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In this paper, we propose a novel multichannel network with infrastructure support, which is called an MC-IS network, that has not been studied in the literature. To the best of our knowledge, we are the first to study such an MC-IS network. Our proposed MC-IS network has a number of advantages over three existing conventional networks: a single-channel wireless ad hoc network (called an SC-AH network), a multichannel wireless ad hoc network (called an MC-AH network), and a single-channel network with infrastructure support (called an SC-IS network). In particular, the network capacity of our proposed MC-IS network is \sqrtn\log n times higher than that of an SC-AH network and an MC-AH network and the same as that of an SC-IS network, where n is the number of nodes in the network. The average delay of our MC-IS network is \sqrt{\log n/n} times lower than that of an SC-AH network and an MC-AH network and \min\{C_{I},m\} times lower than the average delay of an SC-IS network, where CI and m denote the number of channels dedicated for infrastructure communications and the number of interfaces mounted at each infrastructure node, respectively. Our analysis on an MC-IS network equipped with omnidirectional antennas has been extended to an MC-IS network equipped with directional antennas only, which are named as an MC-IS-DA network. We show that an MC-IS-DA network has an even lower delay of c/(\lfloor \text2\pi/\theta\rfloor\cdot CI) compared with an SC-IS network and our MC-IS network. For example, when CI=\text{12} and \theta=\pi/\text12, an MC-IS-DA can further reduce the delay by 24 times lower than that of an MC-IS network and by 288 times lower than that of an SC-IS network. [ABSTRACT FROM AUTHOR]

Small cells are introduced to cellular systems to enhance coverage and improve capacity. Densely deploying small cells can not only offload the traffic of macrocells but also provide an energy- and cost-efficient way to meet the sharp increase in traffic demands in mobile networks. However, such a cell deployment paradigm also leads to heterogeneous network (HetNet) infrastructure and raises new challenges for cell planning. In this paper, we study the cell planning issue in the HetNet. Our optimization task is to select a subset of candidate sites to deploy macro or small cells to minimize the total cost of ownership (TCO) or the energy consumption of the cellular system while satisfying practical constraints. We introduce approximation algorithms to cope with two different cell-planning cases, which are both NP-hard. First, we discuss the macrocell-only case. Our proposed algorithm achieves an approximation ratio of O(\log R) in this scenario, where R is the maximum achievable capacity of macrocells. Then, we introduce an O(\log \widetildeR)-approximation algorithm to the small-cell scenario, where \widetildeR is the maximum achievable capacity of a macrocell with small cells overlaid on it. Numerical results indicate that the HetNet can significantly reduce the TCO and the energy consumption of the cellular system. [ABSTRACT FROM PUBLISHER]

Multiple-input–multiple-output (MIMO) full-duplex relaying (FDR) has been considered an efficient technique to provide coverage to users where their direct links from the base station (BS) are too weak for reliable signal reception. However, when multiple MIMO full-duplex relays are deployed in a network, the signal reception quality relies on the effective suppression of multiple types of interference. In this paper, the distributed beamforming is studied for the MIMO FDR network by formulating a power minimization problem with a nonstrict convex objective function (total transmit power of both the BS and all the relays in the network) under individual user rate constraints. We come up with two iterative distributed beamforming algorithms, Algorithm 1 for relays equipped with single receive antenna and Algorithm 2 with multiple receive antennas. The former can yield a global optimal solution of the power minimization problem, whereas the latter can yield only a local optimal solution due to conservative successive convex approximations (SCAs) performed at each iteration, and a rigorous analysis on the upper bounds of step sizes is proposed to guarantee their convergence. The proposed two algorithms only require local information exchange between relays and hence are scalable for different network sizes and topologies. An “early termination” strategy in the operation of the proposed two algorithms is also presented to acquire an acceptable transmit power solution with less computation time consumption and thus suitable for realistic applications. Finally, some simulation results are provided to demonstrate that the proposed two algorithms perform well and significantly better than the existing state-of-the-art scheme reported in the work of Lee and Shin. [ABSTRACT FROM PUBLISHER]

When a large number of machine-to-machine (M2M) terminals attempt to access the Long-Term Evolution (LTE)/LTE Advanced (LTE-A) cellular network using the physical random access channel (PRACH), congestion and overload may result, which can lead to serious degradation of performance for both M2M and human-to-human (H2H) terminals. The main cause for this is the inherent complexity of the four-way handshake used for random access, which is well suited for H2H terminal access but unsuitable for massive M2M access. In this paper, we describe an efficient scheme for concurrent M2M and H2H access on the PRACH, which separates the resources for M2M and H2H access at the level of preamble codes and avoids the use of the four-step handshake for M2M terminals by implementing a carrier sense multiple access with collision avoidance (CSMA/CA) overlay network using the designated preamble codes. We analyze the performance of the scheme for both H2H and M2M traffic and show the values of the most important design parameters that enable this scheme to support concurrent access by H2H and M2M terminals with little performance degradation. [ABSTRACT FROM PUBLISHER]

In this paper, we consider random-access wireless multihop networks, with multipacket reception capabilities, where multiple flows are forwarded to the gateways through node disjoint paths. We explore the issue of allocating flow on multiple paths, exhibiting both intra- and interpath interference, in order to maximize average aggregate flow throughput (AAT) and provide bounded packet delay. A distributed flow allocation scheme is proposed where allocation of flow on paths is formulated as an optimization problem. Through an illustrative topology, it is shown that the corresponding problem is nonconvex. Furthermore, a simple but accurate model is employed for the AAT achieved by all flows, which captures both intra- and interpath interference through the signal-to-interference-plus-noise ratio (SINR) model. The proposed scheme is evaluated through Ns2 simulations of several random wireless scenarios. Simulation results reveal that the model employed accurately captures the AAT observed in the simulated scenarios, even when the assumption of saturated queues is removed. Simulation results also show that the proposed scheme achieves significantly higher AAT for the vast majority of the wireless scenarios explored than for the following flow allocation schemes: one that assigns flows on paths on a round-robin fashion, one that optimally utilizes the best path (BP) only, and another one that assigns the maximum possible flow on each path. Finally, a variant of the proposed scheme is explored, where interference for each link is approximated by considering its dominant interfering nodes only. [ABSTRACT FROM PUBLISHER]

