Cell-free massive multiple-input multiple-output (CF-mMIMO) systems provide enhanced coverage and capacity for next-generation wireless networks. However, CF-mMIMO systems face significant challenges in downlink power allocation (PA) due to imperfect channel state information (CSI), severe multi-user interference (MUI), and high computational complexity. To address these issues, rate-splitting multiple access (RSMA) is adopted as a robust interference management strategy. Accordingly, this paper proposes an unsupervised and scalable graph neural network (GNN) framework for PA in rate-splitting CF-mMIMO (RS-CF-mMIMO) systems, relying exclusively on large-scale fading (LSF) coefficients without instantaneous CSI. To resolve the dimensionality mismatch in dynamic networks, we introduce a slice-based adaptive layer that projects variable-dimension features into a fixed latent space. This mechanism enables a unified model to generalize across diverse topologies without retraining. Within this architecture, the sum spectral efficiency (SE) is maximized under per-AP power constraints, assuming maximum-ratio precoding for common streams and regularized zero-forcing precoding for private streams. We also derive a weighted minimum mean-square error-alternating direction method of multipliers (WMMSE-ADMM) algorithm as a performance upper bound. Extensive simulations verify that the proposed GNN framework achieves near-optimal SE and outperforms unsupervised deep neural networks (DNNs) across diverse system sizes and pilot assignment schemes. Furthermore, the scalable variant maintains robust performance while reducing the trainable parameter count by over 57% relative to DNNs and decreasing inference latency by up to three orders of magnitude compared with WMMSE-ADMM.

Terahertz (THz) communication is a key enabling technology for achieving high-capacity, long-distance inter-satellite and satellite-ground communications in the next-generation wireless systems. Photonic-assisted upconversion provides a cost-effective approach to realizing ultra-wideband THz communication systems. To explore the potential of quantum neural network for the photonic-assisted THz communication systems, this work is the first to design the hybrid quantum-classical neural network for quadrature amplitude modulation (QAM) symbol recovery over tens of Gbit/s THz kilometer-level wireless transmission link, which can significantly enhance the receiver performance and reduce the computational complexity. For the proof of concept, we create the 10 Gbaud sub-THz prototype to validate the proposed scheme over 4.6km wireless long-distance. The results demonstrate that the proposed scheme achieves a 0.7dB improvement in receiver sensitivity and a one-hundred-times reduction in real-valued multiplications per symbol (RMps) compared to the classical ones.

This paper studies the large-scale cell-free networks where dense distributed access points (APs) serve many users. As a promising next-generation network architecture, cell-free networks enable ultra-reliable connections and minimal fading/blockage, which are much favorable to the millimeter wave and terahertz transmissions. However, conventional beam management with large phased arrays in a cell is very time-consuming in the higher-frequencies, and could be worsened when deploying a large number of coordinated APs in the cell-free systems. To tackle this challenge, the spatial-spectral cell-free networks with the leaky-wave antennas are established by coupling the propagation angles with frequencies. The beam training overhead in this direction can be significantly reduced through exploiting such spatial-spectral coupling effects. In the considered large-scale spatial-spectral cell-free networks, a novel subchannel allocation solution at sub-terahertz bands is proposed by leveraging the relationship between cross-entropy method and mixture model. Since initial access and AP clustering play a key role in achieving scalable large-scale cell-free networks, a hierarchical AP clustering solution is proposed to make the joint initial access and cluster formation, which is adaptive and has no need to initialize the number of AP clusters. After AP clustering, a subchannel allocation solution is devised to manage the interference between AP clusters. Numerical results are presented to confirm the efficiency of the proposed solutions and indicate that besides subchannel allocation, AP clustering can also have a big impact on the large-scale cell-free network performance at sub-terahertz bands.

This paper designs the vehicle tracking and resource allocation in the terahertz (THz) vehicle-to-infrastructure communications (V2I) networks, where roadside units (RSUs) equipped with leaky-wave antennas help to estimate the driving states of multiple vehicles and optimize the transmit power and bandwidth per vehicle after receiving the vehicles’ feedback. Different from the conventional phased arrays, the leaky-wave antenna has the potential of improving the sensing accuracy with lower system overhead thanks to its unique spatial-spectral coupling feature. The generalized mobile scenario is studied in which vehicles drive at time-varying speeds. A novel unscented Kalman filter (UKF) based solution is proposed to track the vehicles without requirement of addressing the Doppler effect. Based on the estimated states of multiple vehicles, a low-complexity resource allocation method is developed to maximize the sum rate under user fairness concern. Simulation results confirm that the proposed tracking solution can evaluate the propagation angle, vehicle’s states and inter-vehicle distance accurately, and the tailored resource allocation method strikes a delicate balance between the sum rate and user fairness in the multi-vehicle V2I scenario.

