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

This paper considers a downlink unicast transmission in a multicell network with multiple users. In a network with frequency reuse factor of one, intercell interference is a limiting factor. The max–min beamforming technique enables a balancing of the signal-to-interference-plus-noise ratio (SINR) among all users in a network under a power budget. Thus, a fair distribution of the achievable rate can be achieved. The max–min beamforming problem (MBP) is nonconvex in general. However, if instantaneous channel-state information (CSI) is available, the MBP has an equivalent quasiconvex form and can optimally be solved with an efficient algorithm based on a convex solver. In addition to this convex-solver-based solution, this paper considers the so-called surrogate dual problem of the MBP with per-antenna and per-antenna-array power constraints. The surrogate dual problem combines multiple power constraints to a single power constraint. Furthermore, the surrogate dual problem can efficiently be solved for long-term CSI in the form of spatial correlation matrices. Strong duality is proved for instantaneous and long-term CSI in the form of higher rank spatial correlation matrices. With the surrogate dual problem, a fast algorithm for the MBP is presented. The convergence issue is discussed. Numerical results verify the convergence and the performance of the proposed algorithm. [ABSTRACT FROM PUBLISHER]

Dynamic spectrum access (DSA) techniques based on the exclusive-use model provide a huge opportunity for wireless service providers (WSPs) to improve the spectrum utilization in their licensed bands and generate additional profits by allowing temporary wireless access to unsubscribed secondary users (SUs). This paper presents a techno-economic analysis for regulated SU access based on a novel base station (BS)-centric framework, where SUs coexist with the subscribers, i.e., primary users (PUs), on a mutually exclusive basis. Considering the highly competitive WSP environment, the proposed framework is aimed at maximizing the localized spectrum utilization within the static spectrum licensed to the WSP and assumes no cooperation and no spectrum sharing among WSPs, thus making this a business case for implementation. The dynamic incentive-based SU pricing model proposed in this paper has the inherent capability of call admission control and, hence, is useful in attracting SUs to obtain temporary wireless access during periods of low PU demand, thus improving spectrum usage in the temporal domain. Although SU access is regulated by the WSP at their BS, the SUs have the freedom to connect or handoff to their preferred BS in the area based on the SU price quoted by the WSP. The implementation of the proposed framework to Long Term Evolution (LTE) infrastructure requires minimal enhancements and can be potentially attractive to WSPs, since the SU devices in this framework do not require spectrum sensing cognitive capabilities. Considering all the aforementioned aspects, this paper can be considered an intermediate step in the evolution toward complete DSA. [ABSTRACT FROM PUBLISHER]

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

Cell search and synchronization in the Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) system is performed in each user equipment (UE) by using the primary synchronization signal (PSS) and secondary synchronization signal (SSS). The overall synchronization performance is heavily dominated by robust PSS detection, which can be achieved in the conventional noncoherent detector by exploiting the essential near-perfect autocorrelation and cross-correlation properties of Zadoff–Chu (ZC) sequences. However, a relatively high computational complexity is observed in conventional algorithms. As compared with them, two new detectors, i.e., almost-half-complexity (AHC) and central-self-correlation (CSC) detectors, are proposed in this paper to achieve reliable PSS detection with much lower complexity by exploiting the central-symmetric property of ZC sequences. The complexity of the proposed CSC detector is only 50% that of the AHC detector, which achieves exactly the same PSS detection accuracy as that of the conventional detector with one half of complexity being saved. An improvement of CSC, i.e., \CSCIns, is also proposed in this paper to combat the large-frequency offset. The performance of the \CSCIns detector is independent of the frequency offset, and numerical results show that the 90% PSS acquisition time of \CSCIns can be well within an 80-ms duration, even in a heavy intercell-interference environment with a signal-to-noise ratio (SNR) of -10 dB. [ABSTRACT FROM PUBLISHER]