Coordinated multipoint transmission (CoMP) with the joint transmission (JT) scheme is employed in cellular networks to improve data rate and cell-edge throughput and/or to increase system throughput. In CoMP-JT, since the user equipment (UE) is capable of receiving the desired signal from an adjacent cell, as well as from its serving cell, it can achieve an improved signal-to-interference ratio (SIR). However, this scheme entails exhaustion of resources in serving base stations. In this paper, we propose a call admission control scheme (CAC) to improve the performance of CoMP-JT-based cellular systems. In this CAC scheme, the CoMP-JT technique is applied to UEs located near the edge of a cell. To establish an analytical model for CoMP-JT-based cellular systems, we introduce a model for traffic analysis using a 2-D Markov chain and approximate the computation of the power sum of multiple lognormal random components in a multicell environment. Performances of CoMP-JT-based cellular systems are evaluated with respect to two quality-of-service (QoS) constraints pertaining to call-blocking and outage probabilities, respectively, from the network-layer and the physical-layer perspectives. We first measure the resource utilization and call blocking probability for the downlink resources for various offered loads in the cell. Based on that, we obtain the outage probability and effective throughput of the system. The analytical results are compared with computer simulations. Finally, we consider the dynamic point selection (DPS) scheme that is a modified version of the JT scheme, in which some resources of adjacent cells are muted. [ABSTRACT FROM PUBLISHER]

The dynamic spectrum access (DSA) principle, relying on the cognitive radio (CR) paradigm, allows users to access spectrum over time intervals or spatial areas where it remains unused. Due to the opportunistic nature of DSA/CR, the behavior and performance of DSA/CR networks depends on the perceived spectrum usage pattern. An accurate modeling of spectrum occupancy therefore becomes essential in the context of DSA/CR. In this context, this paper addresses the problem of accurately modeling the spectrum occupancy pattern perceived by DSA/CR users in the spatial domain. A novel spatial modeling approach is introduced to enable a simple yet practical and accurate characterization of spectrum. First, a set of models is proposed to characterize and predict the average level of occupancy perceived by DSA/CR users at various locations based on the knowledge of some simple signal parameters. An extension is then proposed to characterize not only the average occupancy level but the instantaneous channel state perceived simultaneously by DSA/CR users observing the same transmitter from different locations as well. The validity and accuracy of the theoretical models are demonstrated with results from an extensive spectrum measurement campaign. Some illustrative examples of their potential applicability are presented and discussed as well. [ABSTRACT FROM PUBLISHER]

In this paper, we introduce advancements of the conventional blanking nonlinearity (BN) for orthogonal frequency-division multiplexing (OFDM)-based systems, which is referred to in the following as advanced BN. Blanking is a common measure for mitigating impulsive interference that often occurs in wireless communication systems. Although the BN removes impulsive interference reliably, it possesses various drawbacks for OFDM-based systems. In particular, the choice of the blanking threshold (BT), to decide whether a received sample is blanked, is a critical issue. We present an algorithm for determining the optimal BT to maximize the signal-to-noise-and-interference ratio (SINR) after blanking. Another drawback is that the entire received signal is discarded during a blanking interval, despite the fact that only a fraction of the spectrum of the OFDM signal might be affected by interference. We show how blanking can be limited to subcarriers that are actually affected by interference. Further, we show how these measures can be combined and how a priori information obtained in an iterative loop can be incorporated into the proposed scheme. Simulation results incorporating realistic channel and interference models demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM PUBLISHER]

This paper considers a new power strategy and channel-allocation optimization for secondary users (SUs) in an orthogonal frequency-division multiplexing (OFDM)-based cognitive radio (CR) network where the coverage area of the secondary network is divided into an overlay region and a hybrid region. SUs in the overlay region can adopt the overlay spectrum access method, whereas SUs in the hybrid region may adopt the underlay or sensing-free spectrum access method. We first present a general resource-allocation framework that optimizes the power and channel allocation to SUs who adopt these different spectrum access methods, depending on their locations. To enable sensing-free spectrum access, we then propose a new algorithm that incorporates an interference violation test to decide the parameters in the general framework. The proposed scheme intelligently utilizes frequency and space opportunities, avoids unnecessary spectrum sensing, and minimizes overall power consumption while maintaining the quality of service (QoS) of a primary system. Simulation results validate the effectiveness of the proposed method in terms of energy efficiency and show that enhanced performance can be obtained by utilizing spatial opportunities. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a non-data-aided (NDA) method to estimate the noise variance for orthogonal frequency division multiplexing (OFDM) system in frequency-selective channels. The proposed method is developed based on the signal correlation introduced by the use of the cyclic prefix (CP) and uses the difference between two discrete Fourier transform (DFT) outputs in the CP interval to estimate the noise variance. Analytical result shows that the obtained noise variance is an unbiased estimate in a quasi-static fading channel. Simulation results show that, even in the case in which the maximum delay spread is equal to the CP length and the channel is not quasi-static, the proposed method still works well. [ABSTRACT FROM PUBLISHER]

This paper proposes feasible and satisfactory system design parameters to mitigate the impact of interference on real-time high-definition video streaming in infrastructure-to-vehicle (I2V) telematic platforms utilizing 60-GHz radiation and the corresponding IEEE 802.11ad baseband. The analysis captures the impact of interference on the 60-GHz I2V vehicle (IV), which is caused by multiple interference sources through the 60-GHz wireless transmissions from nearby I2V base stations (IBSs) to their associated IVs. The impact of the interference on the quality of main 1080p at 30-frame/s (30 1080p frames/s) and 1080p at 60-frame/s (60 1080p frames/s) streaming is analyzed and estimated for various simulation settings. [ABSTRACT FROM PUBLISHER]

This paper deals with the problem of user association in heterogeneous networks (HetNets). With the existence of small cells, to better associate user equipment (UE) with base stations (BSs), we propose a novel collaborative filtering (CF)-based wireless network recommendation system, which involves social interactions among UEs. Different from traditional user association schemes, the UEs in the proposed system interact with each other by rating the BSs to improve recommendation qualities. Similarity between UEs' preferences to the quality of service (QoS) and historical information on the QoS of networks are taken into consideration. The core of the network recommendation system is a rating matrix maintained by the operator. A UE can automatically rate the connected BS according to real-time measured parameters (interference, packet loss rate, time delay, etc.) that it experiences during service. Taking the Voice over Internet Protocol (VoIP) service as an example, the measured parameters can be mapped to certain QoS levels with the E-model, which is used as the ratings. During the process of handover, the operator recommends the BSs to the UEs based on the rating matrix. While the ratings help the UEs gain better recommendation qualities, they tend to avoid the costs, e.g., computational and bandwidth resources. Therefore, the UEs have to trade off between the profits and costs brought about by the rating procedure. A satisfaction game is formulated to deal with this problem. We use a utility function to measure a UE's satisfaction. When every UE's utility comes to a preset level, the game is considered to reach the satisfaction equilibrium (SE). An algorithm is designed to learn the SE, and the convergence is analyzed. The advantages of the proposed system lie in two aspects. First, it comprehensively considers multiple factors that influence the QoS, instead of signal strength only. Second, the historical information helps UEs select BSs with better long-term QoS but not immediate QoS. Simulation results show the effectiveness of the learning algorithm on both learning the SE and avoiding severe congestions in each BS. [ABSTRACT FROM PUBLISHER]