In this paper, we design the vehicle tracking in the terahertz (THz) vehicle-to-infrastructure (V2I) networks, where roadside units (RSUs) equipped with leaky-wave antennas help to estimate the driving states of multiple vehicles after receiving the vehicles’ feedback. Different from the conventional phased arrays, the leaky-wave antenna has the potential of improving the sensing accuracy with lower system overhead thanks to its unique spatial-spectral coupling feature. The generalized mobile scenario is studied in which vehicles drive at time-varying speeds. A novel unscented Kalman filter (UKF) based solution is proposed to track the vehicles without requirement of addressing the Doppler effect. Simulation results confirm that the proposed tracking solution can evaluate the propagation angle, vehicle’s states and inter-vehicle distance accurately.

This paper focuses on the spatial-spectral terahertz (THz) networks, where transmitters equipped with leaky-wave antennas send information to their receivers at the THz frequency bands. As a directional and nearly planar antenna, the leaky-wave antenna allows for information transmissions with narrow beams and high antenna gains. The conventional large antenna arrays are confronted with challenging issues such as scaling limits and path discovery in the THz frequencies. Therefore, this work exploits the potential of leaky-wave antennas in the dense THz networks, to establish low-complexity THz links. By addressing the propagation angle-frequency coupling effects, the transmission rate is analyzed. The results show that the leaky-wave antenna is efficient for achieving the high-speed transmission rate. The co-channel interference management is unnecessary when the THz transmitters with large subchannel bandwidths are not extremely dense. A simple subchannel allocation solution is proposed, which enhances the transmission rate compared with the same number of subchannels with the equal allocation of the frequency band. After subchannel allocation, a low-complexity power allocation method is proposed to improve the energy efficiency.

In this paper, we study the coexistence and synergy between edge and central cloud computing in a heterogeneous cellular network (HetNet), which contains a multi-antenna macro base station (MBS), multiple multi-antenna small base stations (SBSs) and multiple single-antenna user equipment (UEs). The SBSs are empowered by edge clouds offering limited computing services for UEs, whereas the MBS provides high-performance central cloud computing services to UEs via a restricted multiple-input multiple-output (MIMO) backhaul to their associated SBSs. With processing latency constraints at the central and the edge networks, we aim to minimize the system energy consumption used for task offloading and computation. The problem is formulated by jointly optimizing the cloud selection, the UEs' transmit powers, the SBSs' receive beamformers, and the SBSs' transmit covariance matrices, which is a mixed-integer and non-convex optimization problem. Based on the methods such as decomposition approach and successive pseudoconvex approach, a tractable solution is proposed via an iterative algorithm. The simulation results show that our proposed solution can achieve great performance gain over conventional schemes using edge or central cloud alone. Also, with large-scale antennas at the MBS, the massive MIMO backhaul can significantly reduce the complexity of the proposed algorithm and obtain even better performance.

In this paper, the synergy of combining the edge and central cloud computing is studied in heterogeneous cellular networks (HetNets). Multi-antenna small base stations (SBSs) equipped with edge cloud servers offer computing services for user equipment (UEs) proximally, whereas a macro base station (MBS) provides central cloud computing services for UEs via wireless multiple-input multiple-output (MIMO) backhaul allocated to their associated SBSs. With task processing latency constraints for UEs, the network energy consumption is minimized through jointly optimizing the cloud selection, the UEs' transmit powers, the SBSs' receive beamformers, and the SBSs' transmit covariance matrices. A mixed integer and non-convex optimization problem is formulated, and a decomposition algorithm is proposed to obtain a tractable solution iteratively. The simulation results confirm that great performance improvement can be achieved compared with the traditional scheme with central cloud computing only.

This paper focuses on edge caching in dense heterogeneous cellular networks, in which small base stations (SBSs) with limited cache size store the popular contents, and massive multiple-input multiple-output (MIMO)-aided macro base stations provide wireless self-backhaul when SBSs require the non-cached contents. Our aim is to address the effects of cell load and hit probability on the successful content delivery (SCD) and present the minimum required base station density for avoiding the access overload in an arbitrary small cell and backhaul overload in an arbitrary macrocell. The achievable rate of massive MIMO backhaul without any downlink channel estimation is derived to calculate the backhaul time, and the latency is also evaluated in such networks. The analytical results confirm that hit probability needs to be appropriately selected in order to achieve SCD. The interplay between cache size and SCD is explicitly quantified. It is theoretically demonstrated that when non-cached contents are requested, the average delay of the non-cached content delivery could be comparable to the cached content delivery with the help of massive MIMO-aided self-backhaul, if the average access rate of cached content delivery is lower than that of self-backhauled content delivery. Simulation results are presented to validate our analysis.