This paper studies the power allocation problem for a cognitive radio (CR) multiple-input–multiple-output (MIMO) system under spectrum sharing with an existing primary radio network. In particular, the ergodic capacity maximization problem is studied in the Rayleigh fading cognitive MIMO channel under both the total transmit power constraint and a set of interference power constraints where each is applied at one of the primary receivers (PRs). This paper considers that the channel from primary transmitter (PT) to secondary receiver (SR), and the channel from secondary transmitter (ST) to SR are both in short-term fading due to the mobility of SR, whereas the channels from ST to PRs are in long-term fading. By using the Lagrangian dual method, the optimal transmit precoding matrix is derived, and some nearly optimal power allocation algorithms are proposed to maximize the bounds of secondary user ergodic capacity. Performance analysis and simulation results show that the proposed schemes can approach the comparative capacity of the optimal power allocation algorithm, which has perfect instant channel state information (CSI), particularly when the antenna number of the ST exceeds the total antenna number of PRs. [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]

Flexible duplexing is a promising technique to improve the spectral efficiency of future cellular networks, which has been proposed mainly to provision asymmetric uplink (UL) and downlink (DL) traffic scenarios, through flexible channel allocations. However, this flexibility in the channel allocation process, which is responsible for allocating the underlying channel to different base stations in a heterogeneous network (HetNet), has brought new technical challenges due to the introduction of complex UL-to-DL and DL-to-UL interference scenarios. This paper analyzes the joint channel allocation (CA) and user scheduling (US) process for orthogonal frequency-division multiple access-based flexible HetNets, while considering exact inter-cell/intra-cell interferences. The resulting joint problem is a large-scale mixed-integer nonlinear programming problem that is computationally intractable, therefore, it has been re-formulated into a convex upper bound problem to find benchmark solutions for CA in flexible HetNets. Since, no new CA scheme has been proposed yet for the HetNets employing flexible duplexing techniques, we discuss the efficacy of existing schemes under various UL and DL traffic scenarios. [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]

This correspondence paper considers a dual-hop underlay cognitive radio nonorthogonal multiple access (NOMA) network. The end-to-end outage probability (OP) is evaluated as the performance metric for secondary NOMA users. Furthermore, the OP results of NOMA is compared with conventional orthogonal multiple access to show the supremacy of the former. Representative numerical and simulation results corroborate the effectiveness of the proposed scheme and presented analysis. [ABSTRACT FROM AUTHOR]

Dynamic spectrum sharing (DSS) has been taken as an encouraging method to address the increasing demand for wireless spectrum resources. Without privacy protection in location, however, the primary user will hesitate to share spectrum with secondary users. In this paper, we present LpriDSS, the first scheme for a spectrum administrator to select spectrum-sharing secondary users while implementing the geo-indistinguishability of primary user. First, we formulate the secondary users selection without privacy in DSS system as an auction problem and demonstrate the location inference attacks based on the winner sets in detail. Then, a ranking metric to characterize the administrators’ preference for secondary users is defined. Moreover, a probability of each secondary user being selected as a winner is calculated and used during the process of secondary user selection. Finally, a truthful payment computation is designed according to that probability. Thorough theoretical analysis and simulation studies show that LpriDSS can simultaneously achieve geo-indistinguishability, approximate social welfare maximization, and truthfulness. [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 multi-user multiple-input–multiple-output (MU-MIMO) systems that employ pilot-symbol aided channel estimation, the pilot-to-data power ratio (PDPR) has a large impact on the system performance. In this paper, we consider the problem of setting the PDPR in multi-cell MU-MIMO systems in the presence of channel estimation errors, intercell interference and pilot contamination. To analyze and address this problem, we first develop a model of the multi-cell MU-MIMO system and derive a closed-form expression for the mean squared error of the uplink received data symbols. Building on this result, we then propose two decentralized PDPR-setting algorithms based on game theoretic approaches that are applicable in multi-cell systems. We find that both algorithms converge to a Nash equilibrium and provide performance improvements over systems that do not properly set the PDPR, while they maintain different levels of fairness. [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]