This paper uses a spatial Aloha model to describe a distributed autonomous wireless network in which a group of transmit–receive pairs (users) shares a common collision channel via slotted-Aloha-like random access. The objective of this study is to develop an intelligent algorithm to be embedded into the transceivers so that all users know how to self-tune their medium access probability (MAP) to achieve overall Pareto optimality in terms of network throughput under spatial reuse while maintaining network stability. While the optimal solution requires each user to have complete information about the network, our proposed algorithm only requires users to have local information. The fundamental of our algorithm is that the users will first self-organize into a number of nonoverlapping neighborhoods, and the user with the maximum node degree in each neighborhood is elected as the local leader (LL). Each LL then adjusts its MAP according to a parameter R, which indicates the radio intensity level in its neighboring region, whereas the remaining users in the neighborhood simply follow the same MAP value. We show that by ensuring R \le \text{2} at the LLs, the stability of the entire network can be assured, even when each user only has partial network information. For practical implementation, we propose each LL to use R=\text{2}$ as the constant reference signal to its built-in proportional and integral controller. The settings of the control parameters are discussed, and we validate through simulations that the proposed method is able to achieve close-to-Pareto-front throughput. [ABSTRACT FROM PUBLISHER]

To support a tremendous amount of traffic demands via wireless access in 2020 and beyond, limited bandwidth of the licensed bands has been a major obstacle to boosting further the capacity of wireless services. To fundamentally break through this predicament, an emerging technology known as heterogeneous carrier communications has been launched into standardization in the form of licensed-assisted access (LAA) to the unlicensed bands. Integrating the heterogeneous cloud radio access networks and carrier aggregation, and although LAA-empowered cellular networks gain wider bandwidth from the unlicensed bands, communications may suffer from intersystem interference. To avoid interference, listen-before-talk has been designated as a mandatory function; however, it leads to significant challenges of the hidden-terminal problem. To address this open issue in LAA, in this paper, we consequently propose a resource-optimal scheme using a minimum amount of replicated radio resources to achieve the most essential latency guarantees for real-time applications. To further support non-real-time applications, a new resource control as well as the mathematical architecture inspired by so-called political communications is proposed to further maximize the throughput of packet delivery. Our scheme not only optimizes resource utilization in time and spatial domains but also suggests optimum energy efficiency and computation efficiency, to successfully deploy cellular networks on the unlicensed bands. [ABSTRACT FROM PUBLISHER]

Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave well, a joint spectrum sensing and resource allocation (JSSRA) scheme in a CRN is proposed in this paper. The JSSRA problem is formulated as a weighted-proportional-fairness-based resource-allocation optimization problem under the constraint that the primary user (PU) network is sufficiently protected. The problem is decomposed into two subproblems, namely, the resource allocation subproblem and cooperative SU number decision subproblem, which are solved by the Lagrangian dual algorithm and the brute-force algorithm, respectively. Moreover, a user-selection method based on reinforcement learning is presented to select reliable SUs for cooperative spectrum sensing (CSS). In addition, the SU's trust degree is updated according to its behavior in CSS and is used in the sensed resource-allocation process. The key point of our proposed scheme is to make SUs improve the sensing reliability and prevent SUs from behaving maliciously by an incentive mechanism. Comprehensive performance evaluation is conducted by computer simulation. It is shown that the proposed JSSRA scheme deals with the SSDF attack well in cooperative sensing process to improve system robustness and achieves a significant system utility gain in resource allocation. [ABSTRACT FROM PUBLISHER]

In this paper, we present a precise comprehensive analysis of the aggregate interference $I$ generated from an underlay network of cognitive radio (CR) nodes employing several transmit power control and receiver association schemes. Importantly, we consider spatial randomness by modeling CR transmitter nodes and receiver nodes as two independent Poisson point processes (PPPs). For the cognitive nodes, we investigate receiver association based on the distance or the instantaneous received power and power control based on the maximum possible transmitter–receiver distance, fixed or location-dependent cutoff power levels, feedback from the primary system, or the maximum number of available receivers. For each of these schemes, the exact moment generating function (mgf) and mean of aggregate $I$ power are derived for links with Rayleigh fading and exponential path loss. The resulting primary outage and the probability of secondary transmitter cutoff are also derived. Numerical results show that the secondary power thresholds and node densities significantly affect the aggregate $I$, the primary receiver (PR) outage, and the secondary transmitter cutoff arising from the different schemes. [ABSTRACT FROM PUBLISHER]

In fifth-generation (5G) wireless networks, heterogeneous networks (HetNets) are used to improve capacity and users' densification. However, to rapidly deploy a large number of femto base stations (BSs) in a cost-efficient manner, they should be connected to the core network through residential broadband links. As such, different femto BSs may have different backhaul capacities, which should be taken into consideration when macro BSs offload traffic to femto BSs. Furthermore, users offloaded to femto BSs can be severely interfered by the macro BSs if macro and femto BSs transmit at the same time in the downlink. This interference can be avoided by proper transmission time scheduling. In view of the problem, this paper proposes a novel scheme to jointly perform traffic offloading and time fraction allocation (TOTFA) to ensure proportional fairness in throughput among the users. The proposed scheme, called TOTFA maximizes the weighted sum of the logarithm of user throughput, subject to constraints imposed by the backhaul capacity. Simulation results show that TOTFA can improve aggregated throughput up to 100% compared with a baseline scheme when the backhaul link capacity is 1.25 Mb/s. Over a range of different backhaul capacities, the average throughput improvement is 45%. [ABSTRACT FROM PUBLISHER]

In this paper, spectrum-sharing technology is integrated into cellular systems to improve spectrum efficiency. Macrocell users are primary users (PUs), whereas those within local cells, e.g., femtocell users, or desiring cost-effective services, e.g., roamers, are identified as secondary users (SUs). The SUs share the spectrum resources of the PUs in an underlay way; thus, the transmit power of a secondary is strictly limited by the primary's tolerable interference power. Given such constraints, a cooperative relaying transmission between an SU and the macrocell base station (BS) is necessary. To guarantee the success of dual-hop relaying and avoid multihop relaying, a new cooperative paradigm is proposed, where an idle PU (instead of a secondary, as assumed in general) in the vicinity of a target SU is chosen to serve as a relaying node, due to the fact that any PU can always transmit to the macrocell BS directly. Moreover, a two-way relaying strategy is applied at the chosen relaying node to further improve spectral efficiency. Our results demonstrate that the proposed system is particularly suitable for delay-tolerant wireless services with asymmetric downlink/uplink traffic, such as e-mail checking, web browsing, social networking, and data streaming, which are the most popular applications for SUs in spectrum-sharing cellular networks. [ABSTRACT FROM PUBLISHER]