This paper studies the performance of cache-enabled dense small cell networks consisting of multi-antenna sub-6 GHz and millimeter-wave (mm-wave) base stations. Different from the existing works which only consider a single antenna at each base station, the optimal content placement is unknown when the base stations have multiple antennas. We first derive the successful content delivery probability by accounting for the key channel features at sub-6 GHz and mm-wave frequencies. The maximization of the successful content delivery probability is a challenging problem. To tackle it, we first propose a constrained cross-entropy algorithm which achieves the near-optimal solution with moderate complexity. We then develop another simple yet effective heuristic probabilistic content placement scheme, termed two-stair algorithm, which strikes a balance between caching the most popular contents and achieving content diversity. Numerical results demonstrate the superior performance of the constrained cross-entropy method and that the two-stair algorithm yields significantly better performance than only caching the most popular contents. The comparisons between the sub-6 GHz and mm-wave systems reveal an interesting tradeoff between caching capacity and density for the mm-wave system to achieve similar performance as the sub-6 GHz system.

This paper studies the performance of cache-enabled dense small cell networks consisting of multi- antenna sub-6 GHz and millimeter-wave base stations. We first derive the successful content delivery probability by accounting for the key channel features at sub-6 GHz and mmWave frequencies. In general, the optimal content placement is unknown when the base stations have multiple antennas. Then we propose a simple yet effective probabilistic content placement scheme to maximize the successful content delivery probability, which could balance caching both the most popular contents and achieving content diversity. Numerical results demonstrate that our proposed content placement scheme yields significantly better performance than only caching the most popular contents. The comparisons between the sub-6 GHz and millimeter-wave systems reveal an interesting tradeoff between caching capacity and base station density for the millimeter-wave system to achieve similar performance as the sub-6 GHz system.

This paper focuses on the energy coverage in wireless powered sub-6 GHz and millimeter wave (mmWave) dense cellular networks, where mobile devices harvest RF energy from sub-6 GHz or mmWave base stations (BSs). The expressions for energy coverage probability in sub-6 GHz and mmWave tiers are respectively derived. The comparisons between sub-6 GHz and mmWave RF energy harvesting are analyzed. In particular, we provide the sufficient conditions for the case that wireless energy harvesting in mmWave tier is better than that in sub-6 GHz tier. Furthermore, in hybrid cellular networks with mode selection mechanism, the probability that a mobile device selects a sub-6 GHz BS or mmWave BS for wireless power transfer is also theoretically obtained.

One of key 5G scenarios is that device-to-device (D2D) and massive multiple-input multiple-output (MIMO) will be co-existed. However, interference in the uplink D2D underlaid massive MIMO cellular networks needs to be coordinated, due to the vast cellular and D2D transmissions. To this end, this paper introduces a spatially dynamic power control solution for mitigating the cellular-to-D2D and D2D-to-cellular interference. In particular, the proposed D2D power control policy is rather flexible including the special cases of no D2D links or using maximum transmit power. Under the considered power control, an analytical approach is developed to evaluate the spectral efficiency (SE) and energy efficiency (EE) in such networks. Thus, the exact expressions of SE and EE for a cellular user or D2D transmitter are derived, which quantify the impacts of key system parameters such as massive MIMO antennas and D2D density. Numerical results corroborate our analysis and show that the proposed power control solution can efficiently mitigate interference between the cellular and D2D tier.

This paper focuses on wireless powered 5G dense cellular networks, where base station (BS) delivers energy to user equipment (UE) via the microwave radiation in sub-6 GHz or millimeter wave (mmWave) frequency, and UE uses the harvested energy for uplink information transmission. By addressing the impacts of employing different numbers of antennas and bandwidths at lower and higher frequencies, we evaluate the amount of harvested energy and throughput in such networks. Based on the derived results, we obtain the required small cell density to achieve an expected level of harvested energy or throughput. Also, we obtain that when the ratio of the number of sub-6-GHz BSs to that of the mmWave BSs is lower than a given threshold, UE harvests more energy from an mmWave BS than a sub-6-GHz BS. We find how many mmWave small cells are needed to perform better than the sub-6-GHz small cells from the perspectives of harvested energy and throughput. Our results reveal that the amount of harvested energy from the mmWave tier can be comparable to the sub-6-GHz counterpart in the dense scenarios. For the same tier scale, mmWave tier can achieve higher throughput. Furthermore, the throughput gap between different mmWave frequencies increases with the mmWave BS density.

One of the key 5G scenarios is that device-to-device (D2D) and massive multiple-input multiple-output (MIMO) will be co-existed. However, interference in the uplink D2D underlaid massive MIMO cellular networks needs to be coordinated, due to the vast cellular and D2D transmissions. To this end, this paper introduces a spatially dynamic power control solution for mitigating the cellular-to-D2D and D2D-to-cellular interference. In particular, the proposed D2D power control policy is rather flexible, including the special cases of no D2D links or using maximum transmit power. Under the considered power control, an analytical approach is developed to evaluate the spectral efficiency (SE) and energy efficiency (EE) in such networks. Thus, the exact expressions of SE for a cellular user or D2D transmitter are derived, which quantify the impacts of key system parameters, such as massive MIMO antennas and D2D density. Moreover, the D2D scale properties are obtained, which provide the sufficient conditions for achieving the anticipated SE. Numerical results corroborate our analysis and show that the proposed power control solution can efficiently mitigate interference between the cellular and the D2D tier. The results demonstrate that there exists the optimal D2D density for maximizing the area SE of D2D tier. In addition, the achievable EE of a cellular user can be comparable with that of a D2D user.

