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This paper studies the secure transmission in a multiuser broadcast channel where only the statistical channel state information of the eavesdropper is available. We propose to apply secret dirty-paper coding (S-DPC) in this scenario to support the secure transmission of one user and the normal (unclassified) transmission of the other users. By adopting the S-DPC and encoding the secret message in the first place, all the information-bearing signals of the normal transmission are treated as noise by potential eavesdroppers and thus provide secrecy for the secure transmission. In this way, the proposed approach exploits the intrinsic secrecy of multiuser broadcasting and can serve as an energy-efficient alternative to the traditional artificial noise (AN) scheme. To evaluate the secrecy performance of this approach and compare it with the AN scheme, we propose two S-DPC-based secure transmission schemes for maximizing the secrecy rate under constraints on the secrecy outage probability (SOP) and the normal transmission rates. The first scheme directly optimizes the covariance matrices of the transmit signals, and a novel approximation of the intractable SOP constraint is derived to facilitate the optimization. The second scheme combines zero-forcing dirty-paper coding and AN, and the optimization involves only power allocation. We establish efficient numerical algorithms to solve the optimization problems for both schemes. Theoretical and simulation results confirm that, in addition to supporting the normal transmission, the achievable secrecy rates of the proposed schemes can be close to that of the traditional AN scheme, which supports only the secure transmission of one user.

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.

Rail transportation, especially, high-speed rails (HSR), is an important infrastructure for the development of national economy and the promotion of passenger experience. Due to the large bandwidth, millimeter wave (mmWave) communication is regarded as a promising technology to meet the demand of high data rates. However, since mmWave communication has the characteristic of high attenuation, mobile relay (MR) is considered in this paper. Also, full-duplex (FD) communications have been proposed to improve the spectral efficiency. However, because of the high speed, as well as the problem of penetration loss, passengers on the train have a poor quality of service. Consequently, an effective user association scheme for HSR in mmWave band is necessary. In this paper, we investigate the user association optimization problem in mmWave mobilerelay systems where the MRs operate in the FD mode. To maximize the system capacity, we propose a cooperative user association approach based on coalition formation game, and develop a coalition formation algorithm to solve the challenging NP-hard problem. We also prove the convergence and Nashstable property of the proposed algorithm. Extensive simulations are done to show the system performance of the proposed scheme under various network settings. It is demonstrated that the proposed distributed low complexity scheme achieves a nearoptimal performance and outperforms two baseline schemes in terms of average system throughput., Comment: 11 pages, 11 figures

The sensitivity to blockages is a key challenge for the high-frequency (5G millimeter wave and 6G sub-terahertz) wireless networks. Since these networks mainly rely on line-of-sight (LOS) links, sudden link blockages highly threaten the reliability of the networks. Further, when the LOS link is blocked, the network typically needs to hand off the user to another LOS basestation, which may incur critical time latency, especially if a search over a large codebook of narrow beams is needed. A promising way to tackle the reliability and latency challenges lies in enabling proaction in wireless networks. Proaction basically allows the network to anticipate blockages, especially dynamic blockages, and initiate user hand-off beforehand. This paper presents a complete machine learning framework for enabling proaction in wireless networks relying on visual data captured, for example, by RGB cameras deployed at the base stations. In particular, the paper proposes a vision-aided wireless communication solution that utilizes bimodal machine learning to perform proactive blockage prediction and user hand-off. The bedrock of this solution is a deep learning algorithm that learns from visual and wireless data how to predict incoming blockages. The predictions of this algorithm are used by the wireless network to proactively initiate hand-off decisions and avoid any unnecessary latency. The algorithm is developed on a vision-wireless dataset generated using the ViWi data-generation framework. Experimental results on two basestations with different cameras indicate that the algorithm is capable of accurately detecting incoming blockages more than $\sim 90\%$ of the time. Such blockage prediction ability is directly reflected in the accuracy of proactive hand-off, which also approaches $87\%$. This highlights a promising direction for enabling high reliability and low latency in future wireless networks., Comment: Submitted to IEEE, 30 pages, 11 figures. The dataset will be available soon on the ViWi website https://viwi-dataset.net/

As one of the three main application scenarios of 5 G cellular system, massive Machine-Type Communications (mMTC) has been regarded as the key solution to facilitate the IoT paradigm. One major bottleneck for accommodating mMTC is the severe congestion at the cellular random access channel when plenty of Machine-Type Devices (MTDs) send access requests concurrently while the preamble resources are limited. To remedy this issue, limiting the number of retransmissions and dropping access requests after the limit is reached can be an effective approach. Yet, the effect of the preamble retransmission limit $K$ on the optimal access performance of mMTC in cellular networks remains largely unexploited, which motivates the study in this paper. Specifically, in this paper, we start by characterizing the network steady-state points based on the limiting probability of successful transmission of access requests. We then obtain explicit expressions of the access throughput and the mean access delay of successfully-transmitted access requests as functions of $K$ and the number of preambles $M$ . The maximum access throughput and the corresponding optimal backoff window size are further derived. It is shown that the maximum access throughput is independent of $K$ , while the mean access delay can be significantly reduced with a small $K$ , yet, at the expense of increased request dropping ratio. In addition, to improve both the throughput and delay performance, the analysis shows that more preambles should be allocated but the performance gain becomes marginal when $M$ is large. Therewith, an algorithm is proposed for determining the least number of preambles $M^\ast$ that maximizes the access throughput and the preamble resource utilization ratio. Numerical results show that a smaller preamble retransmission limit $K$ can further reduce $M^\ast$ .