In this paper, we investigate the uplink transmission performance of low-power wide-area (LPWA) networks with regards to coexisting radio modules. We adopt the long-range (LoRa) radio technique as an example of the network of focus, even though our analysis can be easily extended to other situations. We exploit a new topology to model the network, where the node locations of LoRa follow a Poisson cluster process while other coexisting radio modules follow a Poisson point process. Unlike most of the performance analysis based on stochastic geometry, we take noise into consideration. More specifically, two models, with a fixed and a random number of active LoRa nodes in each cluster, respectively, are considered. To obtain insights, both the exact and simple approximated expressions for coverage probability are derived. Based on them, area spectral efficiency and energy efficiency are obtained. From our analysis, we show how the performance of LPWA networks can be enhanced by adjusting the density of LoRa nodes around each LoRa receiver. Moreover, the simulation results unveil that the optimal number of active LoRa nodes in each cluster exists to maximize the area spectral efficiency. [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]

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]

This paper investigates the precoding design for multicast transmission in multicell massive multiple-input multiple-output (MIMO) systems with finite-alphabet inputs. The users within each cell are interested in common information, and different cells provide distinct information. Focusing on the weighted max–min fairness (MMF) problem with only statistical channel state information at the base station, we provide the necessary conditions of the optimal precoding vectors to maximize the minimum weighted achievable ergodic rate, and an iterative algorithm is proposed to optimize the precoding vectors. To achieve lower computational complexity, we then derive a lower bound on the achievable ergodic rate for finite-alphabet inputs. Considering the problem of the minimum weighted rate lower bound maximization, we utilize the concave–convex procedure (CCCP) to develop a CCCP-based algorithm, which is proven to converge to a local optimum. Furthermore, exploiting the channel characteristic in massive MIMO systems, we prove that the optimal precoding vectors, maximizing the minimum weighted rate lower bound, are linear combinations of eigenvectors of transmit correlation matrices, and the original problem can be shifted into a lower dimensional space. Motivated by this insight, a relation-based algorithm is devised to obtain the optimal solution of the weighted MMF problem by using the duality between the MMF problem and the quality of service problem. Numerical results illustrate the tightness of the achievable ergodic rate lower bound and the significant performance of the devised algorithms. [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]

Best relay selection (BRS) is crucial in enhancing the performance of cooperative networks. In contrast to most previous works, where the guidelines for BRS are limited to Gaussian noise, in this paper, we propose a novel relay selection protocol for a decode-and-forward cooperative network taking into account the bursty impulsive noise (IN). The proposed protocol chooses the $N$ th best relay considering both the channel gains and the states of the IN of the source-relay and relay-destination links. For this scheme, to obtain the state of IN, we propose a state detection algorithm using maximum a posteriori (MAP) detection. To analyze the performance of the proposed protocol, we first derive closed-form expressions for the probability density function (PDF) of the received signal-to-noise ratio assuming all the relays know the state of IN perfectly (genie-condition). Then, these PDFs are used to derive closed-form expressions for the bit error rate (BER) and the outage probability. Finally, we also derive the asymptotic BER and outage expressions to quantify the diversity benefits. We show that the proposed MAP-based $N$ th BRS protocol attains the derived genie-aided analytical results and outperforms the conventional relay selection protocol, optimized for the Gaussian case, and which does not take into account the IN memory. [ABSTRACT FROM AUTHOR]

This paper investigates an integrated wireless communication system including non-orthogonal multiple access, full-duplex relaying, and energy harvesting techniques (named as EH-FD-NOMA). In this scheme, an energy-limited full-duplex relay harvests energy from a source at the first stage. Then, the relay detects the superimposed signal from the source and transmits the decoded signal to destination. Closed-form outage probabilities and ergodic rates at the relay and destination are derived. Numerical results verify the analytical results and show the superior performance of the EH-FD-NOMA if compared to its counterparts. [ABSTRACT FROM AUTHOR]

