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As a bandwidth-efficient technique, bit-interleaved coded modulation with iterative demapping and decoding (BICM-ID) has attracted much research attention in the field of wireless communication. In this paper, we put forth a joint design of root-protograph (RP) low-density parity-check (LDPC) codes and BICM-ID, referred to as RP-based BICM-ID (RP-BICM-ID), over block-fading (BF) channels so as to boost the throughput under limited bandwidth. To preserve the full-diversity property of RP codes, we propose an efficient modulation strategy for the RP-BICM-ID system by taking the fading-block length into consideration. We also analyze the outage-probability limit of the RP-BICM-ID systems to establish the fundamental lower-limit on their word-error-rate (WER) performance. Moreover, we conceive a multi-level protograph extrinsic information transfer (ML-PEXIT) algorithm to derive the asymptotic WER and bit error rate (BER) of the RP-BICM-ID systems over BF channels. As a further insight, we develop a novel unequal-error-protection (UEP) bit-to-symbol (B2S) mapping scheme for the RP-BICM-ID systems, which gives rise to an additional performance improvement. Analyses and simulations show that the proposed RP-BICM-ID systems can not only realize desirable spectral efficiency, but also obtain near-outage-limit performance over BF channels. Therefore, the proposed RP-BICM-ID systems are very promising in achieving high-reliability and high-rate transmissions under slow-fading wireless-communication environments. [ABSTRACT FROM AUTHOR]

The broadcast channel with mutual secrecy requirement at the receivers (BC-MSR-R) is a basic model characterizing the physical layer security (PLS) in the down-link of the wireless communication systems, where one transmitter sends two independent messages to two receivers via a broadcast channel, and each receiver can successfully decode his/her intended message and wishes to overhear the other one’s message. This paper studies how to enhance the already existing secrecy rate region of the BC-MSR-R via receivers’ feedback. Specifically, we propose two feedback strategies for the BC-MSR-R, where one uses the feedback to generate pure secret keys protecting the transmitted messages, and the other uses the feedback to generate not only keys but also cooperative messages helping the receivers to improve their decoding performance. Different inner bounds on the secrecy capacity region of the BC-MSR-R with noiseless feedback are constructed according to different feedback strategies, and these bounds are further illustrated by a Dueck-type example. [ABSTRACT FROM AUTHOR]

This paper investigates the secrecy performance of multiple-input multiple-output systems under generalized $\alpha -\mu $ fading conditions. To this end, we focus on two distinct scenarios: 1) the transmitter has knowledge of the channel state information (CSI) of the eavesdropper channel and 2) the transmitter is not aware of the CSI of the wiretap link. By considering transmit antenna selection in the underlying system, we develop closed-form analytical expressions for the lower bound of the secrecy outage probability (SOP) and the probability of the strictly positive secrecy capacity. Furthermore, two novel approaches are proposed to derive an analytical expression of the average secrecy capacity (ASC). First, the ASC is expressed as a function of the average capacity of the desired link and an interaction term regarded as the ASC loss. Second, the ASC is expressed in terms of the average capacities of the desired and eavesdropper links, plus an interaction term that can be regarded as some sort of ASC gain due to the statistical independence between the desired and eavesdropper links. In addition, asymptotic studies of the SOP and the ASC at high signal-to-noise ratio are carried out, which precisely reveal the secrecy diversity and array gains. [ABSTRACT FROM AUTHOR]

Recently, the newly emerging wireless powered communication network (WPCN) has drawn significant interests, where the network nodes are powered by the energy harvested from the radio-frequency (RF) signal. This paper focuses on the widely studied WPCN, where one hybrid sink (H-sink) coordinates the wireless energy/information transmissions to/from a set of one-hop nodes powered by the harvested RF energy only, and aims to minimize the network-throughput constrained H-sink’s energy provision (EP). Specifically, we investigate the performance of two important MAC protocols: time-division multiple access (TDMA) and non-orthogonal multiple access (NOMA). For both the TDMA-based WPCN (T-WPCN) and NOMA-based WPCN (N-WPCN), we first formulate the EP minimization problems as the non-linear optimization problems, then transform them into convex problems, and finally propose an efficient algorithm, which jointly uses the golden-section search and bisection search methods to determine the optimal time allocation of H-sink’s energy transfer and each node’s information transmission as well as the optimal H-sink’s transmit power. Furthermore, for the scenarios where the circuit power is negligible, we first prove that the optimal H-sink’s transmit power is the maximum allowable value, then prove theoretically that the NOMA and TDMA achieve the same EP, and also present a more efficient algorithm for the EP minimization problem. Simulation results demonstrate that the TDMA outperforms NOMA when the circuit power is non-negligible because the circuit energy consumption of NOMA accounts for a large percentage of the total energy consumption. [ABSTRACT FROM AUTHOR]

In the mobile edge computing (MEC) network, the applications of devices can be offloaded to the MEC server via the wireless link and then processed through the computation resource, to satisfy the computation and latency demand. Thus, a two-stage tandem queue is formed in the MEC network, consisting of the transmission queue and computation processing queue. However, the fluctuating wireless channel environment not only leads to the stochasticity of service in the first transmission queue, but also brings random computation task arrival in the second computation processing queue, which makes it difficult to guarantee the end-to-end quality of service (QoS) requirement. In this paper, we firstly derive the effective capacity of MEC with the two-stage tandem queue. Further, we formulate the joint bandwidth and computation resource allocation problem under the statistical QoS guarantee, to maximize the total revenue of network. This problem is proven to be NP-hard by the reduction to the two-dimensional knapsack problem. Then we propose an efficient algorithm based on alternating direction method of multipliers (ADMM) to reduce the computation complexity, where the complicated problem can be decomposed and transformed into some convex subproblems. Simulation results reveal the inherent relationship between the required bandwidth and computation resource in terms of the supported arrival rate and end-to-end delay, and also demonstrate the proposed scheme can achieve better performance than other schemes. [ABSTRACT FROM AUTHOR]

Mobile cloud computing systems, or simply mobile clouds, have attracted tremendous attention because they allow mobile devices with limited computational resources to offload complex computations. However, due to the channel uncertainty and the complexity of a computation task, mobile computation offloading may suffer from poor outage performance that the offloaded task cannot be completed within the desired delay constraint. Thus, how to efficiently identify and overcome the outage bottleneck, which could be used to optimize resource allocation schemes and improve the system performance effectively is an open problem. In this paper, we shall develop a unified framework that minimizes the overall outage probability in various mobile computation offloading scenarios. More specifically, the outage bottleneck is defined and identified by adopting asymptotic analysis, without any need of the accurate outage probabilities in both transmissions and computations. To overcome the outage bottleneck, resource pairing, matching, and allocation policies are investigated. Both theoretical analysis and numerical results show that the outage bottleneck relies on not only the availability of spectrum and computation resources but also the probability distributions of computation complexities of the computation tasks. [ABSTRACT FROM AUTHOR]