Recently, numerous electronic components are installed in vehicles, providing drivers and passengers with increased safety and convenience. The electronic components construct an in-vehicle network that internally shares relevant status information about the vehicle. As modern vehicles become more computerized, the potential for automotive cyber-security threats also increases a fact that has been illustrated clearly by various car-hacking demonstrations. Using the controller area network (CAN), the de facto standard protocol in the automotive industry that facilitates in-vehicle network communication, car-hacking demonstrations inject critical CAN messages to control vehicular functions. In efforts to address this security issue, car manufacturers, in turn, have made confidential the CAN database (i.e., DBC format file), where signal information assigned in the CAN data payload is specified. However, it has since become known that this policy does not hermetically seal a vehicular network against cyber attacks. On the contrary, in-depth automotive security research has been hindered significantly because of the limited information accessible by researchers. For example, automotive intrusion detection systems (IDS) identify and alert when there is a vehicular break-in, and this technology is a major area of study in automotive cyber security research. For the automotive IDS that analyzes CAN traffic, information in the DBC format file greatly improves detection veracity. However, most IDS technologies to date have been independently developed without the confidential CAN DB information and, as a result, do not mitigate threats to a satisfactory standard. In this paper, we propose an enhanced method that identifies signal boundaries in a CAN data payload, which is specified in the DBC format file. Unlike an existing method that is designed based on total bit-flip rates, our method analyzes bit-flip time series not total bit-flip rates so that signal boundaries can be more clearly identified. In this paper, we use a publicly available DBC format file called OpenDBC as a reference, and show that our method outperforms the existing method.

In this paper, we propose a multi-channel medium access control (MMAC) protocol for the exploitation of retro-directive array antennas in Flying Ad Hoc Networks (named FA-MMAC). This FA-MMAC employs multiple channels and retro-directive array antennas to adjacent unmanned aerial vehicles (UAVs) to transmit simultaneously over the same channel without causing interference. The channel utilization characteristic of FA-MMAC increases the spatial reuse of channel and thus improve the system performance. The key idea is that UAVs first exchange control packets in control window to select data channels and to align beams before exchanging data packets in the data window. In this way, the hidden-terminal and deafness problems are reduced. UAVs can reserve channels and align beams through a circular directional transmission of control frames so that the protocol can take advantage of the benefits of retro-directive array antennas of spatial reuse and increased coverage without prior knowledge of the locations. We develop both antenna model and channel model for FA-MMAC protocol. Analysis and simulation results show that our proposed FA-MMAC can offer a significant performance gain for both static and mobile scenarios than the existing MMAC and 802.11-based protocols. Our findings reported in this paper provide some insights into the performance of multi-channel Flying Ad Hoc Networks which might help network researchers to contribute in the development of next generation UAVs.

This paper addresses the congestion problem in cellular networks through the assistance of parcel delivery drones. Drones have the primary task of parcel delivery and a secondary task of acting as relay nodes (hop) to add extra capacity in a cellular network. Base transceiver stations in the cells can admit ground user equipment to communicate directly with the drone (device-to-device communications) through in-band signalling between them. This paper proposes a novel algorithm, called CARLO, which optimizes trajectory and altitude of the drones in order to deliver physical parcels, maximize network capacity and reduce network interference. Our simulation studies show that our solution improves the network throughput while the energy inefficiency of taking detour path to assist congested cells is kept to a minimum. Moreover, it is guaranteed that parcels are delivered before deadline.

In this paper, we investigate a hybrid multicast/unicast scheme for a multiple-input single-output cache-aided non-orthogonal multiple access (NOMA) vehicular scenario in the face of rapidly fluctuating vehicular wireless channels. Considering a more practical situation, imperfect channel state information is taking into account. In this paper, we formulate an optimization problem to maximize the unicast sum rate under the constraints of the peak power, the peak backhaul, the minimum unicast rate, and the maximum multicast outage probability. To solve the formulated non-convex problem, a lower bound relaxation method is proposed, which enables a division of the original problem into two convex sub-problems. Computer simulations show that the proposed caching-aided NOMA is superior to the orthogonal multiple access counterpart.

The technical challenges, e.g. the mobility management and the offloading process, hinder the conventional cellular systems to meet the huge data traffic requirements of the next generation mobile communications. The traditional system (e.g dual-connectivity (DC)) has been proposed to improve the mobility management, however, it will inherit the big trade-off in the offloading process between the energy consumption for the small cell (SC) discovery (SCD) process and the efficiency of utilizing the system resources (e.g. frequency and signaling). In this paper, we present a framework to model the potential offloading opportunities as well as the offloading loss when a typical user equipment (UE) performs the inter-frequency (IRF) scan periodically. The proposed framework also studies the impact of the SCD on the energy efficiency. To improve the system performance and reduce the power consumption at the UEs, a new scheme, trio-connectivity (TC), is proposed in this paper to tackle the aforementioned challenges. The TC includes three planes: control-plane (C-plane), user-plane (U-plane) and indication-plane (I-plane). The I-plane works as an indicator to help the UE to identify and discover the SCs in the system prior to offloading. The role of the I-plane is to keep the SCD on one frequency channel regardless of the number of frequency channels in the system. In the proposed offloading mechanism, some of the energy consumption is transferred from the UE to the network. By using the proposed framework, UE energy efficiency and system energy efficiency as well as the total energy consumption are derived as performance metrics to compare between the TC and the DC. The results show that the TC can outperform the DC in dense cellular systems.

In this paper, we investigate device-to-device (D2D) communication networks which are one of the key technologies for next-generation mobile communication networks and many other applications such as unmanned aerial vehicles (UAVs), vehicle-to-vehicle (V2V), and Internet of things (IoT). The overlay D2D communication networks that are considered in our study use dedicated radio resources separate from what cellular networks use and there exists co-channel interference in D2D networks without cross-channel interference between two networks. We propose a new transmission scheme for overlay D2D networks that uses a dueling deep reinforcement learning (DRL) architecture. The DRL is especially effective in environments where actions do not affect subsequent states as in wireless communication networks. The main contribution of this paper is that the proposed architecture is designed to utilize only information that each D2D devices can easily obtain by measuring channels. The proposed scheme thus enables D2D devices to train their own neural networks and to decide autonomously whether to transmit data without any intervention from infrastructures. The performance of the proposed scheme is analyzed in terms of average sum-rates and is compared to three baseline schemes. Simulation results show that the proposed scheme can achieve almost optimal sum-rates with low signal-to-noise (SNR) values without any intervention from infrastructure.