This paper considers the bit loading problem for communication systems that utilize orthogonal frequency division multiplexing (OFDM) in conjunction with precoding (POFDM) or time-domain interleaving (IOFDM). In particular, we propose a new bit loading algorithm for P/I-OFDM that has substantially higher effective throughput and less computational complexity, when compared to bit loading in conventional OFDM systems. The obtained results show that the effective throughput of P/I-OFDM can be more than fourfold the conventional OFDM while the complexity is less than $1.5\%$. Moreover, the results show that the peak-to-average power ratio (PAPR) properties of the considered systems are preserved under the adaptation process. [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]

In this paper, we address the problem of power-efficient resource management in Cloud Radio Access Networks (C-RANs). Specifically, we consider the case where Remote Radio Heads perform data transmission, and signal processing is executed in a virtually centralized Base-Band Units pool. Users request to transmit at different time instants; they demand minimum signal-to-noise-plus-interference ratio (SINR) guarantees, and their requests must be accommodated within a given deadline. These constraints pose significant challenges to the management of C-RANs and, as we will show, considerably impact the allocation of processing and radio resources in the network. Accordingly, we analyze the power consumption of the C-RAN system, and we formulate the power consumption minimization problem as a weighted joint scheduling of processing and power allocation problem for C-RANs with minimum SINR and finite horizon constraints. The problem is a Mixed Integer Non-Linear Program, and we propose an optimal offline solution based on Dynamic Programming. We show that the optimal solution is of exponential complexity; thus, we propose a sub-optimal greedy online algorithm of polynomial complexity. We assess the performance of the two proposed solutions through extensive numerical results. Our solution aims to reach an appropriate tradeoff between minimizing the power consumption and maximizing the percentage of satisfied users. We show that it results in power consumption that is only marginally higher than the optimum, at significantly lower complexity. [ABSTRACT FROM AUTHOR]

In this paper, we propose regularized block diagonalization (RBD) precoding using artificial noise (AN) for physical layer security in downlink multi-user MIMO wireless networks. We derive secrecy sum rate and asymptotic secrecy sum rate for the proposed scheme. The optimum power allocation for legitimate users and the AN signal are derived in closed form for optimal asymptotic secrecy sum rate. Our analysis shows that to achieve best performance, it is more efficient to degrade the performance of the eavesdropper than improving legitimate users’ rates. We also study the impact of error in channel estimation on the system and derive closed-form SINR and secrecy sum-rate expressions for this case. Simulations show that the secrecy sum rate of RBD precoding outperforms the secrecy sum rate of regularized channel inversion by 0.5 bits/s/Hz. We also show that in the presence of channel estimation error, our approximate closed forms for secrecy sum rate are very closed to the actual secrecy sum rate over a wide range of SNR and channel estimation error values. [ABSTRACT FROM AUTHOR]

In cognitive radio networks, collaborative spectrum sensing has been recognized as a key technology to enable secondary users (SUs) to detect spectrum holes and opportunistically access primary licensed spectrum band without harmful interference. Most of the existing studies focus on 1D or 2D spectrum opportunity detection and explicitly or implicitly assume that all SUs share the same spectrum opportunity. In this paper, we first investigate the issue of joint spatial-temporal spectrum sensing in 3D spectrum-heterogeneous space by leveraging the location flexibility of flying unmanned aerial vehicle (UAV) spectrum sensors. We divide the sensing space into three layers: black layer, grey layer, and white layer, which represent different spatial spectrum access opportunities. Then, we formulate the 3D spatial-temporal opportunity sensing model and derive the spatial-temporal false alarm and detection probabilities at both single UAV level and whole network level. Afterwards, we design a temporal fusion window and a spatial fusion sphere to address the composite spatial-temporal data fusion, called 3D spatial-temporal sensing (3DSTS). A comparison among 3DSTS, the benchmark 3D non-cooperative sensing (3DNCS) and 3D cooperative sensing (3DCS) shows the inefficiency of the traditional sensing schemes in the 3D spectrum-heterogeneous networks. Furthermore, we develop three improved versions of 3DSTS, which show much better detection performance. To maximize the utilization of spectrum resource and minimize the interference to the PU, a sensing-based power control scheme is also proposed. Finally, numerical simulations corresponding to the theoretical analysis are demonstrated. [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]