Full-duplex (FD) jamming transceivers recently have been shown to enhance the information security of wireless communication systems by simultaneously transmitting artificial noise (AN) while receiving information. In this paper, we investigate whether FD jamming can also improve the system’s secrecy energy efficiency (SEE) in terms of securely communicated bits per Joule when considering the additional power used for jamming and self-interference (SI) cancellation. Moreover, the degrading effect of the residual SI is also taken into account. In this regard, we formulate a set of SEE maximization problems for a FD multiple-input-multiple-output multiple-antenna eavesdropper (MIMOME) wiretap channel, considering both cases where exact or statistical channel state information (CSI) is available. Due to the intractable problem structure, we propose iterative solutions in each case with a proven convergence to a stationary point. Numerical simulations indicate only a marginal SEE gain, through the utilization of FD jamming, for a wide range of system conditions. However, when SI can efficiently be mitigated, the observed gain is considerable for scenarios with a small distance between the FD node and the eavesdropper, a high signal-to-noise ratio (SNR), or for a bidirectional FD communication setup. [ABSTRACT FROM AUTHOR]

In this paper, we optimize the energy efficiency (bits/s/Hz/J) of device-to-multi-device (D2MD) wireless communications. While the device-to-device scenario has been extensively studied to improve the spectral efficiency in cellular networks, the use of multicast communications opens the possibility of reusing the spectrum resources also inside the groups. The optimization problem is formulated as a mixed integer non-linear joint optimization for the power control and allocation of resource blocks (RBs) to each group. Our model explicitly considers resource sharing by letting co-channel transmission over a RB (up to a maximum of $r$ transmitters) and/or transmission through $s$ different channels in each group. We use an iterative decomposition approach, using first matching theory to find a stable even if sub-optimal channel allocation, to then optimize the transmission power vectors in each group via fractional programming. In addition, within this framework, both the network energy efficiency and the max-min individual energy efficiency are investigated. We characterize numerically the energy-efficient capacity region, and our results show that the normalized energy efficiency is nearly optimal (above 90% of the network capacity) for a wide range of minimum-rate constraints. This performance is better than that of other matching-based techniques previously proposed. [ABSTRACT FROM AUTHOR]

Ambient backscatter has been introduced with a wide range of applications for low power wireless communications. In this paper, we propose an optimal and low-complexity dynamic spectrum access framework for the RF-powered ambient backscatter system. In this system, the secondary transmitter not only harvests energy from ambient signals but also reflects these signals to transmit its modulated data to the receiver. Under the dynamics of the ambient signals, we first adopt the Markov decision process (MDP) framework to obtain the optimal policy for the secondary transmitter, aiming to maximize the system throughput. However, the MDP-based optimization requires complete knowledge of environment parameters, e.g., the probability of a channel to be idle and the probability of a successful packet transmission, that may not be practical to obtain. To cope with such incomplete knowledge of the environment, we develop a low-complexity online reinforcement learning algorithm that allows the secondary transmitter to “learn” from its decisions and then attain the optimal policy. Simulation results show that the proposed learning algorithm not only efficiently deals with the dynamics of the environment but also improves the average throughput up to 50% and reduces the blocking probability and delay up to 80% compared with conventional methods. [ABSTRACT FROM AUTHOR]

In this paper, imperfect feedback-based linear precoding schemes are proposed for multiple-input-multiple-output (MIMO) wireless communication systems, where input symbol streams are encoded by using generalized-orthogonal space-time block codes. The imperfect feedback information drastically degrades the system performance. Therefore, to overcome the effect of erroneous feedback information, error-tolerant weighting (ETW) schemes are implemented by employing diagonal precoder. The communication links are assumed to be Nakagami- $m$ distributed for accurately characterizing practical wireless channels under different fading scenarios. Exact and asymptotic symbol-error-rate (SER) expressions of the considered MIMO system are derived under imperfect feedback with the help of order statistics. The most appropriate values of the transmit weights of the precoder matrix are obtained by minimizing the derived average SER over fixed and adaptive signal-to-noise ratio. Further, we study the trade-off between the proposed optimal and suboptimal feedback-based precoding schemes. Moreover, the ergodic-rate of the ETW schemes is also derived with imperfect feedback for arbitrary MIMO system by using the moment generating function approach. The simulated and analytical results show that a significant performance gain is achieved by the ETW schemes as compared to the uniform power allocation and existing precoding techniques under erroneous feedback information. [ABSTRACT FROM AUTHOR]

Backscatter communication (BSC) is being realized as the core technology for pervasive sustainable Internet-of-Things applications. However, owing to the resource limitations of passive tags, the efficient usage of multiple antennas at the reader is essential for both downlink excitation and uplink detection. This paper targets at maximizing the achievable sum-backscattered throughput by jointly optimizing the transceiver (TRX) design at the reader and backscattering coefficients (BCs) at the tags. Since this joint problem is nonconvex, we first present individually optimal designs for the TRX and BC. We show that with precoder and combiner designs at the reader, respectively, targeting downlink energy beamforming and uplink Wiener filtering operations, the BC optimization at tags can be reduced to a binary power control problem. Next, the asymptotically optimal joint-TRX-BC designs are proposed for both low- and high-signal-to-noise ratio regimes. Based on these developments, an iterative low-complexity algorithm is proposed to yield an efficient jointly suboptimal design. Thereafter, we discuss the practical utility of the proposed designs to other application settings, such as wireless powered communication networks and BSC with imperfect channel state information. Finally, selected numerical results, validating the analysis and shedding novel insights, demonstrate that the proposed designs can yield significant enhancement in the sum-backscattered throughput over existing benchmarks. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the problem of power control for streaming variable bit rate (VBR) videos over wireless links. A system model involving a transmitter (e.g., a base station) that sends VBR video data to a receiver (e.g., a mobile user) equipped with a playout buffer is adopted, as used in dynamic adaptive streaming video applications. In this setting, we analyze power control policies considering the following two objectives: 1) the minimization of the transmit power consumption and 2) the minimization of the transmission completion time of the communication session. In order to play the video without interruptions, the power control policy should also satisfy the requirement in which the VBR video data is delivered to the mobile user without causing playout buffer underflow or overflows. A directional water-filling algorithm, which provides a simple and concise interpretation of the necessary optimality conditions, is identified as the optimal offline policy. Following this, two online policies are proposed for power control based on channel side information (CSI) prediction within a short time window. Dynamic programming is employed to implement the optimal offline and the initial online power control policies that minimize the transmit power consumption in the communication session. Subsequently, reinforcement learning (RL)-based approach is employed for the second online power control policy. Through the simulation results, we show that the optimal offline power control policy that minimizes the overall power consumption leads to substantial energy savings compared with the strategy of minimizing the time duration of video streaming. We also demonstrate that the RL algorithm performs better than the dynamic programming-based online grouped water-filling (GWF) strategy unless the channel is highly correlated. [ABSTRACT FROM AUTHOR]