This paper studies the performance of overlay device-to-device (D2D) communication links via carrier-sense multiple access (CSMA) protocols. We assume that the D2D links have heterogeneous rate requirements and different willingness to pay, and each of them acts nonaltruistically to achieve its target rate while maximizing its own payoff. Spatial reuse is allowed if the links are not interfering with each other. A noncooperative game model is used to address the resource allocation among the D2D links, at the same time leveraging on the ideal CSMA network (ICN) model to address the physical channel access issue. We propose a Stackelberg game in which the base station (BS) in the cellular network acts as a Stackelberg leader to regulate the individual payoff by modifying the unit service price so that the total D2D throughput is maximized. The problem is shown to be quasi-convex and can be solved by a sequence of equivalent convex optimization problems. The pricing strategies are designed so that the network always operates within the feasible throughput region. The results are verified by simulations. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the problem of dynamic spectrum access for small-cell networks using a graphical game approach. Compared with existing studies, we take the features of different cell loads and local interference relationship into account. It is proven that the formulated spectrum access game is an exact potential game (EPG) with the aggregate interference level as the potential function, and the Nash equilibrium (NE) of the game corresponds to the global or local optima of the original optimization problem. A lower bound of the achievable aggregate interference level is rigorously derived. Finally, we propose an autonomous best response (BR) learning algorithm to converge toward its NE. It is shown that the proposed game-theoretic solution converges rapidly, and its achievable performance is close to the optimum solution. [ABSTRACT FROM PUBLISHER]

A fundamental problem for signal processing in wireless communications is the separation of multiple signals/users from their mixture. The problem is simpler if they are nonoverlapping in either the time domain or the frequency domain. Two signals may be overlapping in both time and frequency, but they can still be easily separated if they are uncorrelated (orthogonal), as in code-division multiple-access (CDMA) systems. It may be interesting to know that two signals may be overlapping in both the frequency and time domains and not orthogonal to each other, but they can still be separated if each autocorrelation function at the receiver is separable in the time-lag domain. In this paper, we will show how noise-loop (NL) modulation, which was originally thought to produce security at the physical layer, can be used to effectively separate uncoordinated/nonorthogonal users sharing the same time and frequency interval. To show the potential of the NL multiple-access (NLMA) scheme, the theoretical analysis is carried out and compared with simulations. In particular, together with the error probability, a new figure of merit is derived: the multiuser efficiency index. It can be shown that the NLMA scheme is able to distinguish the bit stream of the users, regardless of their number. In addition, the capacity region of the NLMA scheme is derived and compared with the conventional CDMA scheme. All of the aforementioned features, together with the intrinsic security, make the NL an interesting scheme for wireless technology. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate an unmanned aerial vehicle (UAV) communication system, where the trajectories of multi-UAVs are designed for the data collection mission of IoT nodes. We aim at minimizing the mission time with constraints of UAV’s maximum speed and acceleration, the collision avoidance, and communication interference among UAVs. We propose a three-step approach to solve this problem, which is based on the K-means algorithm, and Deep Reinforcement Learning (DRL) with a distributed manner and a centralized manner. The mutual influences like collision avoidance and interference among UAVs are explicitly expressed in our algorithm. Numerical results show the advantage of our proposed approach. [ABSTRACT FROM AUTHOR]

This paper deals with the joint design problem of transmit waveform and receive filter for the robust detection of ground moving target with multiple-input multiple-output Space time adaptive processing (MIMO- STAP) radar in the presence of target and clutter uncertainties. With the prior knowledge of target and clutter statistics, the averaged signal-to-interference-plus-noise ratio (SINR) is formulated as a figure of merit to maximize. The robust joint design problems for the continuous and discrete phase cases, respectively, are formulated with the constant-modulus and similarity constraints. Then, an efficient iterative algorithm is developed for improving the SINR. Specifically, each iteration of the proposed algorithm involves the generalized eigenvalue decomposition to optimize the receive filter, while a nested iterative procedure involving Dinkelbach’s framework and alternating direction penalty method (ADPM) algorithm to design transmit waveform. The proposed algorithm can achieve higher SINR with reduced computational load compared to the recently developed ones. Numerical examples demonstrate the effectiveness of the proposed method for the robust detection of moving target in MIMO-STAP radar. [ABSTRACT FROM AUTHOR]

Sixth generation mobile networks (6G) may experience a huge evolution on vertical industry scenarios, where deep edge networks ($\mathbf{D}\mathrm{E}\mathrm{N}\mathrm{s}$) become an important network structure for the intelligent resource management of computing, caching and communications (3 C). In this paper, we propose two pervasive scenarios including single edge scene and multiple edge scenes for deep integration of wireless communications and computation depending on real-time adaptive collaboration. Specifically, in the single edge scenario, a novel deep reinforcement learning (DRL)-based framework is invoked for collaboratively optimizing the task scheduling, transmission power and CPU cycle frequency under metabolic channel conditions. Meanwhile, in order to alleviate interference in multiple edge scenarios, we propose a multi-agent aided deep deterministic policy gradient (MADDPG) algorithm to minimize total energy consumption and latency. Numerical experiments demonstrate these methods have substantial performance improvement in terms of saving system’s total overhead (i.e., energy consumption and delay) upon considering the task scheduling, transmission power, channel mutual interference and CPU cycle frequency against other conventional benchmarks. [ABSTRACT FROM AUTHOR]

In this paper, an aerial heterogeneous wireless network consists of a high altitude platform (HAP) and low altitude platforms (LAPs) as aerial base stations (ABSs) in a downlink orthogonal division multiple access (OFDMA) transmission is investigated. Two types of spectrum sharing, including spectrum underlay access (SUA) and spectrum overlay access (SOA) are employed to evaluate the inter-tier interference. Distributed problem formulation and solving method are used to reduce the computational complexity, communication overhead and system latency. Subcarrier assignment and power allocation in spectral efficiency (SE), energy efficiency (EE) and transmission power optimization problems are accomplished by the proposed two-layer algorithm. In the proposed algorithm, first, subcarrier assignment based on constraints of the optimization problems is carried out to cover both SUA and SOA with low computational complexity. Second, the proposed algorithm performs power allocation. The simulation results show the relation between spectrum reuse and inter-tier interference, such that system SE, EE and the number of served users are maximized when both spectrum reuse and inter-tier interference management are performed together. [ABSTRACT FROM AUTHOR]