Wireless networks with directional antennas, like millimeter wave (mmWave) networks, have enhanced security. For a large-scale mmWave ad hoc network in which eavesdroppers are randomly located, however, eavesdroppers can still intercept the confidential messages, since they may reside in the signal beam. This paper explores the potential of physical layer security in mmWave ad hoc networks. Specifically, we characterize the impact of mmWave channel characteristics, random blockages, and antenna gains on the secrecy performance. For the special case of uniform linear array (ULA), a tractable approach is proposed to evaluate the average achievable secrecy rate. We also characterize the impact of artificial noise in such networks. Our results reveal that in the low transmit power regime, the use of low mmWave frequency achieves better secrecy performance, and when increasing transmit power, a transition from low mmWave frequency to high mmWave frequency is demanded for obtaining a higher secrecy rate. More antennas at the transmitting nodes are needed to decrease the antenna gain obtained by the eavesdroppers when using ULA. Eavesdroppers can intercept more information by using a wide beam pattern. Furthermore, the use of artificial noise may be ineffective for enhancing the secrecy rate.

This paper considers the massive multiple-input multiple-output (MIMO) enabled heterogeneous cloud radio access network (C-RAN), in which both remote radio heads (RRHs) and massive MIMO macrocell base stations (BS) are deployed to potentially accomplish high throughput and energy efficiency (EE). In this network, the soft fractional frequency reuse (S-FFR) is employed to mitigate the inter-tier interference. We develop a tractable analytical approach to evaluate the throughput and EE of the entire network, which can well predict the impacts of the key system parameters such as number of macrocell BS antennas, RRH density, and S-FFR factor, etc. Our results demonstrate that massive MIMO is still a powerful tool for improving the throughput of the heterogeneous C-RAN while RRHs are capable of achieving higher EE. The impact of S-FFR on the network throughput is dependent on the density of RRHs. Furthermore, more radio resources allocated to the RRHs can greatly improve the EE of the network.

Wireless networks with directional antennas, like millimeter wave (mmWave) networks, have enhanced security. For a large scale mmWave ad hoc network in which eavesdroppers are randomly located, however, eavesdroppers can still intercept the confidential messages, since they may reside in the signal beam. This paper explores the potential of physical layer security in the mmWave ad hoc networks. Specifically, we characterize the impact of mmWave channel characteristics and large antenna arrays on the secrecy performance. We also characterize the impact of artificial noise in this networks. Our results reveal that in the low transmit power regime, the use of low mmWave frequency achieves better secrecy performance, when increasing transmit power, a transition from low mmWave frequency to high mmWave frequency is demanded for obtaining more secrecy rate. Eavesdroppers can intercept more information by using wide beam pattern. Furthermore, the use of artificial noise may be unable to enhance the secrecy rate for the case of low node density.

In this paper, we model and analyze the downlink (DL) wireless power transfer and uplink (UL) information transmission of K-tier heterogeneous cellular networks (HCNs). Due to the densely located BSs and universal frequency reuse between all tiers in HCNs, the typical mobile terminal (MT) is allowed to harvest energy from the serving BS by direct beamforming, as well as from the other interfering BSs. Equipped with large storage battery, the typical MT utilizes the harvested energy to provide constant transmit power for the UL information transmission. Stochastic geometry is used to model and evaluate the intrinsic relationship between the energy harvested from the BSs in the DL and the information transmission performance in the UL. To well evaluate the system performance, we derive exact expressions for the maximum transmit power at MT and the UL average ergodic rate. Our results show that the UL average ergodic rate per random MT is not significantly improved by increasing the energy conversion efficiency.

This study considers amplify‐and‐forward two‐way relay networks, where an energy constrained relay node harvests energy from the received radio‐frequency signal. Based on time switching receiver, they separate the energy harvesting (EH) phase and the information processing (IP) phase in time. In the EH phase, three practical wireless power transfer policies are proposed: (i) dual‐source (DS) power transfer, where both sources transfer power to the relay; (ii) single‐fixed‐source power transfer, where a fixed source transfers power to the relay; and (iii) single‐best‐source (SBS) power transfer, where a source with the strongest channel transfers power to the relay. In the IP phase, a new comparative framework of the proposed wireless power transfer policies is presented in two bi‐directional relaying protocols, known as multiple access broadcast (MABC) and time division broadcast (TDBC). To characterise the performance of the proposed policies, new analytical expressions are derived for the outage probability, the throughput, and the system energy efficiency. Numerical results corroborate the authors’ analysis and show: (i) the DS policy performs the best in terms of both outage probability and throughput among the proposed policies, (ii) the TDBC protocol achieves lower outage probability than the MABC protocol, and (iii) there exits an optimal value of EH time fraction to maximise the throughput.