Multi-group multicast beamforming in wireless systems with large antenna arrays and massive audience is investigated in this paper. Multicast beamforming design is a well-known non-convex quadratically constrained quadratic programming (QCQP) problem. A conventional method to tackle this problem is to approximate it as a semi-definite programming problem via semi-definite relaxation, whose performance, however, deteriorates considerably as the number of per-group users goes large. A recent attempt is to apply convex-concave procedure (CCP) to find a stationary solution by treating it as a difference of convex programming problem, whose complexity, however, increases dramatically as the problem size increases. In this paper, we propose a low-complexity high-performance algorithm for multi-group multicast beamforming design in large-scale wireless systems by leveraging the alternating direction method of multipliers (ADMM) together with CCP. In specific, the original non-convex QCQP problem is first approximated as a sequence of convex subproblems via CCP. Each convex subproblem is then reformulated as a novel ADMM form. Our ADMM reformulation enables that each updating step is performed by solving multiple small-size subproblems with closed-form solutions in parallel. Numerical results show that our fast algorithm maintains the same favorable performance as state-of-the-art algorithms but reduces the complexity by orders of magnitude. [ABSTRACT FROM PUBLISHER]

This paper proposes an encoding/decoding framework for achieving the optimal channel capacities of the two-user broadcast channel where each user (receiver) has the message targeted for the other user (receiver) as side information. Since the link qualities of the channels from the base station to the two users are different, their respective single-user non-broadcast channel capacities are also different. A goal is to simultaneously achieve/approach the single-user non-broadcast channel capacities of the two users with a single broadcast transmission by applying network coding. This is referred to as the rate-diverse wireless network coding problem. For this problem, this paper presents a capacity-achieving framework based on linear-structured nested lattice codes. The significance of the proposed framework, besides its theoretical optimality, is that it suggests a general design principle for linear rate-diverse wireless network coding going beyond the use of lattice codes. We refer to this design principle as the principle of virtual single-user channels. Guided by this design principle, we propose two implementations of our encoding/decoding framework using practical linear codes amenable to decoding with affordable complexities: the first implementation is based on Low Density Lattice Codes (LDLC) and the second implementation is based on Bit-interleaved Coded Modulation (BICM). These two implementations demonstrate the validity and performance advantage of our framework. [ABSTRACT FROM PUBLISHER]

This paper investigates and optimizes the performance of simultaneous wireless information and power transfer (SWIPT) in wireless sensor networks over Nakagami- $m$ fading channels. In the considered system, there is one mobile reader ( $R$ ), which is equipped with one transmit antenna and one receive antenna, and a group of passive sensors. The information delivery includes two stages: 1) $R$ broadcasts a command with radio-frequency energy to the sensors, which adopt time splitting (TS)/power splitting (PS) schemes to harvest energy and 2) sensors deliver their information to $R$ over orthogonal channels by using the harvested energy. In this paper, we propose a unified framework to study and optimize the impact of SWIPT on the system performance with both TS and PS schemes. First, we characterize the probability density function and cumulative distribution function of the signal-to-interference-plus-noise-ratio in high signal-to-noise ratio region, then we study the outage and ergodic capacity performance of the backward links. The approximated closed-form expressions for the outage probability and ergodic capacity are derived and validated through Monte Carlo simulations. Finally, we also evaluate the energy efficiency of the target system, and propose an optimal splitting scheme for TS and PS to maximize the throughput of the target system. [ABSTRACT FROM PUBLISHER]

In this paper, we introduce a new full-duplex wireless communication system, named ReflectFX, that relies on backscatter modulation. This paper offers a new concept for two-way wireless communication: rather than avoiding self-interference as in half-duplex, or combatting self-interference as in conventional full-duplex, nodes will re-use the received interfering radio-carrier waves to transfer information. The electromagnetic waves are modulated and reflected by the same antenna that receives them. We consider two nodes, a base-station and an end-user, that wish to exchange data over a wireless Rayleigh fading channel with additive white Gaussian noise. With ReflectFX, the end-user receives a self-interference free signal. We improve the transmission range of ReflectFX by adding negative resistance to the end-user load. We derive an expression for the overall achievable throughput and ergodic capacity of ReflectFX. Simulation results show that ReflectFX outperforms both conventional full-duplex and half-duplex. [ABSTRACT FROM PUBLISHER]

The Gamma–Gamma distribution has recently emerged in a number of applications ranging from modeling scattering and reverberation in sonar and radar systems to modeling atmospheric turbulence in wireless optical channels. In this respect, assessing the outage probability achieved by some diversity techniques over this kind of channels is of major practical importance. In many circumstances, this is related to the difficult question of analyzing the statistics of a sum of Gamma–Gamma random variables. Answering this question is not a simple matter. This is essentially because outage probabilities encountered in practice are often very small, and hence, the use of classical Monte Carlo methods is not a reasonable choice. This lies behind the main motivation of this paper. In particular, this paper proposes a new approach to estimate the left tail of the sum of Gamma–Gamma variates. More specifically, we propose robust importance sampling schemes that efficiently evaluates the outage probability of diversity receivers over Gamma–Gamma fading channels. The proposed estimators satisfy the well-known bounded relative error criterion for both maximum ratio combining and equal gain combining cases. We show the accuracy and the efficiency of our approach compared with naive Monte Carlo via some selected numerical simulations. [ABSTRACT FROM PUBLISHER]

Besides designing channel-hopping (CH) sequences, finding good methods of communication rendezvous is important for improving spectral efficiency and alleviating traffic load of cognitive radio (CR) networks. In this paper, new asynchronous-symmetric CH sequences are constructed and their (channel overlap, even-channel-use, and pairwise shift invariance) properties are investigated. Their operations in three transmission scenarios involving different basic collision-avoidance mechanisms are analyzed and compared in terms of maximum time-to-rendezvous, rendezvous-success (RS) rate, and RS variance. This paper shows that the new sequences have shorter period, larger cardinality, and smaller RS variations than other CH sequences, thus supporting greater number of secondary users and more frequent and uniform rendezvous in the CR networks. [ABSTRACT FROM PUBLISHER]