Virtual Coupling (VC) is regarded as a breakthrough to the traditional train operation and control for improving the capability and flexibility in railways. It brings benefits as trains under VC are allowed to operate much closer to one another, forming a virtually coupled train set (VCTS). However, the safe and stable spacing between trains in the VCTS is a problem since there are no rigid couplers to connect them into a fixed formation, especially in high-speed scenarios. Due to the close spacing, the interference between trains becomes non-negligible as various maneuvers of the preceding train can significantly affect driving behaviors of the following train; this results in fluctuating spacing and therefore an unstable VCTS. Aiming at minimizing the interference and maintaining constantly safe spacing between trains in the VCTS, this paper presents a distributed model predictive control (DMPC) approach for solving the high-speed VCTS control problem. Particularly, the proposed control method focuses on the feasibility and stability of this problem, with considerations of the coupled constraint of safety braking distance and the individual constraints of speed limit variations and restricted traction/braking performance. To guarantee feasibility and stability, the terminal controller and invariant set of the DMPC are designed. For rigor, sufficient conditions of feasibility and stability are mathematically proved and derived. Based on the data of the Beijing-Shanghai high-speed railway line, numerical experiments are conducted to verify the correctness of derived sufficient conditions and the effectiveness of the proposed control method under interference and disturbances. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communication is an emerging paradigm that can improve system capacity and spectral efficiency by using cooperative communication coexisting with cellular networks. In spite of these advantages, D2D communication suffers from unfair resource usage, security risks posed by eavesdroppers, and limited energy storage. To deal with these issues, in this paper, we propose a resource allocation algorithm to maximize the security-aware energy efficiency (EE) for D2D users (DUs) in a simultaneous wireless information and power transfer (SWIPT)-enabled D2D communication system with $\alpha$ fairness, where multiple random eavesdroppers are present. In particular, we formulate a multi-objective resource allocation problem by jointly optimizing the transmit power, power-splitting (PS) factors of DUs, and the sub-channel allocation factor under multiple constraints, including the maximum interference power for each cellular user, the maximum transmit power of each DU, the PS factor, and the integer sub-channel assignment. To solve the non-convex problem, an iterative algorithm is developed to obtain the sub-optimal solution. Simulation results verify that the proposed algorithm outperforms benchmark algorithms in terms of balancing secrecy EE and fairness. [ABSTRACT FROM AUTHOR]

In ultra-dense cellular networks (UDNs) with user/control plane(U/C) splitting, frequent handovers in user planes are unavoidable, which seriously degrades the transmission control protocol (TCP) throughput of mobile station (MS). To enhance the TCP throughput in UDNs, this paper proposes an intelligent recommendation-based user plane handover scheme. Firstly, based on intelligent recommendation algorithms, a mobility prediction algorithm called content-based collaborative hybrid filters (CCHF) is proposed to predict the target small base station (SBS). When the MS moves into the cell-edge of the source SBS, it can pre-access the predicted target SBS and set up connections to the predicted target SBS and the source SBS simultaneously. This is the proposed CCHF-dual-handover scheme. With an accurate prediction and a simultaneous connection, CCHF-dual-handover can present enhanced signal to interference and noise ratio (SINR) at cell-edge, reduced handover interruption ratio (HIR), and improved MS’s TCP throughput. Moreover, TCP throughput of CCHF-dual-handover is analyzed to show the impact of various key parameters (such as MS’s velocity and pre-access threshold). Finally, simulations are carried out to evaluate the performance of the proposed CCHF-dual-handover. Given random trajectory, the prediction accuracy using CCHF is increased by more than 100% compared with existing prediction algorithms. Given accurate prediction, the CCHF-dual-handover can improve the TCP throughput by up to 150% compared with that of existing handover schemes. [ABSTRACT FROM AUTHOR]

In urban UAV networks, UAVs deployment locations and air-to-ground (AtG) communication links will possibly conflict with densely located buildings, which exacerbate network irregularity and make interference management more complicated. This paper proposes interference coordination via power control under 3D blockage effects in urban environments, where buildings are distributed according to Boolean model with heights ($H_k$) followed Rayleigh distribution. Specifically, a dynamic UAV group (UAVG) is organized to serve each user for interference coordination, which consists several nearest visible UAVs with line-of-sight (LOS) connections considering buildings blockage effects, and the modified distribution from user to its nearest unblocked UAV is derived. Power control is executed in UAVG where adjacent interfering UAVs within the group will mute their transmission for interference mitigation, and optimal UAVG radius coefficient $\mu$ is obtained, which reveals the trade-off between interference mitigation and resource utilization. Leveraging stochastic geometry, theoretical expressions of network metrics are derived with Nakagami- $m$ fading assumption, including network coverage probability and network connectivity. Analytical results show that in urban city scenario, comparing with traditional terrestrial networks, coverage performance can achieve 4.1× gain by deploying UAVs with optimal height, and achieve additional 26 $\%$ gain with respect to scenarios where power control is disabled. [ABSTRACT FROM AUTHOR]

In an ultra-dense network (UDN), how to associate the mobile user equipments (UEs) with the appropriate low power nodes (LPNs) is a very essential and challenging problem, especially when the UEs are moving and may suffer from frequent handovers. In this paper, the UE association problem is investigated from a long-term perspective, where the UE's mobility pattern, i.e., the moving velocity and direction, is taken into consideration. To predict the UE's positions based on their previous activity data, a practical scheme, i.e., the classification and batch online learning method (CBOM), is proposed for achieving the UE's velocity and direction transition matrices. Then the UE association problem with the objective of maximizing the UEs’ expected achievable rate while minimizing the number of handovers is formulated. Since the proposed problem is a NP-hard mixed integer nonlinear programming problem, we reformulate it into a matching game, and propose a mobility-based long-term matching game algorithm to find the near-optimal solutions. We prove that our proposed algorithm is convergent and has low computational complexity. Simulation results show our two proposed schemes outperform the existing schemes in terms of the achieved data rate, the number of handovers, and the overall system utility. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAVs) are emerging as important users of next-generation cellular networks. By operating in the sky, UAV users experience very different radio conditions than terrestrial users, due to factors such as strong Line-of-Sight (LoS) channels (and interference) and Base Station (BS) antenna misalignment. As a consequence, the UAVs may experience significant degradation to their received quality of service, particularly when they are moving and are subject to frequent handovers. The solution is to allow the UAV to be aware of its surrounding environment, and intelligently connect into the cellular network taking advantage of this awareness. In this paper we present REgression and deep Q-learning for Intelligent UAV cellular user to Base station Association (REQIBA), a solution that allows a UAV flying over an urban area to intelligently connect to underlying BSs, using information about the received signal powers, the BS locations, and the surrounding building topology. We demonstrate how REQIBA can as much as double the total UAV throughput, when compared to heuristic association schemes similar to those commonly used by terrestrial users. We also evaluate how environmental factors such as UAV height, building density, and throughput loss due to handovers impact the performance of our solution. [ABSTRACT FROM AUTHOR]