In this paper, we explore the different per-user bandwidths available for each tier of heterogeneous networks (HetNets) and the corresponding downlink range expansion (RE, a key measure to boost small cell association). Based on the practical case of tier-specific path loss exponents, we derive the local delay of HetNets under the random discontinuous transmission scheme (DTX, employed to manage the interference and reduce energy consumption). Using such a new expression for local delay, we then analyze the corresponding energy efficiency (EE). These delay and EE expressions reveal that there exists an optimal value for both the RE bias factor and for the DTX mute probability. A closed-form optimum solution for the RE bias factor is also derived for the low-rate regime. [ABSTRACT FROM AUTHOR]

Sparse code multiple access (SCMA) is one type of non-orthogonal multiple access techniques for the fifth-generation wireless communication networks. Existing multiuser detection algorithms for SCMA uplink systems are based on the assumption that signals are in synchronization. However, asynchrony cannot be neglected due to the propagation delays in practical environments. In this paper, we present three detection algorithms for uplink asynchronous SCMA systems, namely belief propagation message passing algorithm, belief propagation with equal gain combining message passing algorithm, and partial phase-coherent algorithms. Simulation results show that our proposed asynchronous detection algorithms are able to offer descent bit error rate performances, with only a small performances loss compared to the synchronous case. Moreover, our proposed algorithms converge well in the uplink asynchronous SCMA systems. [ABSTRACT FROM AUTHOR]

Spectral efficiency analysis in presence of correlated desired and interfering signals is very important in densely deployed access points scenarios of modern generation wireless networks. However, most works available in literature either address the effect of correlated interfering signals or include interferer activity. Further, available literature has also addressed the effect of large-scale fading (shadowing and distance-dependent path loss) only however, they have fallen short of including the composite effect of line-of-sight and nonline-of-sight multipath small-scale fading. The correlation of desired signals with interfering signals because of shadowing has also not been considered in existing literature either. In this paper, we present a comprehensive analytical signal to interference power ratio evaluation framework addressing all the above-mentioned important propagation effects in a holistic manner. In this analysis, we extend and apply the moment generating function-matching method to such systems to achieve high accuracy. We compare the analytical results against realistic channel model based extensive Monte-Carlo simulation for millimeter Wave and sub-6 GHz in both indoor and outdoor scenarios. The performance of the model is depicted in terms of mean, $\alpha \%$ outage spectral efficiency, and Kullback–Leibler divergence and Kolmogorov–Smirnov distance. [ABSTRACT FROM AUTHOR]

In this paper, we consider a cooperative autonomous driving system where a vehicle overtakes the one in front based on collective perception. To avoid collisions with vehicles on the other lane, we propose a V2X-based cooperative collision avoidance scheme. The overtaking vehicle estimates the distance between itself and the neighbors via V2V communications and decides whether to overtake or not. Two cases where the distance information is obtained independently and cooperatively are taken into account. We derive the probability of collision avoidance and analyze the influence of different factors such as speed and density of vehicles on the system performance. Simulation results verify our analysis and show that our V2X-based cooperative collision avoidance scheme performs better than traditional GNSS-based collision avoidance scheme. The performance gain brought by the cooperative case compared to the independent case in our scheme can also be observed. [ABSTRACT FROM AUTHOR]