In wireless communication systems, channel state feedback (CSF) is widely used to improve link performance. However, CSF consumes extra system resources and results in transmission overhead. In this paper, we evaluate such resource consumption in terms of bit rate and provide an explicit expression for the lower bound of the CSF overhead. We propose an overhead optimization mechanism under the constraint of channel state reconstruction accuracy. The numerical simulations show that our paper is beneficial to select the optimum CSF parameters, including the average bit number and channel state feedback period. It is also shown that the proposed overhead optimization scheme is able to reduce the system resource consumption with a guaranteed reconstruction accuracy. [ABSTRACT FROM AUTHOR]

Multi-channel (MC) optical wireless communication (OWC) systems employing wave-division multiplexing for outdoors free-space optical communications, or multi-user time-division multiple access for indoors visible-light communications, e.g., can be modeled as parallel channels. Multi-input multi-output OWC systems can also be transformed, possibly with some performance loss, to parallel channels using pre-/post-coding. Studying the performance of such MC-OWC systems requires characterizing the capacity of the underlying parallel channels. In this paper, upper and lower bounds on the capacity of constant parallel OWC channels with a total average intensity constraint are derived. Then, this paper focuses on finding intensity allocations that maximize the lower bounds given channel-state information at the transmitter (CSIT). Due to its nonconvexity, the Karush–Kuhn–Tucker conditions are used to describe a list of candidate allocations. Instead searching exhaustively for the best solution, low-complexity near-optimal algorithms are proposed. The resulting optimized lower bound nearly coincides with capacity at high signal-to-noise ratio (SNR). Under a quasi-static channel model and in the absence of CSIT, outage probability upper and lower bounds are derived. Those bounds also meet at high SNR, thus characterizing the outage capacity in this regime. Finally, the results are extended to a system with both average and peak intensity constraints. [ABSTRACT FROM PUBLISHER]

The emergence of interference alignment (IA) as a degrees-of-freedom optimal strategy motivates the need to investigate whether IA can be leveraged to aid conventional network utility maximization algorithms, which are typically only capable of finding locally optimal solutions. To test the usefulness of IA in this context, this paper proposes a two-stage optimization framework for the downlink of a $G$ -cell multi-antenna network with $K$ users/cell. The first stage of the proposed framework focuses on nulling interference from a set of dominant interferers using IA, while the second stage optimizes transmit and receive beamformers to maximize a network-wide utility using the IA solution as the initial condition. Further, this paper establishes a set of new feasibility results for partial IA that can be used to guide the number of dominant interferers to be nulled in the first stage. Through simulations on specific topologies of a cluster of base stations, it is observed that the impact of IA depends on the choice of the utility function and the presence of out-of-cluster interference. In the absence of out-of-cluster interference, the proposed framework outperforms straightforward optimization when maximizing the minimum rate, while providing marginal gains when maximizing sum rate. However, the benefit of IA is greatly diminished in the presence of significant out-of-cluster interference. [ABSTRACT FROM AUTHOR]

In this paper, we study and analyze cooperative cognitive radio networks with arbitrary number of secondary users (SUs). Each SU is considered a prospective relay for the primary user (PU) besides having its own data transmission demand. We consider a multi-packet transmission framework that allows multiple SUs to transmit simultaneously because of dirty-paper coding. We propose power allocation and scheduling policies that optimize the throughput for both PU and SU with minimum energy expenditure. The performance of the system is evaluated in terms of throughput and delay under different opportunistic relay selection policies. Toward this objective, we present a mathematical framework for deriving stability conditions for all queues in the system. Consequently, the throughput of both primary and secondary links is quantified. Furthermore, a moment generating function approach is employed to derive a closed-form expression for the average delay encountered by the PU packets. Results reveal that we achieve better performance in terms of throughput and delay at lower energy cost as compared with equal power allocation schemes proposed earlier in the literature. Extensive simulations are conducted to validate our theoretical findings. [ABSTRACT FROM AUTHOR]

Today’s mobile data traffic is dominated by content-oriented traffic. Caching popular contents at the network edge can alleviate network congestion and reduce content delivery latency. This paper provides a comprehensive and unified study of caching and delivery techniques in wireless radio access networks (RANs) with caches at all edge nodes (ENs) and user equipments (UEs). Three cache-aided RAN architectures are considered: RANs without fronthaul, with dedicated fronthaul, and with wireless fronthaul. It first reviews in a tutorial nature how caching facilitates interference management in these networks by enabling interference cancelation (IC), zero-forcing (ZF), and interference alignment (IA). Then, two new delivery schemes are presented. One is for RANs with dedicated fronthaul, which considers centralized cache placement at the ENs but both centralized and decentralized placement at the UEs. This scheme combines IA, ZF, and IC together with soft-transfer fronthauling. The other is for RANs with wireless fronthaul, which considers decentralized cache placement at all nodes. It leverages the broadcast nature of wireless fronthaul to fetch not only uncached but also cached contents to boost transmission cooperation among the ENs. The numerical results show that both schemes outperform existing results for a wide range of system parameters, thanks to the various caching gains obtained opportunistically. [ABSTRACT FROM AUTHOR]

Massive machine-type communication (mMTC) is a newly introduced service category in 5G wireless communication systems to support a variety of Internet-of-Things (IoT) applications. In recovering sparsely represented multi-user vectors, compressed sensing-based multi-user detection (CS-MUD) can be used. CS-MUD is a feasible solution to the grant-free uplink non-orthogonal multiple access (NOMA) environments. In CS-MUD, active user detection (AUD) and channel estimation (CE) should be performed before data detection. In this paper, we propose the expectation propagation-based joint AUD and CE (EP-AUD/CE) technique for mMTC networks. The EP algorithm is a Bayesian framework that approximates a computationally intractable probability distribution to an easily tractable distribution. The proposed technique finds a close approximation of the posterior distribution of the sparse channel vector. Using the approximate distribution, AUD and CE are jointly performed. We show by numerical simulations that the proposed technique substantially enhances AUD and CE performances over competing algorithms. [ABSTRACT FROM AUTHOR]