This paper studies the integration of the newly-emerged intelligent reflecting surface (IRS) technology into non-orthogonal multiple access (NOMA)-based wireless powered communication networks (WPCNs). We consider two WPCNs which communicate with a common hybrid access point (HAP), where there exists two types of devices in each WPCN, namely information receiving device (IRD) and harvest-then-transmit device (HTTD). Downlink communication from the HAP to IRDs, downlink energy transfer (ET) from the HAP to HTTDs, and uplink information transmission (IT) from the HTTDs to the HAP are assisted by two IRSs, one in each WPCN. Under this setup, we propose efficient algorithms to optimize reflection coefficients, beamforming vectors, and resource allocation for the sake of uplink sum-rate maximization, taking into account the minimum rate requirement at the IRDs. Numerical results show the considerable performance gain of the proposed NOMA-based scheme as compared to the conventional orthogonal multiple access (OMA)-based counterpart. [ABSTRACT FROM AUTHOR]

This paper applies combinatorial optimization techniques to improve the downlink transmission to multiple users in a network with N cells, where intercell interference is a performance-limiting factor. A fair distribution of the signal-to-interference-plus-noise ratio (SINR) is desirable. A well-known technique to get a fair (balanced) SINR is max–min unicast beamforming (MBF). However, in a multicell network, there are conditions where MBF can result in a low balanced SINR. This happens if, e.g., two users are geographically close together and served by two base stations (BSs) from, e.g., two different interfering sectors. Then, the mutual interference among the two links will be large, and the balanced SINR among all jointly optimized links decreases. Therefore, the users must be scheduled such that these situations are avoided. In this paper, smart selection of active beams to avoid intercell interference is called beam scheduling and leads to a combinatorial optimization problem. This paper proposes a graph-theory-based problem that is closely related to the beam scheduling problem. The proposed algorithms maximize the sum rate or the minimum SINR among all users and slots. For the two-cell case, an optimal algorithm exists. In the N > \2-cell case, the beam scheduling problem is proven to be NP-hard. Based on the close relation between the beam scheduling problem and the multidimensional assignment problem (MAP), this paper presents suboptimal algorithms for N > \2 to maximize either the sum rate or the minimum SINR among all users and slots. The performance gain in terms of the mean sum rate or the minimum SINR is significant compared with random scheduling. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the outage behavior of a dual-hop opportunistic decode-and-forward (DF) relay system with cochannel interference (CCI) at both the relay and the destination. The source–relay and relay–destination channels and the interferers' channels at both the relay and the destination nodes are assumed to follow Nakagami-m distribution. Exact closed-form expressions for the outage probability for both independent nonidentically distributed (i.n.d.) and independent identically distributed (i.i.d.) cases of interferers' channels are derived in this paper. Furthermore, the system behavior at high SNR values is studied via deriving the asymptotic outage probability, and hence, the diversity order and the coding gain are characterized. Our results show that the cochannel interferers do not reduce the diversity gain of the system; instead, they degrade the outage performance by affecting the coding gain of the system. The accuracy of the analytical results is supported by Monte Carlo simulations. [ABSTRACT FROM PUBLISHER]

This paper investigates user cooperation diversity systems with decode-and-forward (DF) selection relaying over nonidentical shadowed Nakagami/shadowed Nakagami channels in cellular networks. The outage probability and the system spectral efficiency are evaluated as a function of a cochannel reuse factor and compared with multireceive (Rx) antenna systems for omnidirectional and sectorized cells in both the uplink and the downlink. The results of this paper show that the system spectral efficiency of the proposed system shows comparable performance with that of the single-Rx antenna system, and the outage probability of the system outperforms that of the dual-Rx antenna system in a particular region of the cell with respect to the relay location. The particular region shows that the DF cooperative diversity provides better performance in the uplink than in the downlink, but unlike in the downlink, the impact of cochannel interference (CCI) on the relay in the uplink degrades system performance, in spite of the cell sectorization. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the beamformer design of the energy-efficient downlink multicast cloud radio access network (C-RAN) with the compression and data-sharing strategies, respectively. With the imperfect channel state information, we aim to maximize the worst-case energy efficiency (EE), which is defined as the ratio of the sum of worst-case group rates to the total power consumption of the network. The formulated problems for both strategies are non-convex and challenging to solve. In order to find the solutions, we develop a two-layer iterative algorithm that recast the formulated problems as a series of convex quadratic matrix inequality problems which can be solved by the generated Augmented Lagrangian method. The convergence of the proposed algorithms is proved via both analytical and simulated ways, and the effectiveness of them on improving EE is also validated. Moreover, through the comparison of the two transmission strategies considered, we find that the compression strategy can achieve higher worst-case EE than the data-sharing strategy in most scenarios, except for the case with low rate requirement in small-size network. Our conclusions can be used as meaningful references for the practical system design. [ABSTRACT FROM AUTHOR]

With the increasing penetration of smart devices, device-to-device (D2D) communications offer a promising paradigm to accommodate the ever-growing mobile video traffic and unremitting demands for fast content distribution. The redundant storage and communication capacities of smart devices can be exploited for collaborative content caching and distribution. Such united resources at the network edge can serve end users with low delivery cost and high performance. In this paper, we analyze a heuristic distance-based scheme, which appropriately pairs a device requesting a content item with a cache device within a collaboration distance and providing the requested content. An analytical framework is developed to derive the optimal collaboration distance so as to maximize the likelihood that the paired cache devices successfully fulfill the content requests. The simulation results validate the analytical framework and the effectiveness of the heuristic distance-based scheme for D2D-assisted content distribution. We also investigate the effects of various system parameters on the performance in terms of expected satisfaction probability. [ABSTRACT FROM AUTHOR]