In this paper, we model and analyze the downlink (DL) wireless power transfer and uplink (UL) information transmission of K-tier heterogeneous cellular networks (HCNs) with randomly located base stations (BSs) and mobile terminals (MTs). In the DL and UL, each energy-constrained MT pairs up with its corresponding BS, which provides the maximum received power at the MT. Due to the densely located BSs and universal frequency reuse between all tiers in HCNs, the typical MT is allowed to harvest energy from the serving BS by direct beamforming as well as from the other interfering BSs. Equipped with large storage battery, the typical MT utilizes the harvested energy to provide constant transmit power for the UL information transmission. Stochastic geometry is used to model and evaluate the intrinsic relationship between the energy harvested from the BSs in the DL and the information transmission performance in the UL. To well evaluate the system performance, we first derive exact expressions for the maximum transmit power at MT, the UL outage probability, and the UL average ergodic rate per MT. As the number of BS antennas goes to infinity, we further derive asymptotic expressions for the maximum transmit power at MT, the UL outage probability, and the UL average ergodic rate per MT. Our results show that the UL outage probability per MT first decreases and then increases with increasing the time allocation factor (the fraction of time allocated to the DL), and the UL outage probability, and the UL average ergodic rate per MT, can be largely improved by using the massive antenna arrays at the BSs.

We investigate beamforming and artificial noise generation at the secondary transmitters to establish secure transmission in large scale spectrum sharing networks, where multiple noncolluding eavesdroppers attempt to intercept the secondary transmission. We develop a comprehensive analytical framework to accurately assess the secrecy performance under the primary users' quality of service constraint. Our aim is to characterize the impact of beamforming and artificial noise generation (BF&AN) on this complex large scale network. We first derive exact expressions for the average secrecy rate and the secrecy outage probability. We then derive an easy-to-evaluate asymptotic average secrecy rate and asymptotic secrecy outage probability when the number of antennas at the secondary transmitter goes to infinity. Our results show that the equal power allocation between the useful signal and artificial noise is not always the best strategy to achieve maximum average secrecy rate in large scale spectrum sharing networks. Another interesting observation is that the advantage of BF&AN over BF on the average secrecy rate is lost when the aggregate interference from the primary and secondary transmitters is strong, such that it overtakes the effect of the generated AN.

In this paper, we investigate secure device-to-device (D2D) communication in energy harvesting large-scale cognitive cellular networks. The energy constrained D2D transmitter harvests energy from multiantenna equipped power beacons (PBs), and communicates with the corresponding receiver using the spectrum of the primary base stations (BSs). We introduce a power transfer model and an information signal model to enable wireless energy harvesting and secure information transmission. In the power transfer model, three wireless power transfer (WPT) policies are proposed: 1) co-operative power beacons (CPB) power transfer, 2) best power beacon (BPB) power transfer, and 3) nearest power beacon (NPB) power transfer. To characterize the power transfer reliability of the proposed three policies, we derive new expressions for the exact power outage probability. Moreover, the analysis of the power outage probability is extended to the case when PBs are equipped with large antenna arrays. In the information signal model, we present a new comparative framework with two receiver selection schemes: 1) best receiver selection (BRS), where the receiver with the strongest channel is selected; and 2) nearest receiver selection (NRS), where the nearest receiver is selected. To assess the secrecy performance, we derive new analytical expressions for the secrecy outage probability and the secrecy throughput considering the two receiver selection schemes using the proposed WPT policies. We presented Monte carlo simulation results to corroborate our analysis and show: 1) secrecy performance improves with increasing densities of PBs and D2D receivers due to larger multiuser diversity gain; 2) CPB achieves better secrecy performance than BPB and NPB but consumes more power; and 3) BRS achieves better secrecy performance than NRS but demands more instantaneous feedback and overhead. A pivotal conclusion is reached that with increasing number of antennas at PBs, NPB offers a comparable secrecy performance to that of BPB but with a lower complexity.

This paper explores the potential of wireless power transfer (WPT) in massive multiple-input multiple-output (MIMO)-aided heterogeneous networks (HetNets), where massive MIMO is applied in the macrocells, and users aim to harvest as much energy as possible and reduce the uplink path loss for enhancing their information transfer. By addressing the impact of massive MIMO on the user association, we compare and analyze user association schemes: 1) downlink received signal power (DRSP)-based approach for maximizing the harvested energy and 2) uplink received signal power (URSP)-based approach for minimizing the uplink path loss. We adopt the linear maximal-ratio transmission beamforming for massive MIMO power transfer to recharge users. By deriving new statistical properties, we obtain the exact and asymptotic expressions for the average harvested energy. Then, we derive the average uplink achievable rate under the harvested energy constraint. Numerical results demonstrate that the use of massive MIMO antennas can improve both the users' harvested energy and uplink achievable rate in the HetNets; however, it has negligible effect on the ambient RF energy harvesting. Serving more users in the massive MIMO macrocells will deteriorate the uplink information transfer because of less harvested energy and more uplink interference. Moreover, although DRSP-based user association harvests more energy to provide larger uplink transmit power than the URSP-based one in the massive MIMO HetNets, URSP-based user association could achieve better performance in the uplink information transmission.