To satisfy the rapidly growing demands of wireless communications, new structures have been proposed for the fifth-generation (5G) mobile communication networks, such as cloud radio access networks (C-RANs), which have advantages including high energy efficiency, large network capacity, and high flexibility. This paper concentrates on the problem of remote radio head (RRH) activation, user association, and power allocation in C-RANs. To tackle the problem with $l_{0}$ norm, we transform it into a mixed-integer nonlinear programming (MINLP) problem. Instead of solving it by centralized solvers, we propose a novel algorithm based on Benders decomposition, which can obtain the optimal solution of the MINLP problem. To solve the primal problem in Benders decomposition efficiently, we adopt the alternating direction method of multipliers (ADMM) to achieve a parallel implementation. To further reduce the complexity of solving the MINLP problem, a distributed two-stage iterative algorithm combining the ADMM and the max-sum algorithm is also proposed. The simulation results demonstrate that the first proposed algorithm can obtain the optimal solution, and the second proposed algorithm outperforms conventional algorithms significantly. [ABSTRACT FROM AUTHOR]

Joint optimal resource allocation and probabilistic caching design is conceived for device-to-device (D2D) communications in a heterogeneous wireless network (HetNet) relying on full-duplex (FD) relays. In particular, popular contents can be cached at user devices and at relays that are located close to users. A user may request the contents of interest from another user via D2D communications and also from a nearby relay equipped with FD radios. If the requested contents are not found in the buffers of other users/relays within the coverage range, users may opt for connecting to the macro base station (MBS) via a relay by using an FD communication. Furthermore, we propose a beneficial mobility-aware coded caching philosophy for D2D communications in the HetNet considered. Especially, we model the mobility pattern of users as discrete random jumps and exploit coded caching for improving the throughput attained. Subsequently, we develop mathematical models for analyzing the throughput in the presence of edge caching, where both the system-level co-channel interference and the FD self-interference are considered. We circumvent the high complexity of stochastic optimization by developing low-complexity optimization. Finally, numerical results are presented to illustrate the theoretical findings developed in this paper and quantify the throughput gains attained. [ABSTRACT FROM AUTHOR]

By supporting asynchronous transmission and flexible subband (SB) setting, filtered orthogonal frequency division multiplexing (f-OFDM) has been identified as one of the most promising waveforms for future wireless communications, which makes the deep investigation on the f-OFDM an urgent mission. Therefore, this paper investigates the downlink interference of asynchronous f-OFDM systems under different SB configurations. We initially classify the overall interference into two categories, termed as the inner-SB and inter-SB interferences. Subsequently, the closed-form expressions for interference and its variances are derived on the basis of interference structures and are then verified via simulations. Some important influencing factors, such as the timing offset between the user of interest and the interfering user, the width of guard band, as well as the choice of SB filter, are simulated and analyzed. Our simulations and comparisons explicitly reveal the interference characteristic of the f-OFDM systems, which will benefit the design of the f-OFDM systems in the future. [ABSTRACT FROM AUTHOR]

A transmission profile refers to a transmission power and a modulation and coding scheme to be used for packet transmissions over a wireless link. The goal of this paper is to develop transmission profile selection policies so as to minimize the average power consumption on a wireless link while satisfying a certain delay constraint given in terms of a delay violation probability. Toward the assessment of profile selection policies, a multi-regime Markov fluid queue model is proposed to obtain the average power consumption and the queue waiting time distribution which allows one to analyze the energy-delay tradeoff in queuing systems for which the packet transmission duration is allowed to depend on the delay experienced by the packet until the beginning of service. Numerical examples are presented with transmission profiles obtained from realistic LTE simulations. Several transmission profile selection policies are proposed and subsequently compared using the analytical model. [ABSTRACT FROM AUTHOR]

Future wireless communication systems face several transceiver hardware imperfections that may significantly degrade their performance. In-phase (I) and quadrature-phase (Q) imbalance (IQI), which causes self-interference effects on the desired signal, is an important and practical example to these impairments. In this paper, a channel state information-assisted dual-hop amplify-and-forward (AF) relaying system in the presence of IQI is analyzed. The error performance of the relevant AF cooperative protocol is firstly studied by considering the traditional maximum likelihood detection (MLD) algorithm as a benchmark. Then, two compensation methods, weighting and zero-forcing, are proposed to mitigate the IQI effects. Finally, an optimal MLD solution is introduced by adapting the traditional MLD technique in compliance with the asymmetric characteristics of the IQI. The system performance is evaluated in terms of average symbol error probability (ASEP) through the computer simulations. The ASEP is calculated analytically for the optimal MLD method as well under the assumption of point-to-point communication, which has been envisioned as an allied technology of the fifth generation (5G) wireless systems, between the source and the relay nodes. A power allocation algorithm is provided for this specific case. The extensive computer simulations and analytical results prove that the proposed optimal MLD method provides the best results. [ABSTRACT FROM AUTHOR]

In this paper, we investigate an unmanned aerial vehicle (UAV) enabled wireless powered communication network, where the UAV with constant power supply first charges all users by transmitting wireless energy to all users simultaneously, and after that all users send their own information to the UAV. Our target is the joint optimization of the time allocation as well as the position of the UAV to make the uplink sum achievable rate for all users as large as possible. To solve this non-convex problem, we first derive the analytic optimal solution of the time allocation, which is expressed as the function of UAV position. The original problem, after substituting the derived optimal time allocation, is reformulated as a new optimization problem whose optimization variable is only UAV position. We propose a sequential unconstrained convex minimization-based algorithm to obtain the globally optimal solution. The simulation results demonstrate that the performance of our proposed algorithm matches with that obtained by two-dimensional exhaustive search. To decrease the complexity, a Dinkelbach-based algorithm to obtain the locally optimal solution is also proposed. The simulation results show that the performances of our proposed two algorithms are superior to the schemes without time allocation optimization and/or position optimization. [ABSTRACT FROM AUTHOR]

Coded caching, which could significantly reduce the maximum amount of transmission rate during the peak traffic times in wireless network, has been widely studied recently. Apart from the transmission rate, sub-packetization $F$ reflecting the implementation complexity, is also concerned in coded caching. The grouping method proposed by Shanmugam et al. is well-known and widely used to reduce the sub-packetization level of the coded caching problem. In this paper, we propose a concatenating construction method for coded caching schemes, which generalizes the grouping method. Moreover, we demonstrate the advantage of our method in reducing the transmission rate over the grouping method. In particular, some new explicit schemes are obtained from previously known schemes. From one of these schemes, we can derive all the results by Tang and Ramamoorthy as special cases. Furthermore, the analysis and comparison of these new schemes are also performed. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV) can be utilized as a relay to connect nodes with long distance, which can achieve significant throughput gain owing to its mobility and line-of-sight (LoS) channel with ground nodes. However, such LoS channels make UAV transmission easy to eavesdrop. In this paper, we propose a novel scheme to guarantee the security of UAV-relayed wireless networks with caching via jointly optimizing the UAV trajectory and time scheduling. For every two users that have cached the required file for the other, the UAV broadcasts the files together to these two users, and the eavesdropping can be disrupted. For the users without caching, we maximize their minimum average secrecy rate by jointly optimizing the trajectory and scheduling, with the secrecy rate of the caching users satisfied. The corresponding optimization problem is difficult to solve due to its non-convexity, and we propose an iterative algorithm via successive convex optimization to solve it approximately. Furthermore, we also consider a benchmark scheme in which we maximize the minimum average secrecy rate among all users by jointly optimizing the UAV trajectory and time scheduling when no user has the caching ability. Simulation results are provided to show the effectiveness and efficiency of our proposed scheme. [ABSTRACT FROM AUTHOR]