Optimal power allocation (PA) strategies can make a significant rate improvement in secure spatial modulation (SM). Due to the lack of secrecy rate (SR) closed-form expression in secure SM networks, it is hard to optimize the PA factor. In this paper, two PA strategies are proposed: gradient descent (GD), and maximum product of signal-to-interference-plus-noise ratio (SINR) and artificial-noise-to-signal-plus-noise ratio (ANSNR) (Max-P-SINR-ANSNR). The former is an iterative method and the latter is a closed-form solution. Compared to the former, the latter is of low-complexity. Simulation results show that the proposed two PA methods can approximately achieve the same SR performance as the exhaustive search method and perform far better than three fixed PA ones. With extremely low complexity, the SR performance of the proposed Max-P-SINR-ANSNR performs slightly better and worse than that of the proposed GD in the low to medium, and high signal-to-noise ratio regions, respectively. [ABSTRACT FROM AUTHOR]

In this paper, a general two-way relay (TWR) transmission method is proposed under per-antenna power constraints by combining space-time line codes (STLCs) with transmit power allocation for two source nodes. We introduce a general STLC-based encoding scheme for a decode-and-forward TWR and derive the detection signal-to-interference-plus-noise ratio (SINR) values at two source nodes. An optimal encoder structure with power allocation is proposed in terms of maximizing the minimum SINRs, and it is verified that the optimal encoder is identical to the superposition of two conventional STLCs. An iterative method is proposed to find the optimal power allocation for detection at two source nodes. Moreover, a low-complexity suboptimal encoder is proposed for practical implementation. Numerical simulations present that the proposed STLC-based transmission method outperforms a conventional eigen-beamforming scheme with nulling and an STLC-based scheme with equal power allocation, in terms of the average bit error rate of source nodes, regardless of the distribution of source nodes, the number of TWR antennas, and the transmit power. [ABSTRACT FROM AUTHOR]

As a conventional metric, spectrum efficiency has been investigated widely in communication systems due to the limited bandwidth resources and increasing subscriber density. Beamforming technology is used in TD-LTE-A and 5G downlink to improve the spectrum efficiency and system capacity, and a proper resource allocation algorithm can also be used to improve the spectrum efficiency on the premise of satisfying user equipment (UE) requirements. In recent years, energy efficiency has attracted more and more attention as the power consumption on the communication systems increases rapidly, which lays a heavy burden on the environment. In this paper, we propose a joint resource allocation and power allocation algorithm in multi-user beamforming mode, which aims at maximizing the energy efficiency, and also takes UE requirements and spectrum efficiency into consideration. The proposed algorithm first calculates the user priorities and gives a UE grouping method to allocate resource blocks (RBs) to different UEs under the assumption that the power is equally allocated among UEs on the same RB. After that, on each RB, it calculates the power allocation among different UEs to realize the improvement of energy efficiency. In addition, the satisfaction of UE requirements is added in the algorithm as a constraint. Simulation results demonstrate that the proposed algorithm shows an excellent performance on system capacity, i.e., spectrum efficiency, and also provides higher energy efficiency than existing algorithms. Moreover, the UE requirements can be better satisfied and system fairness can also be improved. [ABSTRACT FROM AUTHOR]

In this correspondence paper, we analytically characterize the benefit of digital processing in uplink massive multiple-input multiple-output (MIMO) with a sub-connected hybrid architecture. By assuming that the number of radio frequency chains is equal to that of users, we characterize achievable rates of both pure analog detection and hybrid detection under the independent identically distributed Rayleigh fading channel model. From the derived expressions, we discover that the analog processing can outperform the hybrid processing using the maximal ratio combining or zero-forcing criterion in cases under some engineering assumptions. Performance comparison of the schemes are presented under tests with various number of users and number of antennas at the base station. [ABSTRACT FROM AUTHOR]