This paper develops a tractable framework for exploiting the potential benefits of physical layer security in three-tier wireless sensor networks (WSNs) using stochastic geometry. In such networks, the sensing data from the remote sensors are collected by sinks with the help of access points, and the external eavesdroppers intercept the data transmissions. We focus on the secure transmission in two scenarios: 1) the active sensors transmit their sensing data to the access points and 2) the active access points forward the data to the sinks. We derive new compact expressions for the average secrecy rate in these two scenarios. We also derive a new compact expression for the overall average secrecy rate. Numerical results corroborate our analysis and show that multiple antennas at the access points can enhance the security of three-tier WSNs. Our results show that increasing the number of access points decreases the average secrecy rate between the access point and its associated sink. However, we find that increasing the number of access points first increases the overall average secrecy rate, with a critical value beyond which the overall average secrecy rate then decreases. When increasing the number of active sensors, both the average secrecy rate between the sensor and its associated access point, and the overall average secrecy rate decrease. In contrast, increasing the number of sinks improves both the average secrecy rate between the access point and its associated sink, and the overall average secrecy rate.

This paper develops a tractable framework for exploiting the potential benefits of physical layer security in three-tier wireless sensor networks. In such networks, the sensing data from the remote sensors are collected by sinks with the help of access points, and the external eavesdroppers intercept the data transmissions. We adopt the stochastic geometry approach to model the random locations and spatial densities of the sensors, access points, sinks, and eavesdroppers. We focus on the secure transmission in two scenarios: i) the active sensors transmit their sensing data to the access points, and ii) the active access points forward the data to the sinks. We derive new compact expressions for the overall average secrecy rate in such networks. Numerical results corroborate our analysis and show that multiple- antenna technique at the access points can enhance the security. Our results show that the overall average secrecy rate first increases with increasing the number of access points, and there exists a critical value beyond which the overall average secrecy rate decreases with increasing the number of access points. When adding the number of active sensors, the overall average secrecy rate decreases. In contrast, increasing the number of sinks improves the overall average secrecy rate.

This paper exploits the potential of massive multiple input multiple output (MIMO) in K-tier heterogeneous cellular networks (HCNs), to enhance the data rate for 5G. In such a network, macro base stations (MBSs) are equipped with large number of antennas and support multi-user transmission. We first examine the impact of massive MIMO on user association in K-tier HCNs. Exact and asymptotic expressions for the probability of a user being associated with a macro cell or a small cell are derived. Based on the asymptotic analysis, the impacts of system parameters such as tier's density and BS transmit power on user association are explicitly identified. Furthermore, we derive the coverage probability and rate of the proposed network. Numerical results corroborate our analysis and show that the implementation of massive MIMO in macro cells can significantly enhance the performance of HCNs in terms of coverage and rate. A guideline for practical cellular deployment is reached that MBSs with large antenna arrays can decrease the demands for small cells.

Compared to the existing lower frequency wireless power transfer, millimeter wave (mmWave) power transfer takes advantage of the high-dimensional multi-antenna and narrow beam transmission. In this paper we introduce wireless power transfer for mmWave cellular networks. Here, we consider users with large energy storage that are recharged by the mmWave base stations prior to uplink information transmission, and analyze the average harvested energy and average achievable rate. Numerical results corroborate our analysis and show that the serving base station plays a dominant role in wireless power transfer, and the contribution of the interference power from the interfering base stations is negligible, even when the interfering base stations are dense. By examining the average achievable rate in the uplink, when increasing the base station density, a transition from a noise-limited regime to an interference-limited regime is observed.

We investigate beamforming and artificial noise generation at the secondary transmitters to establish secure transmission in large scale spectrum sharing networks, where multiple non-colluding eavesdroppers attempt to intercept the secondary transmission. We develop a comprehensive analytical framework to accurately assess the secrecy performance under the primary user's quality of service constraint. Our aim is to characterize the impact of beamforming and artificial noise generation on this complex large scale network. We first derive the exact expressions for the average secrecy rate and the secrecy outage probability. Our results show that there exists an average secrecy rate wall beyond which the primary user's quality of service is violated. Interestingly, we find that different from the conventional network with fixed nodes where equal power allocation achieves near optimal average secrecy rate, the equal power allocation may not be a good option for large scale spectrum sharing networks.