This paper studies the uplink (UL) transmission of a generalized cell-free massive multiple-input multiple-output (massive MIMO) system in which multiple base stations (or access points), each equipped with a multiple-antenna array and connected to a central processing unit (CPU) over a backhaul network, simultaneously serve multiple users in a cell-free service area. The paper focuses on the non-orthogonal multiple access (NOMA) approach for sharing pilot sequences among users. Unlike the conventional cell-free massive MIMO-NOMA systems in which the UL signals from different access points are equally combined over the backhaul network, this paper first develops an optimal backhaul combining (OBC) method to maximize the UL signal-to-interference-plus-noise ratio (SINR). It is shown that, by using OBC, the correlated interference can be effectively mitigated if the number of users assigned to each pilot sequence is less than or equal to the number of base stations (BSs). As a result, the cell-free massive MIMO-NOMA system with OBC can enjoy unlimited performance when the number of antennas at each BS tends to infinity. A closed-form SINR expression is derived under Rayleigh fading and used to formulate a max-min quality-of-service (QoS) power control problem to further enhance the system performance. To deal with the NP-hardness of the concerned optimization problem, a successive inner approximation technique is applied to convert the original problem into a series of convex optimizations, which can be solved iteratively. In addition, a user grouping algorithm is also developed and shown to be better than random user grouping and a grouping method recently proposed in the literature. Numerical results are presented to corroborate the analysis and demonstrate the superiority of the proposed optimal backhaul combining over both equal-gain backhaul combining and zero-forcing backhaul combining.

This paper investigates a heterogeneous cellular network (HCN) topology, where multiple sub-6 GHz bands are available for access and device-to-device (D2D) links with the full-duplex (FD) mode, and an integrated millimeter-wave (mm-wave) band is added to the D2D links’ sub-channel resource options. D2D links share spectrum resources of cellular users or dedicated mm-wave sub-channel. Densely deployed small cells scenario provides an ideal platform to implement mm-wave, FD and D2D communications. With large bandwidths available, mm-wave has the potential to meet the expected extreme data rate demands. Leveraging highly directional beamforming, severe transmission loss and the blockage phenomenon of mm-wave can be alleviated. Theoretically, FD communications can double the spectral efficiency due to bi-directional communications with the same spectral and temporal resources. However, such benefit comes at the cost of residual self-interference (RSI). Multi-user interference (MUI) and RSI among network uplink, downlink and D2D links are the main challenges. In the paper, we formulate an optimization problem for FD access and D2D links sub-channel allocation underlaying HCNs combining sub-6 GHz and mm-wave bands to make the system transmission rate maximized. Then, a scheme based on the coalition formation game is proposed to deal with this challenging NP-complete optimization. Finally, performance evaluation investigates the suitable conditions for FD and HD operations. Under different network parameter settings, we quantify associated performance of proposed scheme.

Vehicular ad hoc networks (VANETs) are wireless self-organizing networks, whose communication is conducted through open wireless channels, thus making it vulnerable to various attacks. It is therefore necessary to employ encryption technology to ensure secure communication. In view of the foregoing, key agreement techniques are introduced to VANET communications. The group key agreement (GKA) protocol allows a group of participants to establish a public session key for a secure communication channel over an insecure network. The traditional GKA protocol is inefficient, however, and consumes considerable amounts of resources. With the aim of resolving problems related to information security and privacy preservation in VANETs, this paper proposes a full session key agreement scheme based on chaos mapping. In this paper, the first phase describes the key agreement between the fog server and group administrator; the second phase describes the group key agreement for vehicle nodes in the group where the vehicle can only communicate with vehicles having the same group key without the aid of a trusted key center or centralized key distributor. The proposed scheme is based on Chebyshev chaotic mapping algorithm, in which a chaotic map is utilized to provide a one-way hash; Chebyshev polynomial is also employed to establish a public multi-party key; it avoids the modular multiplication index or scalar multiplication on the elliptic curve. The proposed scheme does not only satisfy the security requirements in VANETs but also performs detailed analysis.

In this paper, we study the underlay relay-aided Device-to-Device (D2D) communications to improve the physical layer (PHY) security of the cellular network. We propose a cooperative scheme, whereby the D2D pair, in return of being allowed to share the spectrum band of the cellular network, serves as a friendly jammer, through its multiple-input multiple-output relay, to degrade the wiretapped signal at an eavesdropper. This paper aims to show that spectrum sharing is advantageous for both D2D communications and cellular networks with respect to reliability and robustness for the former, and the physical layer security enhancement for the latter. To assess the proposed cooperative system model, closed-form expressions for the D2D outage probability, the secrecy outage probability, and the probability of non-zero secrecy capacity are derived. More importantly, the benefits due to the cooperation scheme are verified through numerical and simulation results.

To overcome the limitations of DSRC with short range, non-supportability of high density networks, unreliable broadcast services, signal congestion and connectivity disruptions, cellular vehicle-to-everything (C-V2X) communication networks, standardized in 3rd Generation Partnership Project (3GPP) Release 14, have been recently introduced to cover broader vehicular communication scenarios including vehicle-to-vehicle (V2V), vehicle-to-pedestrian (V2P) and vehicle-to-infrastructure/network (V2I/N). In C-V2X, vehicles can directly communicate over PC5 based dedicated sidelinks called direct mode or V2V communication. However, high vehicle densities may require reuse of cellular spectrum for V2V. Moreover, infrastructure mode communication through V2I/N links can augment V2V communication by enhancing communication range and reliability for enhanced safety along with consistent performance under traffic congestions. Motivated by the stringent connection reliability, spectral efficiency, and coverage requirements in C-V2X, this paper presents the first comprehensive and tractable analytical framework for performance of C-V2X networks over shared V2V and cellular uplink channels, where the transmitting vehicles can deliver their information via infrastructure or direct mode, based on their distances, propagation environments and the bias factor. By practically modeling the vehicles on the roads using the doubly stochastic Cox process and the base-stations, we derive new association probabilities, new success probabilities of infrastructure and direct mode, and overall success probability of the C-V2X communication over shared channels, which are validated by the simulations results. Our results reveal the benefits of our proposed model (possibility of selecting both direct and infrastructure modes over shared channels) compared to V2V network in terms of success probability., Comment: Paper revised

Compromised by the ever increasing amount of mobile data traffic generated by mobile devices, edge servers are expected to provide caching resources for users so as to enable low-latency content delivery and release the burden on backhaul network. Considering the limited caching capacities of edge servers, it is essential to design an efficient content placement strategy to increase the data offloading ratio, i.e., the proportion of requested contents that are delivered via edge caching rather than backhaul links. In this paper, we propose a spatially cooperative caching strategy for a two-tier heterogeneous network consisting of edge servers and caching helpers aiming at reducing the storage space taken by duplicate contents on caching helpers and increasing hit probability. We develop an analysis framework for the proposed spatially cooperative caching strategy by using tools from stochastic geometry and maximize the hit probability by optimizing the caching probabilities of contents on edge servers and caching helpers. Particular, we derive the closed-form solution of the optimization problem for unit cache size. The simulation results are identical with the analytical ones and the outperformance is observed with the optimal caching probability derived in this paper compared with the existing caching strategies.