The demand for mobile services is growing aberrantly, which provides both challenges and opportunities for wireless networks. Wireless network virtualization is suggested as a key progression path for enhancing the capacity and resource utilization in the forthcoming fifth-generation mobile networks. In this paper, a software-defined network (SDN) enabled cloud radio access network (C-RAN) framework is proposed for enabling spectrum auction with a two-tier architecture support. In Tier-I, several remote radio heads (RRHs) are introduced to act as the secondary service providers to provide services to its small cell users (SUEs) by exploiting the purchased underutilized or idle resources from the primary service provider in Tier-II. Specifically, in order to maintain quality-of-service requirements of the SUEs, the revenue maximization problem for the RRHs is formulated by considering the user association, band assignment, interference management, and budget allowance. In Tier-II, an SDN-enabled spectrum auction mechanism is proposed for maximizing the social welfare based on the SUEs’ service requirements of all participating RRHs from Tier-I. In this auction mechanism, the bipartite graph is utilized to determine the socially optimal winners and the price charging scheme is proposed inspired by the well-known Vickrey–Clarke–Groves auction method. Simulation results reveal the performance and the benefits of the proposed SDN-enabled spectrum auction mechanism under different scenarios. [ABSTRACT FROM AUTHOR]

The increasing demand for rich multimedia services and the emergence of the Internet of Things (IoT) pose challenging requirements for the next-generation vehicular networks. Such challenges are largely related to high spectral efficiency and low latency requirements in the context of massive content delivery and increased connectivity. In this respect, caching and non-orthogonal multiple access (NOMA) paradigms have been recently proposed as potential solutions to effectively address some of these key challenges. In this paper, we introduce cache-aided NOMA as an enabling technology for vehicular networks. In this context, we first consider the full file caching case, where each vehicle caches and requests entire files using the NOMA principle. Without loss of generality, we consider a two-user vehicular network communication scenario under double Nakagami $\text{-}m$ fading conditions and propose an optimum power allocation policy. To this end, an optimization problem that maximizes the overall probability of successful decoding of files at each vehicle is formulated and solved. Furthermore, we consider the case of split file caching, where each file is divided into two parts. A joint power allocation optimization problem is formulated, where power allocation across vehicles and cached split files is investigated. The offered analytic results are corroborated by extensive results from computer simulations and interesting insights are developed. Indicatively, it is shown that the proposed caching-aided NOMA outperforms the conventional NOMA technique. [ABSTRACT FROM AUTHOR]

Cloud-radio access network (C-RAN) is regarded as a promising solution to manage heterogeneity and scalability of future wireless networks. The centralized cooperative resource allocation and interference cancellation methods in C-RAN significantly reduce the interference levels to provide high data rates. However, the centralized solution is not scalable due to the dense deployment of small cells with fractional frequency reuse, causing severe inter-tier and inter-cell interference turning the resource allocation and user association into a more challenging problem. In this paper, we investigate joint communication and computing resource allocation along with user association, and baseband unit (BBU) and remote radio head (RRH) mapping in C-RANs. We initially establish a queueing model in C-RAN, followed by formulation of two optimization problems for communication [e.g., resource blocks (RBs) and power] and computing [e.g., virtual machines (VMs)] resources allocation with the aim to minimize mean response time. User association along with the RB allocation, interference, and queueing stability constraints are considered in the communication resource optimization problem. The computing resource optimization problem considers BBU-RRH mapping and VM allocation for small cells, constrained to BBU server capacity and queueing stability. To solve the communication and computing resource optimization problem, we propose a joint resource allocation solution that considers a double-sided auction based distributed resource allocation (DS-ADRA) method, where small cell base stations and users jointly participate using the concept of auction theory. The proposed method is evaluated via simulations by considering the effect of bandwidth utilization percentage, signal-to-interference ratio threshold value and the number of users. The results show that the proposed method can be successfully implemented for 5G C-RANs. [ABSTRACT FROM AUTHOR]

In this paper, we analyze cooperative wireless primary networks operating under randomly located interfering nodes (secondary networks). Applying Poisson point processes to modeling of network and interfering node locations, we derive the statistics of signal-to-interference ratio (SIR) under different operational scenarios and show that the SIR statistical models can be viewed as special cases of the H-function distribution. On this basis, we obtain formulas for the average information rates. The presented results are general, and they are applicable to arbitrary fading conditions. [ABSTRACT FROM AUTHOR]

This paper studies positioning fundamentals in low-power wide area (LPWA) Internet of Things (IoT), where those devices with locations known operate as anchors. A tractable model is developed to analyze localizability of target devices. A random scenario is investigated, where anchors are randomly distributed. The model first studies the positioning of a target which can be anywhere. Then, from the point of view of system level, target randomness is further considered so that the study can be conducted over the whole network area. The model has no limitations on area shape but can consider any arbitrary polygonal one. It incorporates the ability for participating anchors to coordinate transmissions, and the interference effect on positioning is theoretically investigated. The model is then extensively validated in comparison with simulations, and the effects of a set of parameter settings are investigated. Compared to the existing positioning performance studies targeting deterministic scenarios, the proposed model considers location randomness through distance distributions using a powerful probabilistic distance-based tool from geometric probability. The model considers both interference and system-related parameter settings, investigating anchor transmission coordination and traffic load, which reveals how participating anchors in general impact positioning performance in LPWA IoT. [ABSTRACT FROM AUTHOR]

In this paper, a novel interference mitigation and power allocation (PA) scheme is investigated for downlink non-orthogonal multiple access (NOMA) with multiple input multiple output (MIMO) technology in heterogeneous networks (HetNets). The proposed scheme, named PA based interference alignment and coordinated beamforming (PA-IA-CB), consists of two stages. The first stage applies two steps of IA-CB; one step for canceling the inter-cluster and the co-tier interference among small cells, whereas the other step deals with the inter-cluster interference within the macro cell. In the second stage, the cross-tier interference is proposed to be managed by properly handling the allocated power to the macro base station (MBS) and the small base stations (SBSs). The PA problem is modeled as a non-cooperative game between the MBS and the SBS with the aim of increasing the system sum rate. Simulation results verify the efficiency of the proposed technique in terms of total system sum rate and outage probability compared to the conventional schemes. [ABSTRACT FROM AUTHOR]

The carrier frequency offset (CFO) on the orthogonal waveforms such as orthogonal frequency division multiplexing and offset quadrature amplitude modulation filter-bank multi-carrier (QAM-FBMC) has been well studied. However, the impact of the CFO on the QAM-FBMC systems is more complicated because of non-orthogonal prototype filters. The unavoidable interference from the non-orthogonality makes pilot signal design difficult and makes it hard to estimate the CFO accurately. In this paper, we discover the impact of the CFO on QAM-FBMC systems, evaluate the procedures of the basic CFO estimation methods, and analyze the performances of the CFO estimations. For the integer part estimation of CFO, we propose the design of pilot symbol that has a prominent peak at pilot subcarrier location in the up-sampled frequency domain. For the fractional part estimation, we formulate the basic CFO estimation by using two adjacent pilot symbols, and we analyze the mean-squared error performances with linear approximation and Cramer–Rao lower bound. We compare the performance of the CFO estimator and analytic approach in the additive white Gaussian noise and the pedestrian channel and show that the proposed estimator works well in the non-orthogonal QAM-FBMC systems. [ABSTRACT FROM AUTHOR]