Heterogeneous cellular networks (HCNs) with millimeter wave (mm-wave) communications are considered as a promising technology for the fifth-generation mobile networks. Mm-wave has the potential to provide multiple gigabit data rate due to the broad spectrum. Unfortunately, additional free space path loss is also caused by the high carrier frequency. On the other hand, mm-wave signals are sensitive to obstacles and more vulnerable to blocking effects. To address this issue, highly directional narrow beams are utilized in mm-wave networks. Additionally, device-to-device (D2D) users make full use of their proximity and share uplink spectrum resources in HCNs to increase the spectrum efficiency and network capacity. Toward the caused complex interferences, the combination of D2D-enabled HCNs with small cells densely deployed and mm-wave communications poses a big challenge to the resource allocation problems. In this paper, we formulate the optimization problem of D2D communication spectrum resource allocation among multiple micro-wave bands and multiple mm-wave bands in HCNs. Then, considering the totally different propagation conditions on the two bands, a heuristic algorithm is proposed to maximize the system transmission rate and approximate the solutions with sufficient accuracies. Compared with other practical schemes, we carry out extensive simulations with different system parameters, and demonstrate the superior performance of the proposed scheme. In addition, the optimality and complexity are simulated to further verify effectiveness and efficiency. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communications underlaying cellular networks have been recognized as a promising technology to improve the system capacity and spectral efficiency of 5G networks. In this paper, we investigate the problem of designing the joint uplink subcarrier assignment and power allocation scheme to optimize the sum data rate of D2D pairs, under a general “many-to-many” scenario in which a subcarrier could be shared by multiple D2D pairs and a D2D pair could also reuse multiple subcarriers. In particular, the optimization problem is to maximize the sum data rate of all D2D pairs under the constraints of minimum data rate requirements of cellular user equipments (CUEs). The formulated problem falls into a mixed integer nonlinear programming, which is generally NP-hard. To solve the problem, we decompose it into two subproblems: the subcarrier assignment subproblem and the power allocation subproblem. More specifically, we first propose an effective algorithm to assign subcarriers for both D2D pairs and CUEs under the assumption that the transmit power of each user is equally allocated among all the subcarriers. After that, we apply the successive convex approximation approach to transform the nonconvex power allocation problem into a sequence of convex problems, based on which an effective power allocation algorithm is designed. Simulations validate that the proposed scheme can significantly improve the achievable sum data rate of D2D pairs, compared with the other existing schemes. [ABSTRACT FROM AUTHOR]

In this paper, we propose a joint channel allocation and power control algorithm by using cognitive radio non-orthogonal multiple access (CR-NOMA) for femtocell users (FUs). The aim is to maximize the sum rate of the FUs for guaranteed quality of service (QoS). With an aim to have guaranteed QoS for FUs, we use CR-NOMA at the femto base station (FBS). Then, an algorithm for pairing among strong and weak users is proposed by using the channel gain difference. Using pairing, the NOMA interference between them reduces which results in better channel utilization. Moreover, we differentiate the even/odd number of FUs in a femtocell to provide the QoS for weak users also. For this purpose, OMA is used to get a predefined data rate using a greedy channel allocation algorithm. The power of each FBS is controlled by using the successive convex approximation for low complexity (SCALE) protocol with Karush-Kuhn-Tucker (KKT) conditions. Numerical results demonstrate that the proposed scheme enhances the sum rate and provides guaranteed QoS for CR-NOMA based femtocell users in comparison to the existing conventional OMA based-femtocell techniques. [ABSTRACT FROM AUTHOR]