There has been much increased interest in the academic and industrial research communities on vehicular ad-hoc networks (VANETs). In this paper, we present an analytical model to study the end-to-end delay in a one-way VANET. This paper proposes an analytical formula for the end-to-end delay probability distribution. Using the derived probability distribution, the probability that the end-to-end delay is lower than a given threshold may be calculated. In addition, one can straightforwardly study the impact of parameters such as wireless communication range, vehicular densities, distance between source the destination, and minimum and maximum vehicle speeds on the end-to-end delay. This can help to better understand data dissemination in VANETs. Moreover, closed forms for lower and upper bounds on the end-to-end delay probability distribution are obtained. Extensive simulation results demonstrate the accuracy of our analysis.

This paper proposes an analytical model to investigate the performance of periodical broadcast of safety messages in vehicular ad hoc networks (VANETs), regarding a hybrid medium access control (MAC) protocol, called NC-PNC MAC. We first examine the percent of vehicles involved in subcarrier collisions during a random orthogonal frequency-division multiple access scheme, and then theoretically analyze the total number of transmissions and the packet delivery ratio (PDR) during one dissemination period. Based upon the analysis, this paper not only reveals how the subcarrier collision probability influences the PDR performance, but mathematically obtains the maximum PDR. To confirm the results, by adjusting a pivotal parameter of the MAC protocol, the PDR performance for basic safety message broadcast in VANETs can be enhanced by 10% to 30% under the constraint of the delivery latency.

With the dramatic growth of Bluetooth low energy (BLE), the indoor radio environment suffers from complex spectrum interference in the 2.4-GHz Industrial Scientific and Medical equipment (ISM) band, because BLE unconditionally transmits data without any carrier sensing or energy detection. With some recent trends reintroducing traditional wireless personal area networks standard for supporting the deployment of Internet of Things (e.g., Thread), IEEE 802.15.4 is spotlighted again, requiring mitigation of the mutual interference problem in the ISM band. For suitable coexistence under densely deployed BLE, this paper considers key impact phenomena of BLE characteristics, including studying a channelization and frequency-hopping mechanism. It finds a solution that can efficiently prevent problems by designing a multiple spectrum access scheme employing the same channelization that comes with BLE. To investigate the performance, this paper constructs a 4D Markov chain model describing the behavior of one communication node, and adopts an analytic matrix method to solve the model. The numerical results and experimental output are presented for further evaluation.

Nowadays, wireless communication has become a fabric of our daily life, and it has been a universal demand for higher capacity and longer battery lifetime. For the sake of solving these problems, this paper considers taking the advantage of cooperative communication with the assistance of green relays. So, in this paper, we design an auction market that is composed of one base station (acts as the auctioneer), multiple green relays (act as sellers), and multiple mobile terminals (act as buyers). The terminals need to pay for the cooperative service, and the relays sell it for revenue. In addition, the terminals can raise their bid according to their residual energy; thus the terminals that lack energy have more opportunities to get cooperative service to avoid energy exhaustion. At the same time, the relays can reduce the price based on their instantaneous energy harvesting amount, and, hence, the relays can serve more terminals when they can harvest more energy from the environment. This paper also proposes three different auction rules to show the effect of relay selection. Furthermore, power allocation among relays and terminals is adopted to minimize the power consumption of terminals under the SNR requirement. Simulation results show that the three relay selection rules perform diversely and have their own advantages and disadvantages, but all of them can improve system capacity and prolong the lifetime of the mobile terminals effectively. And, with power allocation, the terminal can utilize the least energy to achieve its SNR requirement.

This correspondence paper investigates uplink non-orthogonal multiple access (NOMA) for unmanned aerial vehicle base stations (UAV-BSs). Users under the service area of a UAV-BS perform NOMA random access (RA) by controlling their transmit power so that the UAV-BS can receive one of two predefined power levels. This facilitates successive interference cancellation (SIC) at the UAV-BS. This correspondence paper shows the maximum stable throughput of uplink NOMA RA in terms of the altitude and beamwidth of the UAV-BS. Further, we propose a stabilizing algorithm, with which a UAV-BS broadcasts the throughput-maximal retransmission probability every slot, while users access the channel based on the retransmission probability. Extensive simulations show that the proposed algorithm can achieve the maximum throughput 0.5869 (packets/slot) and stabilize the system with time-varying traffic.

Connection and service request scheduling affects the performance of a mobile relay node (MRN) in a relay-assisted long-term evolution network in terms of crucial quality-of-service (QoS) metrics such as the blocking probability and the system's response time. In this paper, a novel Deadline-constrained Connection and service Request Scheduling (DCRS) scheme is proposed with the objective of improving an MRN's performance in terms of the above-mentioned metrics. In this paper, a stochastic queueing model is formulated for the purpose of capturing the MRN's behavioral dynamics and evaluating its performance as it operates under DCRS. Simulations are conducted in order to verify the model's results’ validity and accuracy. Moreover, the MRN performance achieved under DCRS is compared to that achieved under the typically adopted first-come-first-service (FCFS) scheme. Results indicate that DCRS remarkably outperforms FCFS.