We consider a two-way half-duplex relaying system where multiple pairs of single-antenna users exchange information assisted by a multiple-antenna relay. Taking into account the practical constraint of imperfect channel knowledge, we study the achievable sum spectral efficiency (SE) of the amplify-and-forward protocol, assuming that the relay employs maximum ratio processing. We derive a closed-form expression for the sum SE for arbitrary system parameters and a large-scale approximation for the sum SE when the number of relay antennas $M$ becomes sufficiently large. In addition, we study how the transmit power reduces with $M$ to maintain a desired SE. Our results show that by using a large number of relay antennas, the transmit powers of the user, relay, and pilot symbol can be scaled down proportionally to $1/M^\alpha$ , $1/M^\beta$ , and $1/M^\gamma$ for certain combinations of $\alpha$ , $\beta$ , and $\gamma$ , respectively. This elegant power scaling law reveals a fundamental tradeoff between the transmit powers of the user/relay and pilot symbol. Finally, capitalizing on the new expressions for the sum SE, novel power allocation schemes are designed to further improve the sum SE. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the interference mitigation problem in two-tier femtocell networks where the femtocell users (FUEs), share the same frequency band with the existing macrocell users (MUEs). More specifically, we formulate the problem as a multiple-leader-multiple-follower non-cooperative hierarchical game to maximize the utilities of both MUEs and FUEs by obtaining the optimal powers. We theoretically prove that there exists a unique Nash equilibrium in the hierarchical game. We then develop a distributed iterative power update strategy to allocate transmission powers efficiently. In addition, we take advantage of dynamic and adaptive pricing and maximum power adaptation to manage the interferences introduced by the transmission powers of FUEs and mitigate the near-far effect in the networks. Furthermore, we propose an admission control algorithm to alleviate the network congestion when the quality of service of FUEs cannot be guaranteed. We carry out extensive simulations to demonstrate that our proposed scheme is able to maximize the utilities of both MUEs and FUEs, while guaranteeing MUEs’ required signal-to-interference-plus-noise ratios and admitting as many FUEs as possible to share network resources. [ABSTRACT FROM AUTHOR]

Wireless access points on Unmanned Aerial Vehicles (UAVs) are being considered for mobile service provisioning in commercial networks. These UAV access points will carry radio infrastructure and will be temporarily deployed in areas of dense user traffic to deal with excess user data demand. In this paper, we analyze the coverage when UAVs act as access points for users on the ground in an urban area. We consider the impact of several UAV placement strategies, either independent of, or responsive to, the locations of the users on the ground. Our analysis allows us to demonstrate how the density of the UAVs in the network will determine whether the UAVs should position themselves closer to user hotspots to improve the received signal strength, or further away from one another to mitigate interference. In addition, we demonstrate how network design parameters such as the UAV height above ground or the antenna beamwidth impact the coverage probability. In addition to simulations, we provide mathematical expressions for the coverage probability, for the scenario where UAVs are positioned directly above the centers of user hotspots. [ABSTRACT FROM AUTHOR]

This paper proposes a new location-based multicasting technique, for dual phase amplify-and-forward (AF) large networks, aiming to improve the security in the presence of non-colluding passive eavesdroppers. These eavesdroppers could also be part of this cooperative network as relays. In order to reduce the impact of these eavesdroppers on the network security, we propose a new transmission strategy where, for the first hop of each transmission time, while the destination is jamming, the source randomly chooses a different subset $K$ of the total $T$ relays, to transmit its message toward the destination. For practical implementation, sectoral transmission can be achieved with analog beamforming at the source's side. In the second hop, using the distributed beamforming technique, the $K$ AF relays retransmit the received signal to the destination. We analytically demonstrated that the proposed technique decreases the probability of choosing the same sector that has certain eavesdroppers again, for each transmission time, to $K/T$. Moreover, we also show that the secrecy capacity scaling of our technique is still the same as for broadcasting. Hereafter, the lower and upper bounds of the secrecy outage probability are calculated, and it is shown that the security performance is remarkably enhanced, compared to conventional multicasting technique. [ABSTRACT FROM AUTHOR]

The advancement of integrated millimeter-wave products opens the possibility of leveraging communications in 60-GHz band to meet the unprecedented traffic demand in WLAN. Despite the vast bandwidth available, millimeter-wave signals suffer from high attenuation and weak diffraction ability. Therefore, wireless communication at 60 GHz is characterized by the inherent directivity and susceptibility to blockage. Multiple Access Point (AP) architecture is proposed for 60-GHz WLAN to enhance spatial reuse and survive blockage. In the presence of multiple APs in the network, this paper addresses the important problem of user-AP association and resource allocation. We study three schemes of different complexity and investigate how to maximize user throughput with joint consideration of AP assignment and transmission scheduling. To solve the formulated problem, we propose a branch-and-cut-based solution procedure. We perform a detailed comparative analysis of the three schemes and advocate to use one-shot AP assignment-based scheduling scheme due to its simplicity and good performance. To deal with real-time traffic and human blockage, we propose an online algorithm to implement the one-shot AP assignment-based scheme to avoid frequent service disruption. Our results show that the proposed online algorithm is competitive when compared with the optimal offline algorithm. [ABSTRACT FROM AUTHOR]

This paper deals with an efficient resource allocation algorithm for Wide-Area Low Rate Wireless Personal Area Networks (LR-WPANs), based on the IEEE 802.15.4 m standard. The proposed scheme aims at lowering the spectrum congestion problems and optimizing performance in terms of data packets dropping probability for all the active clusters of end-devices. The algorithm realizes a many-to-one mapping between the sets of LR-WPANs and available access bands (i.e., TV white space bands). It is based on a matching game with externalities and involves two-side preferences, i.e., clusters over bands and bands over clusters, respectively. The procedure provides high resource reuse, adaptation to changes of system conditions, and improvements on quality of service. Furthermore, a post-matching procedure is also discussed to ensure stability of the provided many-to-one matching. Finally, the good behavior of the matching approach is validated by providing performance comparisons with alternative schemes based on the random assignment, the Brelaz graph coloring algorithm applied in a modified form, and potential game strategy. [ABSTRACT FROM AUTHOR]