In this paper, we investigate secure device-to-device (D2D) communication in energy harvesting large-scale cognitive cellular networks. The energy constrained D2D transmitter harvests energy from multi-antenna equipped power beacons (PBs), and communicates with the corresponding receiver using the spectrum of the cellular base stations (BSs). We introduce a power transfer model and an information signal model to enable wireless energy harvesting and secure information transmission. In the power transfer model, we propose a new power transfer policy, namely, best power beacon (BPB) power transfer. To characterize the power transfer reliability of the proposed policy, we derive new closed-form expressions for the exact power outage probability and the asymptotic power outage probability with large antenna arrays at PBs. In the information signal model, we present a new comparative framework with two receiver selection schemes: 1) best receiver selection (BRS), and 2) nearest receiver selection (NRS). To assess the secrecy performance, we derive new expressions for the secrecy throughput considering the two receiver selection schemes using the BPB power transfer policies. We show that secrecy performance improves with increasing densities of PBs and D2D receivers because of a larger multiuser diversity gain. A pivotal conclusion is reached that BRS achieves better secrecy performance than NRS but demands more instantaneous feedback and overhead.

In this paper, the impact of multiple active eavesdroppers on cooperative single carrier systems with multiple relays and multiple destinations is examined. To achieve the secrecy diversity gains in the form of opportunistic selection, a two-stage scheme is proposed for joint relay and destination selection, in which, after the selection of the relay with the minimum effective maximum signal-to-noise ratio (SNR) to a cluster of eavesdroppers, the destination that has the maximum SNR from the chosen relay is selected. To accurately assess the secrecy performance, exact and asymptotic expressions are obtained in closed form for several security metrics, including the secrecy outage probability, probability of nonzero secrecy rate, and ergodic secrecy rate in frequency selective fading. Based on the asymptotic analysis, key design parameters, such as secrecy diversity gain, secrecy array gain, secrecy multiplexing gain, and power cost, are characterized, from which new insights are drawn. In addition, it is concluded that secrecy performance limits occur when the average received power at the eavesdropper is proportional to the counterpart at the destination. In particular, for the secrecy outage probability, it is confirmed that the secrecy diversity gain collapses to zero with outage floor, whereas for the ergodic secrecy rate, it is confirmed that its slope collapses to zero with capacity ceiling.

This paper exploits an amplify-and-forward (AF) two-way relaying network (TWRN), where an energy constrained relay node harvests energy with wireless power transfer. Two bidirectional protocols, multiple access broadcast (MABC) protocol and time division broadcast (TDBC) protocol, are considered. Three wireless power transfer policies, namely, dual-source (DS) power transfer; single-fixed-source (SFS) power transfer; and single-best-source (SBS) power transfer are proposed and well-designed based on time switching receiver architecture. We derive analytical expressions to determine the throughput both for delay-limited transmission and delay-tolerant transmission. Numerical results corroborate our analysis and show that MABC protocol achieves a higher throughput than TDBC protocol. An important observation is that SBS policy offers a good tradeoff between throughput and power.

In this paper, the impact of multiple eavesdroppers on cooperative single carrier systems with multiple relays and multiple destinations is examined. To achieve the secrecy diversity gains in the form of opportunistic selection, a two-stage scheme is proposed for joint relay and destination selection, in which, after the selection of the relay with the minimum effective maximum signal-to-noise ratio (SNR) to a cluster of eavesdroppers, the destination that has the maximum SNR from the chosen relay is selected. In order to accurately assess the secrecy performance, the exact and asymptotic expressions are obtained in closed-form for the ergodic secrecy rate in frequency selective fading. Based on the asymptotic analysis, key design parameters such as multiplexing gain, and power cost are characterized, from which new insights are drawn. Moreover, it is concluded that capacity ceiling occurs when the average received power at the eavesdropper is proportional to the counterpart at the destination.

We examine the impact of transmit antenna selection with receive generalized selection combining (TAS/GSC) for cognitive decode-and-forward (DF) relaying in Nakagami-m fading channels. We select a single transmit antenna at the secondary transmitter which maximizes the receive signal-to-noise ratio (SNR) and combine a subset of receive antennas with the largest SNRs at the secondary receiver. In an effort to assess the performance, we first derive the probability density function and cumulative distribution function of the end-to-end SNR using the moment generating function. We then derive new exact closed-form expression for the ergodic capacity. More importantly, by deriving the asymptotic expression for the high SNR approximation of the ergodic capacity, we gather deep insights into the high SNR slope and the power offset. Our results show that the high SNR slope is 1/2 under the proportional interference power constraint. Under the fixed interference power constraint, the high SNR slope is zero.

This paper considers transmit antenna selection (TAS) and receive generalized selection combining (GSC) for secure communication in MIMO wiretap channel, where confidential messages transmitted from an NA-antenna transmitter to an NB-antenna legitimate receiver are overheard by an NE-antenna eavesdropper. We assume that the main channel and the eavesdropper's channel undergo Nakagami-m fading with fading parameters mBand mE, respectively. In an effort to assess the secrecy performance, we present a closed-form expression for the secrecy outage probability. We then derive closed-form expressions for the secrecy outage probability at high signal-to-noise ratio (SNR) for two realistic scenarios: 1) the legitimate receiver is located close to the transmitter, and 2) the legitimate receiver and the eavesdropper are located close to the transmitter. In the first scenario, we confirm that the secrecy diversity order is mBNBNA. In the second scenario, we confirm that the secrecy diversity order collapses to zero. While this may appear discouraging at a first glance, we show that low secrecy outage probability can still be achieved.