High-speed rail public broadband wireless access requires communication terminals with high mobility to perform seamless cell switching in a harsh and fast time-varying environment. However, frequent switching caused by fast motion inevitably leads to unpredictable high volatility of the available spectrum, resulting in inefficient wireless communication. The application of highly mobile cognitive radio technology may address this challenge. This paper first analyzes the physical structure of the existing railway wireless communication network, and determines the characteristics of chainlike distribution and cascade operation of the base stations along the railway. Furthermore, using Bayesian reinforcement learning and multi-agent theory, a distributed cognitive base station model suitable for railway wireless environment is constructed. Based on the joint spectrum management of cascaded base station groups, this model proposes a multi-agent coordination algorithm with the goal of global optimal communication performance of the entire rail line. Finally, this paper evaluates the network performance of various test scenarios, and proves that the cognitive base station multi-agent cascade cooperative system can significantly increase the probability of successful data transmission and greatly reduce wireless spectrum handovers. This proposed scheme provides a brand-new solution for solving the problem of low wireless spectrum efficiency in the typical railway wireless network.

The restricted resources of mobile wireless networks such as limited bandwidth have resulted in stringent requirements on the available quality of service (QoS). To enhance the communication performance, mobile nodes attempt to optimize the available bandwidth of wireless networks, which, however, makes them vulnerable to the malicious attacks of adversaries owing to the open and mobile context. Furthermore, improving the security level of the communication consumes bandwidth and thus degrades the communication quality. In order to harmonize the QoS and security, in this paper, the two conflicting terms “communication player” and “security player” are considered as two individual players and are balanced using game theory. Furthermore, we construct a non-cooperative game model, wherein the utilities of the communication player and security player are maximized by controlling the number of nodes transmitted and the length of hash, respectively. We formulate the utility functions of the communication player with respect to the throughput as well as the security level of the Merkle tree for the security player. This paper considers complete information game and incomplete information game, for which we theoretically determine the pure strategy Nash equilibrium and the pure strategy Bayesian Nash equilibrium, respectively. Extensive numerical calculations are performed to comprehensively investigate the utilities of each player and the Nash equilibrium for various combinations of the concerned parameters. The results show that the presented theoretical game approach enables a mobile node to adaptively perform specific actions based on the derived Nash equilibrium. With the obtained Nash equilibrium values, both communication player's and security player's utilities reach to the maximum so that satisfactory communication quality can be realized without compromising the security.

Coordinated multipoint joint transmission (JT) is a vital technique of the fifth-generation (5G) networks to increase throughput but causes a significant burden on network backhaul because the same user data must distribute to multiple base stations, called a JT cluster. Thus, many studies have explored how to reduce backhaul data traffic using caching user data at base stations. Millimeter wave (mmWave) mesh backhaul is a promising architecture for small cells to exchange cache data over 5G networks. However, this paper observes that inappropriate JT clusters and routing paths will result in unnecessary mmWave mesh backhaul bandwidth consumption such that the performance gain of the JT will be reduced. Therefore, in this paper, we study the JT clustering problem with the consideration of caches at base stations and mmWave mesh backhaul. The objective is to minimize total backhaul traffic while satisfying the data rate requirement of each user under limited radio resource units. We propose a two-stage algorithm based on dynamic programming approach to solve the problem. We prove that the dynamic programming algorithm can find an optimal solution for our subproblem. The simulation results provide several insights and show that compared with two baseline algorithms, our proposed algorithm can significantly reduce more backhaul bandwidth consumption.

Delay/disruption tolerant networking (DTN) was proposed as a networking architecture for reliable data delivery in space vehicle communications despite long propagation delays and/or lengthy link disruptions. As one of the main data transport protocols of DTN, Licklider transmission protocol (LTP) was proposed by the NASA for reliable data delivery in challenging space environments in which the existing transport protocols of DTN, TCP, and UDP do not perform effectively. Pair-wise comparisons among LTP, TCP, and UDP running in the DTN stack have previously been done using statistical methods; evaluation results and performance analysis are available in the existing LTP research literature. However, there is as yet no solid analytical model of LTP performance in the presence of link disruptions. In this paper, we present an analytical method to predict transmission performance of LTP for reliable file delivery in space vehicle communications with focus on the expected file delivery delay (or latency) over space channels characterized by random link disruptions. Realistic file-transmission experiments using a PC-based infrastructure are presented to validate the analytical models. The analysis and study results presented in this paper are expected to be useful in understanding the impact of transmission conditions and configurations, on the efficiency of LTP when deployed for reliable data delivery in space missions using communication links that are subject to frequent and random interruptions.

Vehicle platooning systems are often equipped with vehicle-to-vehicle (V2V) communication technologies to improve both the road efficiency and road safety by exchanging vehicle information over wireless networks to maintain relatively small inter-vehicle distance. The road safety often relies on the quality of service delivered by the V2V communication. The V2V networks are, however, subject to channel fading and often have limited communication bandwidth. The limited bandwidth inevitably compromises the road safety as the vehicular network will easily get congested if the number of vehicles joining the network increases. To address the challenges of ensuring vehicle safety under unreliable wireless network with limited bandwidth, this paper first uses a two-state Markov chain to model the channel fading in vehicular networks. Under the Markov chain model, this paper further develops a novel distributed event triggered strategies under which the vehicle platooning system achieves stochastic $\mathcal {L}_2$ string stability while ensuring an efficient use of the limited communication bandwidth. The simulation results are provided to verify the effectiveness and advantages of the proposed methods.

Major international automakers have considered the deployment of the 5.9 GHz dedicated short-range communications (DSRC) on their vehicle fleets for wireless connectivity. DSRC-enabled vehicle-to-vehicle (V2V) communication through broadcast of basic safety messages enables safety applications for crash warning and avoidance. However, in dense traffic conditions as the V2V deployment scales up, the resultant channel load increases and leads to channel congestion and may adversely affect the performance of the safety applications. The Society of Automotive Engineers J2945/1 standard that builds atop Institute of Electrical and Electronics Engineers (IEEE) 802.11p and IEEE 1609 standards provides the minimum performance requirements for V2V safety communications. Specifically, it provides a congestion control protocol for transmission rate and power adaptations to achieve robust performance in dense vehicular networks. The primary contribution of this paper is that using a congestion generation testbed that emulates channel congestion including a large number of remote vehicles, we can validate and test any V2V equipped vehicle for compliance with the J2945/1 standard. Our paper also demonstrates that under heavy congestion, even with 600 ms of inter-transmit time, a moving vehicle can be tracked to a lane-level accuracy.