By blending the concepts of non-orthogonal multiple access (NOMA) and orthogonal frequency division multiplexing, in this paper, a novel hybrid scheme is conceived for supporting diverse services in future wireless systems. Motivating to maximize energy efficiency (EE), the joint resource management of user clustering (UC) and power allocation is investigated for the downlink hybrid NOMA systems. Under two different power consumption cases, the optimal resource allocation (Opt-RA) algorithm is developed with the help of converting the original mixed integer non-linear programming (MINLP) problem to the tractable decoupled problems. For practical implementation, the heuristic resource allocation (Heur-RA) algorithm is also proposed, and it includes a low-complexity UC algorithm based on the candidate search-and-allocation approach. Our simulation results show that, both the Opt-RA and Heur-RA algorithms achieve significantly higher EE performance than other existing algorithms. Further, the results also prove that, the hybrid NOMA conceived is able to exploit the advantages of NOMA scheme, and is superior to conventional orthogonal multiple access (OMA) in terms of EE, as well as achieving higher flexibility for system configuration than NOMA. [ABSTRACT FROM AUTHOR]

The broadcast nature of wireless communications makes transmission susceptible to eavesdropping. Recently, physical-layer security has been extensively studied to secure the wireless transmissions, but the security is severely compromised when the eavesdropper has the superiority in the channel quality. Toward this issue, we in this paper propose a joint ARQ and network coding method exploiting the characteristics of both the physical layer and the link layer. Specifically, we relate the message to be transmitted in the current slot with the successfully decoded messages in previous slots, where the ARQ is employed at the legitimate side to guarantee the successful transmission and decoding. Once one or more received messages fail to be decoded at the eavesdropper, it further prevents the eavesdropper from decoding the transmissions in later slots and thus the message transmitted currently and later is secured at the legitimate side. Moreover, for the more disadvantageous case that the eavesdropper is geographically closer to the transmitter, we further propose a destination-aided network coding scheme, which secures private information no matter where the eavesdropper is. The closed-form expressions of intercept probability and loss probability of the private information are analytically presented. The simulation results are provided to confirm our theoretical findings. [ABSTRACT FROM AUTHOR]

In this paper, we analyze a carrier-sense multiple access system with all-to-all broadcast data traffic to assess the performance gain obtained by using multiple sector antennas and a receiver setup that can decode multiple packets simultaneously when packets arrive in narrow angle of arrivals. In the broadcast mode of IEEE 802.11p-based vehicle-to-vehicle communications, acknowledgment messages are absent and a fixed contention window is used in medium access. As a result, the probability of multiple vehicles simultaneously transmitting a packet increases with the number of vehicles. In the case of a simultaneous transmission, a receiver with omnidirectional antennas receives power from all the transmitting vehicles and the probability of successfully decoding a packet decreases. This problem can be alleviated by using sector antennas when the simultaneously transmitted packets arrive at a receiver in the narrow angle of arrivals. We show through analysis and simulations that the packet success rate (PSR) can be improved significantly by using the sector antennas’ setup instead of an omnidirectional antenna. Numerical results show that a several-fold increase in the PSR can be achieved in a setup with four sector antennas compared with an omnidirectional antenna when the density of vehicles is large. [ABSTRACT FROM AUTHOR]

Aimed at providing high data rate in wireless local area networks (WLANs), the IEEE 802.11ac standard has been developed with key enhancements, including increasing the transmission rate and enlarging the packet payload length. The improvement in the sum rate performance, nevertheless, could become marginal or even disappear when nodes of legacy 802.11a/n standards coexist. It is, therefore, of paramount importance to study how to optimize the network sum rate of a multi-standard WLAN. In this paper, a multi-group model is proposed to analyze the data rate performance of a multi-standard WLAN where nodes with different standards have distinct transmission rates and packet payload lengths. It is shown that the packet payload length is a key system parameter that has a crucial impact on both the network sum rate and the ratio of node data rates. The enhancement proposed in the latest 802.11ac standard on enlarging the packet payload length can improve the data rate performance of its own nodes, but it may lead to the starvation of the legacy 802.11a/n nodes, and even impair the sum rate performance. To maximize the network sum rate with given target ratios of node data rates, the optimal packet payload lengths with or without joint tuning of the initial backoff window sizes are further obtained, which shed important light on the optimal network design of WLANs. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) have been widely used in a range of compelling applications. In this paper, we integrate both the networking techniques and the cloud computing tasks of multi-UAV systems. We commence by proposing an energy efficient scheme for selecting the gateway of UAVs invoked for relaying data to the heterogenous cloud. Then, relying on queuing theory and Lyapunov optimization, we strike a power-delay trade-off by jointly optimizing the computational task scheduling and resource allocation in the heterogeneous cloud architecture, which is comprised of an edge cloud and a powerful remote cloud. We analyze the optimal resource-allocation strategy for each time slot and an iterative algorithm is conceived for reducing the computational complexity. Finally, our numerical results demonstrate the superiority of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, we consider device-to-device (D2D) communication that is underlaid in a multi-cell massive multiple-input multiple-output (MIMO) system and proposes a new framework for power control and pilot allocation. In this scheme, the cellular users (CUs) in each cell get orthogonal pilots which are reused with reuse factor one across cells, while all the D2D pairs share another set of orthogonal pilots. We derive a closed-form capacity lower bound for the CUs with different receive processing schemes. In addition, we derive a capacity lower bound for the D2D receivers and a closed-form approximation of it. We provide power control algorithms to maximize the minimum spectral efficiency (SE) and to maximize the product of the signal-to-interference-plus-noise ratios in the network. Different from prior works, in our proposed power control schemes, we consider joint pilot and data transmission optimization. Finally, we provide a numerical evaluation, where we compare our proposed power control schemes with the maximum transmit power case and the case of conventional multi-cell massive MIMO without D2D communication. Based on the provided results, we conclude that our proposed scheme increases the sum SE of multi-cell massive MIMO networks. [ABSTRACT FROM AUTHOR]