In this paper, a new mode selection (MS) scheme for device-to-device (D2D) enabled cellular networks is proposed. The MS is carried out using a predefined signal-to-interference plus noise ratio (SINR) threshold and it aims to guarantee a minimum level of quality of service. With the new scheme, interfering effects are taken into consideration, while realistic assumptions for the acquisition of the channel information are made. Assuming a single-user case, an analytical framework is developed, which is based on the Markov-chain theory, and is used to study the system's performance. The various performance results obtained reveal that with the proposed MS, the probability of mode switching can be reduced (as compared to other systems), and thus, an increase on the overhead and signal processing is avoided. Moreover, a new approach is applied in a multi-user communication scenario, where a joint MS, resource allocation (RA), and scheduling optimization problem is formulated. The solution to this problem is based on a greedy heuristic algorithm that properly assigns the available resources among cellular users and D2D pairs. The joint MS, RA, and scheduling algorithm considers limited SINR awareness and it provides significant performance improvement in terms of sum-rate. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communication standardization is underway and considered as one of the key technologies in the 5G ecosystem. Eavesdropping is a well-known security risk for D2D communications. Thus, ensuring information security for both cellular users (CUs) and D2D pairs in an underlay network is quite challenging. In this paper, we look into the problem of physical-layer secure transmission jointly with resource allocation in D2D communications. Existing research works for D2D underlay networks considered perfect channel state information (CSI), which is usually unrealistic in practical networks due to the wireless channels’ dynamic nature. Hence, unlike the previous works, we are considering imperfect CSI that include estimation errors. We leverage social-domain and frame a coalitional game approach, enabling multiple D2D pairs to share CU spectral resource. We assume heterogeneous cellular network based practical scenario considering multiple eavesdroppers, intra-cell interference, and inter-cell interference to evaluate achievable performances in terms of sum-rate and secrecy capacity for both CUs and D2D pairs. Moreover, we prove our proposed algorithm stability, convergence, and computational complexity. The simulation results establish the effectiveness of our proposed approach that not only maximizes the sum rate (i.e., 10 $ \%$ –60 $ \%$) but also improves the secrecy capacity (i.e., 20 $ \%$ –67 $ \%$) in comparison to the baseline schemes. [ABSTRACT FROM AUTHOR]

The deployment of large-scale UAV clusters for cluster advantages will lead to high competition and excessive congestion of spectrum resources, which results in mutual interference. This paper investigates the interference-aware online spectrum access problem for multicluster Flying Ad-Hoc Network (FANET) under different network topologies, i.e., the locations of UAV clusters are varying. First, the problem is formulated as a data-assisted multistage channel access game with the goal of mitigating interference of all UAV clusters and decreasing channel switching cost during each slot. As we prove that the game is an exact potential game that guarantees at least one pure-strategy Nash equilibrium and interference-aware online channel preserving based concurrent best response (IOCPCBR) algorithm, an online distributed algorithm is proposed to achieve the desirable solution. Finally, the simulation results demonstrate the validity and effectiveness of the multistage channel access game as well as IOCPCBR algorithm. [ABSTRACT FROM AUTHOR]

In cellular heterogeneous networks (HetNets), a number of distributed base stations cooperatively provide services to multiple mobile users. This paper addresses joint base-station activation and coordinated beamforming design for downlink transmission in HetNets. To this end, a mixed integer program is formulated to optimize the total power consumption of a HetNet. A novel approach based on Benders’ decomposition is then put forth to obtain the optimal solution for the problem of interest with guaranteed convergence. Building on our new formulation, a dual-subgradient algorithm is also proposed to find an approximate solution in polynomial time. The proposed approaches can be generalized to more general setups, including robust beamforming designs under channel uncertainty, and coordinated beamforming for multi-cell scenarios. [ABSTRACT FROM AUTHOR]

In this paper, antenna diversity is used to improve the outage performance of downlink non-orthogonal multiple access (NOMA) systems combined with single-user multiple-input multiple-output (SU-MIMO) due to the statistical channel state information (CSI), that the transmitter only knows the statistical characteristic associated with each user's channel matrix. We design the precoding and detection vectors, which makes the proposed MIMO-NOMA system reduce to a single-antenna NOMA system with statistical CSI. Next, a dynamic power allocation scheme is proposed to maximize the ergodic sum rate of the considered NOMA group with the minimum ergodic rate constraints of the weaker users. Under this power allocation, we analyze the impact of user clustering and then develop a novel user clustering algorithm. Also, the outage analysis indicates that the proposed system only obtains receive diversity and under the proposed power allocation, the users’ diversity gains are linear with their successive interference cancellation decoding orders. Simulation results confirm our proposed analysis. [ABSTRACT FROM AUTHOR]