ETSI multi-access edge computing (MEC) provides an IT service environment and cloud-computing capabilities at the edge of the mobile network, enabling application and content providers to deploy new use cases, such as intelligent video acceleration, with low latency and high bandwidth. Specifically, ETSI MEC introduces an MEC server that implements the edge-cloud platform to host partial server-side service logics in the form of MEC applications (MEC Apps). In this paper, we aim to implement the first proof-of-concept (PoC) in the literature for the MEC-enhanced mobile video streaming service. Our PoC consists of Android User Apps, an MEC App, and the YouTube server. The MEC App implements two main functions: popular video caching and radio analytics/video quality adaptation. The User App provides general functions of a YouTube video streaming app and can access the videos from the cache server or the YouTube server under the MEC server's guidance. In addition to the PoC implementation, this paper further develops two machine learning models to be incorporated into the MEC App for popular video prediction and radio channel quality prediction, which allows to consider the effect of non-negligible round-trip times and adjust the video quality more accurately. The experimental results justify that our models, together with other advantages from MEC, can guarantee good performance for the mobile video streaming service. Finally, we model and investigate the effectiveness of the MEC architecture for improving the quality of experience of video-streaming users.

This paper studies and analyzes the performance of the licensed-assisted access (LAA) scheme introduced by 3GPP in LTE Release 13, and adopted by 3GPP in LTE Release 14, which is called 3GPP LAA scheme for short. Considering the characteristics that the 3GPP LAA scheme is different from other LAA schemes and IEEE 802.11 distributed coordination function (DCF) protocol in WiFi systems, the 3GPP LAA scheme is modeled as a new two-dimensional discrete Markov model, and the collision probability and the channel occupancy utilization are further derived based on the proposed model. To more deeply analyze the performance of the 3GPP LAA scheme by comparisons, we also derive the expressions of the same performance indices for the linear backoff based LAA scheme proposed in this paper and the fixed contention window based LAA scheme mentioned in existing literatures. The simulation and numerical results prove the validity of the proposed Markov chain model, and also show that the 3GPP LAA scheme is the friendliest one to WiFi networks among the three LAA schemes, whereas its total channel occupancy utilization is the lowest when the number of LAA small base stations (SBSs) is little and that is the highest when large. However, the other two LAA schemes are still the graceful coexistence, which is defined as the scheme where the interference to WiFi users caused by LAA SBSs coexisting with them is not more than that caused by other WiFi APs replacing the LAA SBSs.

This paper studies the optimization of signal processing strategies for downlink and uplink of a cloud radio access network (C-RAN) that serves wireless powered users with non-linear energy harvesting (EH) circuits. On the downlink, a baseband processing unit (BBU) sends radio frequency signals to the users through a set of remote radio heads (RRHs), which is centrally managed by the BBU via finite-fronthaul links. Then, each user splits the received signal for information decoding and EH by utilizing the power splitting circuit. By using the harvested energy, each user communicates with the BBU via the RRHs on the uplink. In this paper, we tackle a problem of maximizing the minimum uplink rate of the users subject to the minimum downlink rate constraint as well as the per-node transmit power and fronthaul capacity constraints. To overcome the non-convexity of the problem, we propose an iterative algorithm based on a successive convex approximation method, which obtains a locally optimal solution. Numerical results confirm the effectiveness of the proposed techniques for C-RAN systems with battery-limited users.

To promote the massive video content delivery and to realize the long-term overall cost, the caching and computing functions have to be installed at some intermediate nodes within the networks. This paper presents a cache-aware multicast beamforming design for multicell multigroup multicast, where information-centric networking and mobile edge computing techniques are brought in the multicell multicast system to cache and transcode the contents passing through the nodes. The proposed cache-aware multicast beamforming design jointly optimizes the multicast mode, the caching strategy, and the network-wide beamforming vector, and focuses on minimizing the energy cost of the caching, computing, and communications. To make the formulated problem tractable, a two step method is proposed in this paper, where the first step is devoted to the cache-aware multicast approach design, while the second step is focused on the sparse multicast beamforming design. Furthermore, in order to promote the stabilization of the system, we further design a robust joint optimization strategy for the scenario with the imperfect channel state information. Extensive simulations are conducted to evaluate the performance of our proposed schemes.

Vehicle-to-vehicle (V2V) communication based on the device-to-device (D2D) communication in long term evolution (LTE) system is emerging as a key enabler for connected vehicles today. In this paper, we consider safety-related messages periodically transmitted by vehicle to announce its current status to other neighboring vehicles. The current state-of-the-art LTE V2V communication uses greedy algorithm for the transmission of such periodic messages. Greedy algorithm is known to have decent performance, but the performance is limited due to the lack of a collision–detection mechanism. In this paper, we propose feedback-aided greedy algorithm (FAGA) to complement the drawback of greedy algorithm. We evaluate FAGA via realistic simulations to show that it outperforms comparison schemes in terms of overall message reception ratio (MRR). As a result, it is shown that FAGA operates well even with small amount of feedback and its performance is close to the performance of centralized scheduling method. Moreover, FAGA outperforms greedy algorithm by up to 23.7% in terms of MRR performance.

This paper studies computation offloading for mobile users in legacy vehicles that are not equipped with powerful computing devices. While running a time-sensitive and computation-intensive application on a mobile device (MD) of these users, the MD may offload part or all the applications to a nearby smart vehicle that can serve as a cloudlet. This provides a possibility to complete the application in time while saving the battery energy of the MD. However, high mobility of the vehicles causes short-lived communication links between the vehicles. As a result, the MD may have to offload tasks to a new cloudlet each time it loses the connection to the current cloudlet. In this paper, we propose a vehicle-based cloudlet relaying (VCR) scheme for mobile computation offloading. The objective is to effectively utilize the computation resources available in surrounding smart vehicles of the MD in the highly dynamic network environment, where each vehicle-based cloudlet may only be available to help the MD execute a small portion of the application. Instead of offloading tasks directly from the MD to individual cloudlets, which may consume high power and a long time, especially when the link just becomes available or is about to disconnect, we propose computation relaying that allows the current executing cloudlet to offload tasks to the next executing cloudlet on behalf of the MD. A set of conditions are established to enable the inter-cloudlet offloading so that the computation relaying can be achieved between the vehicle cloudlets, while the results can be returned to the MD. In addition, the computation relaying is always backed up by direct offloading between the MD and individual cloudlets. An algorithm is proposed to find the time to switch to a new cloudlet and select the best cloudlet as the next execution site or return the execution back to the MD, in order to minimize the energy consumption of the MD while satisfying the delay constraint of the application. Extensive simulation results are shown to demonstrate the effectiveness of the proposed VCR scheme.

