l'épine dorsale d'un réseau urbain tolérant aux délais, qui exploite les transmissions à courte portée, le stockage temporaire des données aux arrêts, et la mobilité prévisible de bus pour délivrer des informations non en temps réel. Cet article étudie le problème de savoir comment router les données à partir de la source jusqu'à la destination afin de maximiser la probabilité de livraison dans un délai donné. Nous supposons que nous connaissons les horaires de bus, mais nous prenons en compte le caractère aléatoire de la mobilité des bus, dû aux conditions de circulation ou au temps nécessaire pour l'embarquement et le débarquement des passagers. En ce sens, le présent document est l'un des premiers à aborder un scénario de mobilité quasi-déterministe. Nous proposons un modèle stochastique simple pour les arrivées de bus aux arrêts, motivé par une étude des traces réelles recueillies dans un vaste réseau urbain avec 250 lignes de bus et environ 7500 arrêts de bus. Une représentation graphique succincte de ce modèle nous permet de concevoir un algorithme de routage optimal (conformément à notre modèle) utilisant une seule copie des données, puis de l'étendre au cas où plusieurs copies des mêmes données sont permises. Grâce à une vaste étude de simulation, nous comparons l'algorithme de routage optimal avec trois autres approches : minimiser le temps attendu de traversement du graphe, maximiser la probabilité de livraison sur un horizon temporel infini, et un algorithme heuristique récemment proposé basé sur les fréquences de bus. Nous montrons que, en général, notre algorithme optimal surpasse les trois autres, mais il se réduit essentiellement à minimiser le temps de traversement quand les transmissions sont toujours couronnées de succès, ou à maximiser la probabilité de livraison sur un horizon temporel infini lorsque les transmissions échouent fréquemment. Pour les transmissions fiables et des valeurs des délais «raisonnables», l'extension multi-copie nécessite seulement 10 copies pour atteindre quasiment la même performance que celle du flooding, particulièrement coûteux en terme de nombre de transmissions et utilisation de buffers.

Integrating optical and wireless broadband access networks is an important step in achieving fixed mobile convergence in metropolitan areas. In this paper, a promising network architecture by integrating a passive optical network and a wireless cooperative network is investigated, in which intercell cooperative transmission is incorporated. Our goal is to exploit both economic and performance benefits. To achieve a cost-effective deployment and meet long-term performance requirements, this paper addresses the issue of dimensioning and site planning (DSP). We provide a complete formulation to capture the challenges behind network deployment. A number of long-term design subjects are jointly considered in a unified optimization framework, including infrastructure placement, base station user allocation, and resource breakdown assignment. To reduce the computation complexity, the DSP problem is decomposed into two subproblems. An approach is further developed to reformulate the problem into a solvable mixed integer linear program. Moreover, we conduct case studies to validate the formulation, in which performance gains are demonstrated in terms of total infrastructure cost reduction, spectral efficiency improvement, and scalability in capacity enhancement.

Wireless networks in an open environment are exposed to various large region threats, e.g., natural disasters and malicious attacks. Available works with regard to region failures generally adopt a kind of “deterministic” failure models, which failed to reflect some key features of a real region failure. In this paper, we provide a more general “probabilistic” region failure model to capture the key features of a region failure and apply it for the reliability assessment of wireless mesh networks. To facilitate such an assessment, we develop a grid-partition-based scheme to estimate the expected flow capacity degradation from a random region failure. We then establish a theoretical framework to determine a suitable grid partition such that a specified estimation error requirement is satisfied. The grid partition technique is also useful for identifying the vulnerable zones of a network, which can guide network designers to initiate proper network protection against such failures. This paper helps us understand the network reliability under a region failure and facilitates the design and maintenance of future highly survivable wireless networks.