In this paper, we propose two non-uniform quantization (NUQ) codebook-based hybrid precoding schemes for two main hybrid precoding implementations, i.e., the full-connected structure and the sub-connected structure, to reduce the feedback overhead in millimeter wave single user multiple-input multiple-output systems. Specifically, we firstly group the angles of the arrive/departures (AOAs/AODs) of the scattering paths into several spatial lobes by exploiting the sparseness property of the millimeter wave in the angular domain, which divides the total angular domain into effective spatial lobes’ coverage angles and ineffective coverage angles. Then, we map the quantization bits non-uniformly to different coverage angles and construct NUQ codebooks, where high numbers of quantization bits are employed for the effective coverage angles to quantize AoAs/AoDs and zero quantization bit is employed for ineffective coverage angles. Finally, two low-complexity hybrid analog/digital precoding schemes are proposed, which utilize the NUQ codebooks. Simulation results demonstrate that the proposed two NUQ codebook-based hybrid precoding schemes achieve near-optimal spectral efficiencies and show the superiority in reducing the feedback overhead compared with the uniform quantization codebook-based works. [ABSTRACT FROM AUTHOR]

The interdependency between different network layers is commonly observed in cyber physical systems and communication networks adopting the dissociation of logic and hardware implementation, such as software defined networking and network function virtualization. This paper formulates an optimization problem to improve the survivability of interdependent networks by restructuring the provisioning relations. A characteristic of the proposed algorithm is that the continuous availability of the entire system is guaranteed during the restructuring of dependencies by the preservation of certain structures in the original networks. Our simulation results demonstrate that the proposed restructuring algorithm can substantially enhance the survivability of interdependent networks and provide insights into the ideal allocation of dependencies. [ABSTRACT FROM AUTHOR]

In this paper, we consider the frequency synchronization issue in orthogonal frequency division multiplexing distributed antenna systems. There may exist multiple carrier frequency offsets (CFOs) between the transmitter and distributed receive antennas. To solve the multi-CFO estimation problem, we first derive the blind maximum likelihood estimator, which has superior estimation performance, but exhibits high computational complexity. Furthermore, we develop a blind pairing-based efficient estimator (PBEE), which divides the multiple antennas into pairs of two. The two CFOs in each pair are jointly estimated with a carefully designed cost function, which proves to be exactly a cosine function parameterized by the two CFOs even with the effect of noise. Consequently, the joint estimation of the two CFOs can be simplified to the one-dimensional search optimization problem. The PBEE can achieve better CFO estimation performance than the existing competitors. From the theoretical mean square error (MSE) analysis of PBEE, we further derive the optimal antenna pairing scheme by minimizing the signal-to-noise ratio degradation caused by the uncompensated residual CFOs. Finally, the Cramér-Rao bound of CFO estimation is derived and numerical results are provided to corroborate the proposed studies. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle-based aerial base stations (BSs) can provide rapid communication services to ground users and are thus promising for future communication systems. In this paper, we consider a scenario where no functional terrestrial BSs are available and the aim is deploying multiple aerial BSs to cover a maximum number of users within a certain target area. To this end, we first propose a naive successive deployment method, which converts the non-convex constraints in the involved optimization into a combination of linear constraints through geometrical relaxation. Then, we investigate a deployment method based on $K$ -means clustering. The method divides the target area into $K$ convex subareas, where within each subarea, a mixed integer non-linear problem is solved. An iterative power efficient technique is further proposed to improve coverage probability with reduced power. Finally, we propose a robust technique for compensating the loss of coverage probability in the existence of inaccurate user location information. Our simulation results show that the proposed techniques achieve an up to 30% higher coverage probability when users are not distributed uniformly. In addition, the proposed simultaneous deployment techniques, especially the one using iterative algorithm, improve power-efficiency by up to 15% compared with the benchmark circle packing theory. [ABSTRACT FROM AUTHOR]

Massive multiple-input–multiple-output (MIMO) systems can suffer from coherent intercell interference due to the phenomenon of pilot contamination. This paper investigates a two-layer decoding method that mitigates both coherent and non-coherent interference in multi-cell Massive MIMO. To this end, each base station (BS) first estimates the channels to intra-cell users using either minimum mean-squared error (MMSE) or element-wise MMSE estimation based on uplink pilots. The estimates are used for local decoding on each BS followed by a second decoding layer where the BSs cooperate to mitigate inter-cell interference. An uplink achievable spectral efficiency (SE) expression is computed for arbitrary two-layer decoding schemes. A closed form expression is then obtained for correlated Rayleigh fading, maximum-ratio combining, and the proposed large-scale fading decoding (LSFD) in the second layer. We also formulate a sum SE maximization problem with both the data power and LSFD vectors as optimization variables. Since this is an NP-hard problem, we develop a low-complexity algorithm based on the weighted MMSE approach to obtain a local optimum. The numerical results show that both data power control and LSFD improve the sum SE performance over single-layer decoding multi-cell Massive MIMO systems. [ABSTRACT FROM AUTHOR]

Light-fidelity (LiFi) is a networked optical wireless communication (OWC) solution for high-speed indoor connectivity for fixed and mobile optical communications. Unlike conventional radio frequency wireless systems, the OWC channel is not isotropic, meaning that the device orientation affects the channel gain significantly, particularly for mobile users. However, due to the lack of a proper model for device orientation, many studies have assumed that the receiver is vertically upward and fixed. In this paper, a novel model for device orientation based on experimental measurements of 40 participants has been proposed. It is shown that the probability density function (PDF) of the polar angle can be modeled either based on a Laplace (for static users) or a Gaussian (for mobile users) distribution. In addition, a closed-form expression is obtained for the PDF of the cosine of the incidence angle based on which the line-of-sight (LOS) channel gain is described in OWC channels. An approximation of this PDF based on the truncated Laplace is proposed and the accuracy of this approximation is confirmed by the Kolmogorov–Smirnov distance. Moreover, the statistics of the LOS channel gain are calculated and the random orientation of a user equipment (UE) is modeled as a random process. The influence of the random orientation on signal-to-noise-ratio performance of OWC systems has been evaluated. Finally, an orientation-based random waypoint (ORWP) mobility model is proposed by considering the random orientation of the UE during the user’s movement. The performance of ORWP is assessed on the handover rate and it is shown that it is important to take the random orientation into account. [ABSTRACT FROM AUTHOR]