This paper represents the design, feasibility evaluation, and performance validation of ICMR, a novel cross layer protocol that can maximize concurrent transmissions and avoid data frame interference in wireless networks, achieving a higher throughput comparing with the 802.11 standard and other state-of-the-art protocols. Observations on the 802.11 standard reveal that nodes around both the transmitter and receiver of the ongoing link waste concurrent transmission opportunities, degrading the network throughput dramatically. A state-of-the-art protocol IRMA is proposed to improve the network throughput through exploiting concurrent transmissions at the transmitter side. In this paper, a new ICMR protocol focuses on the receiver side to further improve the network throughput, through exploiting discernible interference cancellation, a physical layer mechanism that can successfully detect data frames when collided by control frames. We analyze the concurrent transmission opportunities of one link from the transmitter's transmission opportunities and the receiver's reception opportunities, then formulate the opportunities and give theoretical analysis to indicate that ICMR will have a higher opportunity over other protocols. Feasibility of the discernible interference cancellation mechanism is demonstrated through experiment results based on USRP2, and the throughput improvement of ICMR comparing with the other protocols is confirmed through simulations based on ns-2.

© 1967-2012 IEEE. Next-generation wireless networks will give rise to heterogeneous networks by integrating multiple wireless access technologies to provide seamless mobility to mobile users with high-speed wireless connectivity. Device-to-device (D2D) communication has proven to be a promising technology that can increase the capacity and coverage of wireless networks. The D2D communication was first introduced in long-term evolution advanced (LTE-A) and has gained immense popularity for the offloading traffic using the licensed and unlicensed band. Challenges arise from resource allocation, provision of quality-of-service (QoS), and the quantification of capacity in an unlicensed band due to the distributed nature of Wi-Fi. In this paper, we propose an analytical performance model for the scalable MAC protocol (SC-MP) in which a resource allocation mechanism is based on the IEEE 802.11 point coordinated function to access the Wi-Fi channel for voice and video/multimedia traffic. In the SC-MP, D2D communication is applied to further offload the video/multimedia traffic. In particular, this paper establishes a three-state semi-Markovian model to derive a closed-form expression of effective capacity in terms of transmission rate and quality-of-service. Further, the SC-MP is analytically modeled using the four-state traditional Markov model to derive the saturation throughput. The analytical results are validated through simulations, hence, proving the appropriateness of the model.

This paper investigates the joint power control and spectrum sharing problem for vehicle-to-everything (V2X) communications based on long term evolution unlicensed (LTE-U) technology in a heterogeneous network environment. We classify vehicle user equipments (VUEs) into safety and non-safety VUEs according to their respective service and access categories. To address the joint problem of spectrum allocation, power control, and spectrum sharing, a resource allocation strategy is proposed to guarantee fair coexistence among users. Each periodic access interval over unlicensed spectrum is divided into content period (CP) duration and content free period (CFP) duration. Accordingly, this paper proposes a framework which allows non-safety VUEs to not only contend for unlicensed spectrum in CP duration, but also utilize reserved unlicensed spectrum in CFP duration. Based on the framework, we set our objective to maximize the total throughput of cellular user equipments and non-safety VUEs, and propose a three-step decomposing scheme, which is nested with interior point method and matching algorithm. We also assess the ergodic sum rate with respect to statistical channel state information with reduced computation complexity.

Considering that the future cellular networks are more content-centric and content sharing among user equipments is more universal, device-to-device (D2D) technique attracts attention on supplying a feasible way for content delivery among proximal users without deploying additional infrastructure. Whereas some problems are still not clear such as the limitation on D2D communication for content delivery and which transmission mode (unicast or multicast) is more efficient. In this paper, the performance of content delivery is analyzed for D2D unicast and multicast, respectively. Several metrics such as the number of caching users, the number of request users, and the serving time of a content request are quantified with the consideration of user deployment and interference environment. These analyses provide an insight into D2D content delivery and deep understanding of D2D unicast and multicast on content delivery. To further distinguish appropriate conditions of employing unicast and multicast, energy efficiency is also investigated for two transmission modes. Extensive evaluations show that a better transmission mode can be selected based on the work presented in this paper. It is also verified that the efficiency of content delivery in cellular networks can be improved by this mode selection.

Mobile services like GSM and LTE are increasingly offered on board of long-haul flights. This is achieved by installing an onboard base station, namely a GSM BTS or an LTE eNodeB in the airplane. Additionally, the airplane is equipped with a network control unit (NCU) device which prevents onboard mobile users from attempting to connect to ground mobile networks and, therefore, affect or interfere with terrestrial communications. The objective of this paper is to evaluate the need of the network control unit. For that purpose, it is investigated if a mobile user in the airplane can establish a connection with an existing terrestrial GSM or LTE network without the presence of the network control unit and the onboard base station. Only a few studies exist which investigate this connection. The analysis done in this paper takes into consideration physical and high layer requirements of both GSM and LTE networks.

The next generation of mobile communication has progressed toward the deployment of small cells to meet the growing demands of increased capacity and QoS as compared to the conventional method, where all the computations were performed by the base station (BS)'s only. To reduce burden at the BS side, small cells deployment has been stressed upon, thus resulting in the formation of ultradense networks (UDN) having high concentration of small cells (e.g., picocell, femtocell, hotspots) and as a counter effect of which distance between two small cells is reduced to a greater extent. With such a close association of cells in UDN, the probability of frequent handovers also increases abruptly. As a result, the chances for attacker to spoof the bandwidth also increases many folds. In this paper, we have analyzed SNR, signal-to-interference-plus-noise ratio, and channel quality information channel parameters, such that the position of moving users at which handover is initiated in picocell deployment of UDN can be traced out successfully or region where the probability of attackers presence is high. Through this paper, we have tried to introduce the attacking scenario for the high mobility conditions in UDN.