This paper advocates physical layer security in wiretap channels with two-wave with diffuse power fading. In such a wiretap channel, we consider that confidential messages transmitted from a single antenna transmitter to an M-antenna receiver is overheard by an N-antenna eavesdropper. The receiver adopts maximal-ratio combining (MRC) to enhance transmission security, whereas the eavesdropper adopts MRC to maximize the probability of successful eavesdropping. We develop a new analytical framework to characterize the average secrecy capacity as the principal security performance metric in active eavesdropping. Specifically, we derive new closed-form expressions for the exact and asymptotic average secrecy capacity. Based on these, we determine the high signal-to-noise ratio power offset to explicitly quantify the impact of the main channel and the eavesdropper's channel on the average secrecy capacity.

This paper advocates physical layer security of maximal ratio combining (MRC) in wiretap two-wave with diffuse power fading channels. In such a wiretap channel, we consider that confidential messages transmitted from a single antenna transmitter to an M-antenna receiver are overheard by an N-antenna eavesdropper. The receiver adopts MRC to maximize the probability of secure transmission, whereas the eavesdropper adopts MRC to maximize the probability of successful eavesdropping. We derive the secrecy performance for two practical scenarios: 1) the eavesdropper's channel state information (CSI) is available at the transmitter and 2) the eavesdropper's CSI is not available at the transmitter. For the first scenario, we develop a new analytical framework to characterize the average secrecy capacity as the principal security performance metric. Specifically, we derive new closed-form expressions for the exact and asymptotic average secrecy capacity. Based on these, we determine the high signal-to-noise ratio power offset to explicitly quantify the impacts of the main channel and the eavesdropper's channel on the average secrecy capacity. For the second scenario, the secrecy outage probability is the primary security performance metric. Here, we derive new closed-form expressions for the exact and asymptotic secrecy outage probability. We also derive the probability of nonzero secrecy capacity. The asymptotic secrecy outage probability explicitly indicates that the positive impact of M is reflected in the secrecy diversity order and the negative impact of N is reflected in the secrecy array gain. Motivated by this, we examine the performance gap between N and N+1 antennas based on their respective secrecy array gains.

In this paper, the impact of interference from multiple licensed transceivers on cognitive underlay single-carrier systems is examined. Specifically, the situation is considered in which the secondary network is limited by three key parameters: 1) maximum transmit power at the secondary transmitter, 2) peak interference power at the primary receivers, and 3) interference power from the primary transmitters. For this cognitive underlay single-carrier system, the signal-to-interference ratio (SIR) of the secondary network is obtained for transmission over frequency-selective fading channels. Based on this, a new closed-form expression for the cumulative distribution function of the SIR is evaluated, from which the outage probability and the ergodic capacity are derived. Further insights are established by analyzing the asymptotic outage probability and the asymptotic ergodic capacity in the high-transmission-power regime. In particular, it is corroborated that the asymptotic outage diversity gain is equal to the multipath gain of the frequency-selective channel in the secondary network. The asymptotic ergodic capacity also gives new insight into the additional power cost for different network parameters while maintaining a specified target ergodic capacity. Illustrative numerical examples are presented to validate the outage probability and ergodic capacity under different interference power profiles.

This paper considers transmit antenna selection (TAS) and receive generalized selection combining (GSC) for secure communication in the multiple-input-multiple-output wiretap channel, where confidential messages transmitted from an NA-antenna transmitter to an NB-antenna legitimate receiver are overheard by an NE-antenna eavesdropper. We assume that the main channel and the eavesdropper's channel undergo Nakagami-m fading with fading parameters mB and mE, respectively. In order to assess the secrecy performance, we present a new unifying framework for the average secrecy rate and the secrecy outage probability. We first derive expressions for the probability density function and the cumulative distribution function of the signal-to-noise ratio with TAS/GSC, from which we derive exact expressions for the average secrecy rate and the secrecy outage probability. We then derive compact expressions for the asymptotic average secrecy rate and the asymptotic secrecy outage probability for two distinct scenarios: 1) the legitimate receiver is located close to the transmitter, and 2) the legitimate receiver and the eavesdropper are located close to the transmitter. For these scenarios, we present new closed-form expressions for several key performance indicators: 1) the capacity slope and the power offset of the asymptotic average secrecy rate, and 2) the secrecy diversity order and the secrecy array gain of the asymptotic secrecy outage probability. For the first scenario, we confirm that the capacity slope is one and the secrecy diversity order is mBNBNA. For the second scenario, we confirm that the capacity slope and the secrecy diversity order collapse to zero.