Integrating the unmanned aerial vehicles (UAVs) into the cellular network is envisioned to be a promising technology to significantly enhance the communication performance of both UAVs and existing terrestrial users. In this paper, we first provide an overview on the two main research paradigms in cellular UAV communications, namely, cellular-enabled UAV communication with UAVs as new aerial users served by the ground base stations (GBSs), and UAV-assisted cellular communication with UAVs as new aerial communication platforms serving the terrestrial users. Then, we focus on the former paradigm and study a new UAV trajectory design problem subject to practical communication connectivity constraints with the GBSs. Specifically, we consider a cellular-connected UAV in the mission of flying from an initial location to a final location that are given, during which it needs to maintain reliable communication with the cellular network by associating with one of the available GBSs at each time instant that has the best line-of-sight channel (or shortest distance) with it. We aim to minimize the UAV’s mission completion time by optimizing its trajectory, subject to a quality-of-connectivity constraint of the GBS-UAV link specified by a minimum receive signal-to-noise ratio target, which needs to be satisfied throughout its mission. To tackle this challenging non-convex optimization problem, we first propose an efficient method to verify its feasibility via checking the connectivity between two given vertices on an equivalent graph. Next, by examining the GBS-UAV association sequence over time, we obtain useful structural results on the optimal UAV trajectory, based on which two efficient methods are proposed to find high-quality approximate trajectory solutions by leveraging the techniques from graph theory and convex optimization. The proposed methods are analytically shown to be capable of achieving a flexible tradeoff between complexity and performance, and yielding a solution in polynomial time with the performance arbitrarily close to that of the optimal solution. Numerical results further validate the effectiveness of our proposed designs against benchmark schemes. Finally, we make concluding remarks and point out promising directions for future work. [ABSTRACT FROM AUTHOR]

This paper gives a novel perspective on physical layer security (PLS) and end-to-end (e2e) analysis under dual correlated Nakagami- $m$ fading, and outdated channel state information, by employing 1) decode-and-forward opportunistic relays, and 2) an adaptive encoder with on/off transmission. Assuming an infinite relay buffer size, two new sets of independent results for 1) non-integer fading parameter $m$ , mathematically employing infinite summations, and 2) integer $m$ , mathematically employing finite summations, are obtained. The adaptive encoder deployment improves transmission quality, and simultaneously enhances secrecy performance. The proposed e2e analysis coherently links secrecy, and e2e system performance for the first time under dual correlated Nakagami- $m$ fading. Findings for wireless secrecy, and e2e system analysis with the non-integer fading parameter $m$ offer an extra dimension to existing PLS literature, which has chronically been valid for only integer $m$. Convergence for infinite summations is achieved for a finite number of terms, realising the practicality of the proposed findings. Monte Carlo simulation successfully validates the new findings for non-integer $m$ , and an asymptotic analysis under several specific scenarios is also presented. [ABSTRACT FROM AUTHOR]

The position and time of mobile agents are essential information for many wireless network applications. In this paper, we propose a single-anchor localization and synchronization scheme of full-duplex (FD) agents in the line-of-sight scenario, where the anchor is equipped with an antenna array. The agents perform inter-node ranging using the FD radios, while the anchor only receives signals transmitted from the agents. We derive the Cramér-Rao lower bounds for the agent positions and clock offsets based on the frames received by the agents and anchor. In particular, the Fisher information matrix for the positions and clock offsets can be decomposed into the information from the measurements of the arrival angles and arrival times. Then, we design the channel estimation algorithm to obtain the arrival angles, arrival times, and signal-to-noise ratios, based on which we further develop the network localization and synchronization algorithms to obtain the agent positions and clock offsets. The simulation results illustrate the performance of our proposed scheme and algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we first introduce a generalized modeling and analysis framework to explore the fundamental interactions between user association, coverage probability, and link rate in a millimeter-wave (mmWave) heterogeneous cellular network (HetNet), in which there are multiple tiers of the ultra-high-frequency (UHF) macrocell and small-cell base stations (BSs) and a single tier of mmWave small-cell BSs. A generalized user association scheme that can cover many path-loss-based user association schemes is proposed, and its related probabilistic properties that facilitate the derivations of the coverage probability and link rate are derived. The derived general expressions of the coverage and link rate not only shed light on how to design user association functions in order to maximize the coverage and link rate but also show that it is impossible to devise a user association scheme that maximizes the coverage and link rate at the same time. Namely, there exists a fundamental tradeoff between the coverage and link rate in mmWave HetNets with distinct bandwidths in the UHF and mmWave bands while a user is mymargin associating with a BS. We characterize the coverage-optimal and rate-optimal user association schemes and numerically validate their performances and show the coverage-rate tradeoff problem. [ABSTRACT FROM AUTHOR]

While modern wireless devices are capable of using multiple WiFi interfaces, the Multipath TCP (MPTCP) protocol has been employed to make full use of the capacity of many radios by enabling multiple path communication simultaneously. To provide exceptional mobility support in wireless networks, a key question is to determine the best handoff strategy to switch between access points or among WiFi/3G interfaces during roaming. In this paper, we propose SERO, a novel model-driven SEamless ROaming framework to optimize layer-2 handoff and vertical handoff for multihomed devices using MPTCP. The proposed framework adopts a measurement-based method to derive the TCP throughput model for wireless communication during handoff. Based on the throughput model, we propose a hybrid handoff strategy that uses multiple WiFi interfaces for data transmission and employs 3G augmentation to bridge the network interruption caused by handoff and to guarantee the total throughput above a predefined threshold for roaming devices. We implement the SERO framework in a real-deployed wireless mesh network testbed, and evaluate its performance by extensive experiments, which shows that SERO achieves performance gain of 26%–180% compared with several existing handoff strategies. [ABSTRACT FROM AUTHOR]

In this paper, a security-aware energy-efficient resource allocation is modeled as a fractional programming problem for heterogeneous multi-homing networks. The security-aware resource allocation is formulated as a secrecy energy efficiency maximization problem subject to the average packet delay, the average packet dropping probability, and the total available power consumption. In order to guarantee the packet-level quality of service (QoS), first, the average packet delay and the average packet dropping probability requirement for each mobile terminal at the link layer are transformed into a minimum secrecy rate constraint at the physical layer. Then, the non-convex secrecy energy efficiency maximization problem is approximated by a convex problem through epigraph representation. A security-aware energy-efficient resource allocation algorithm is then proposed leveraging dual-decomposition method and bi-section search method. Finally, a heuristic security-aware resource allocation algorithm is proposed to serve as a benchmark. Simulation results demonstrate that the proposed security-aware energy-efficient resource allocation algorithm not only improves the secrecy energy efficiency and throughput, but also guarantees the packet-level QoS. [ABSTRACT FROM AUTHOR]