This paper describes techniques that enable vehicles to collect local information (such as road conditions and traffic information) and report it via road-to-vehicle communications. To exclude malicious data, the collected information is signed by each vehicle. In this communication system, the location privacy of vehicles must be maintained. However, simultaneously linkable information (such as travel routes) is also important. That is, no such linkable information can be collected when full anonymity is guaranteed using cryptographic tools such as group signatures. Similarly, continuous linkability (via pseudonyms, for example) may also cause problem from the viewpoint of privacy. In this paper, we propose a road-to-vehicle communication system with relaxed anonymity via group signatures with time-token dependent linking (GS-TDL). Briefly, a vehicle is unlinkable unless it generates multiple signatures in the same time period. We provide our experimental results (using the RELIC library on a cheap and constrained computational power device, Raspberry Pi) and simulate our system by using a traffic simulator (PTV), a radio wave propagation analysis tool (RapLab), and a network simulator (QualNet). Though a similar functionality of time-token-dependent linking was proposed by Wu et al. (“Balanced trustworthiness, safety, and privacy in vehicle-to-vehicle communications,” IEEE Trans. Veh. Technol., vol. 59, 2010), we can show an attack against the scheme where anyone can forge a valid group signature without using a secret key. In contrast, our GS-TDL scheme is provably secure. In addition to the time-dependent linking property, our GS-TDL scheme supports verifier-local revocation, where a signer (vehicle) is not involved in the revocation procedure. It is particularly worth noting that no secret key or certificate of a signer (vehicle) must be updated, whereas the security credential management system must update certificates frequently for vehicle privacy. Moreover, our technique maintains constant signing and verification costs by using the linkable part of signatures. This might be of independent interest.

In this paper, we investigate spectrum sharing with power-constrained multiradio secondary users (SUs) in cognitive radio networks. The scenario under consideration consists of a primary spectrum owner who runs auctions for leasing her idle channels and multiple SU bidding for winning the usage of spectrum channels. Different from existing works in the literature with an assumption of single-minded SUs, in this paper, SUs can benefit from flexible quantity of channels. In addition, since each SU is ordinarily equipped with a fixed number of radios, she cannot utilize the amount of channels that exceed her radio capacity. Moreover, each SU has a certain power limitation so that the quality of service (QoS) of her transmission may also be constrained, even though the number of allocated channels is increased. To jointly address all these challenges, a novel ascending-price progressive auction algorithm is proposed, where the spectrum allocation decisions are made by gradually increasing the unit channel price. Theoretical analyses prove that the proposed algorithm meets the properties of QoS satisfaction , individual rationality , and incentive compatibility and achieves Pareto optimality . Simulation results further demonstrate that the proposed auction algorithm can improve both the auction revenue and the social welfare, and increase the number of winning SUs compared to the counterparts.

Communications-based train control (CBTC) is a modern signaling system that uses radio communication to transfer train control information between the train and the wayside. A vast majority of CBTC systems worldwide use IEEE 802.11 Wi-Fi as the radio technology mostly due to its cost effectiveness. The trackside networks in these systems are mostly based on the conventional infrastructure Wi-Fi. It means a train has to continuously associate (i.e., perform handshake) with the trackside Wi-Fi access points (AP) as it moves. This is a time-consuming process associated with a certain delay. Additionally, these APs are connected to the wayside infrastructure via optical fiber cables that incurs huge costs. This paper presents a novel design in which trackside nodes function in ad-hoc Wi-Fi mode, which means no association has to be performed with them prior to transmitting. A train simply broadcasts packets to any nodes in its range. A node upon receiving these packets forwards them to the next node and so on, forming a chain of nodes. Following this chain, packets arrive at the destination. To make the design resilient against interference, transmissions are separated on multiple frequencies. Furthermore, redundancy is introduced in the design as a node forwards packets to not only one but two of its neighbors. This paper investigates the performance of the new design from the perspective of resiliency, redundancy, and scalability, and presents the results both from a field experiment carried out using prototype hardware and an extensive simulations study.

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.

In wireless networks, retransmissions are used by senders to recover lost packets. The conventional retransmission schemes usually retransmit only one lost packet each time, resulting in a low retransmission efficiency. However, using broadcasting nature of a wireless channel with network coding (NC), we can recover more than one lost packet per transmission. Different from single-sender multiple-receiver wireless networks as considered in the existing works, this paper explores the ways to use NC for retransmissions in multiple-sender multiple-receiver scenarios. In addition, this paper also aims to investigate the advantages and shortcomings of using NC in retransmissions. In order to maximize the gain and minimize the impact in NC retransmissions, a probabilistic network coding retransmission (PNCR) scheme is proposed, where a buyer/seller game-theoretic approach is adopted to optimize the performance. The experimental results confirm the effectiveness of the PNCR scheme.

Device-to-device (D2D) communication is developed as a new paradigm to enhance network performance according to LTE and WiMAX advanced standards. The D2D communication may have dedicated spectrum (overlay) or shared spectrum (underlay). However, the allocated dedicated spectrum may not be effectively used in the overlay mode, while interference between the D2D users and cellular users cause impairments in the underlay mode. Can the resource allocation of a D2D system be optimized using the cognitive approach where the D2D users opportunistically access the underutilized radio spectrum? That is the focus of this paper. In this paper, the transmission rate of the D2D users is optimized while simultaneously satisfying five sets of constraints related to power, interference, and data rate, modeling D2D users as cognitive secondary users. Furthermore, a two-stage approach is considered to allocate the radio resources efficiently. A new adaptive subcarrier allocation scheme is designed first, and then, a novel power allocation scheme is developed utilizing geometric water-filling approach that provides optimal solution with low computation complexity for this nonlinear problem. Numerical results show that the proposed approach achieved significant performance enhancement than the existing schemes.

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.