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Recently, multi-hop flying ad hoc networks (FANETs) have received considerable attention because of their various advantages, such as ease of deployment, scalability, cost, and latency reduction. However, FANETs still encounter serious problems such as a highly dynamic network topology and the limited on-board battery of unmanned aerial vehicles (UAVs). Thus, to increase the coverage probability while reducing unnecessary packet transmissions, realizing efficient and effective relay selection is important. To resolve these issues, this paper proposes a proactive and probabilistic uncovered neighbor-aware relay selection (P2URE) method that considers FANET’s topological dynamics. Specifically, the relay decision factor to identify relay UAV candidates and the probabilistic relay decision to reduce coverage overlaps and minimize redundant packet transmissions are devised. Through extensive simulations, it has been validated that the proposed P2URE method surpasses the benchmark methods in terms of the total number of transmissions, coverage probability, and energy efficiency. This superiority is observed across various network dynamics resulting from variations in the UAV density, speed, neighbor-information update period, and delay interval.

We propose a novel cooperative space–time line code (C-STLC) scheme to improve performance of a relay-assisted internet of things (R-IoT). The proposed C-STLC operates with fully distributed manner, where each relay IoT device (RID) attempts to decode the received signal from a source IoT device at the first hop and the RIDs, that succeeded decoding, send the STLC encoded signal based on their local channel state information (CSI) to a single access point (AP) at the second hop. Then, the AP decodes the received signals without CSI. As a main result, we mathematically analyze the outage probability (OP) of the proposed C-STLC scheme. It is shown that the proposed C-STLC significantly outperforms conventional cooperative relaying techniques in terms of the OP.

We propose a novel interference alignment (IA) technique with receive antenna partitioning (RAP) for simultaneous wireless information and power transfer (SWIPT)-enabled downlink fog radio access networks (F-RANs). The basic idea of the proposed scheme is to apply a generalized downlink IA for each access point (AP) and to divide receive antennas at each user into two groups for information decoding (ID) and energy harvesting (EH), respectively. With the proposed scheme, an optimal receive antenna configuration at each user is obtained to maximize the weighted sum of achievable rate and the sum of harvested energy of the network. Also we develop an antenna configuration selection algorithm to obtain near-optimal performance with low computational complexity. Through extensive computer simulations, it is shown that the proposed scheme significantly improves a rate-energy region compared with existing techniques.

In this paper, we mathematically analyze bit-error rate (BER) and diversity order of physical-layer network coding (PNC) scheme in the two-way relay channel (TWRC) under the assumption of multiple antennas at relay node. We assume the quadrature phase shift keying (QPSK) modulation for simple data transmission in IoT applications, and max–min transmit antenna selection (TAS) scheme in the broadcast (BC) phase for achieving full diversity gain. In particular, we obtain the upper bound of BER at the multiple access (MA) phase, while deriving the exact BER performance at the BC phase. To the best our knowledge, the mathematical analysis in this paper is the first analytical results in the literature. Through computer simulations, the analytical results are validated.

Abstract In this letter, a novel multiple‐input multiple‐output transceiver technique, named space–time line coded spatial modulation (STLC‐SM) is proposed, where two modulation symbols are transmitted through one of the multiple transmit antennas determined by the incoming information bits after constellation‐rotated STLC encoding. The receiver decodes the transmitted modulation symbols and the activated antenna index through an optimal joint maximum‐likelihood detector. As a main result, the closed‐form upper‐bound of bit‐error‐rate of the proposed STLC‐SM system in general antenna configurations is mathematically analysed. Finally, it is validated that the STLC‐SM significantly outperforms the conventional STLC in terms of the bit‐error‐rate.

In this paper, we propose a novel simultaneous Correlative Interferometer (CI) technique that elaborately estimates the Direction of Arrival (DOA) of multiple source signals incident on an antenna array. The basic idea of the proposed technique is that the antenna-array-based receiver compares the phase of the received signal with one of the candidates at each time sample and jointly exploits these multiple time samples to estimate the DOAs of multiple signal sources. The proposed simultaneous CI-based DOA estimation technique collectively utilizes multiple time-domain samples and can be regarded as a generalized version of the conventional CI algorithm for the case of multiple time-domain samples. We first thoroughly review the conventional CI algorithm to comprehensively explain the procedure of the direction-finding algorithm that adopts the phase information of received signals. We also discuss several technical issues of conventional CI-based DOA estimation techniques that are originally proposed for the case of a single time-domain sample. Then, we propose a simultaneous CI-based DOA estimation technique with multi-sample diversity as a novel solution for the case of multiple time-domain samples. We clearly compare the proposed simultaneous CI technique with the conventional CI technique and we compare the existing Multiple Signal Classification (MUSIC)-based DOA estimation technique with the conventional CI-based technique by using the DOA spectrum as well. To the best of our knowledge, the simultaneous CI-based DOA estimation technique that effectively utilizes the characteristics of multiple signal sources over multiple time-domain samples has not been reported in the literature. Through extensive computer simulations, we show that the proposed simultaneous CI technique significantly outperforms both the conventional CI technique in terms of DOA estimation even in harsh environments and with various antenna array structures. It is worth noting that the proposed simultaneous CI technique results in much better performance than the classical MUSIC algorithm, which is one of the most representative subspace-based DOA estimation techniques.

To overcome the problems caused by the limited battery lifetime in multiple-unmanned aerial vehicle (UAV) wireless networks, we propose a hierarchical multi-agent reinforcement learning (RL) framework to maximize the energy efficiency (EE) of UAVs by finding the optimal frequency reuse factor and transmit power. The proposed algorithm consists of distributed inner-loop RL for transmit power control of the UAV terminal (UT) and centralized outer-loop RL for finding the optimal frequency reuse factor. Specifically, the proposed algorithm adjusts these two factors jointly to effectively mitigate intercell interference and reduce undesired transmit power consumption in multi-UAV wireless networks. We show that, for this reason, the proposed algorithm outperforms conventional algorithms, such as a random action algorithm with a fixed frequency reuse factor and a hierarchical multi-agent Q-learning algorithm with binary transmit power controls. Furthermore, even in the environment where UTs are continuously moving based on the mixed mobility model, we show that the proposed algorithm can find the best reward when compared to conventional algorithms.

We investigate the uplink non-orthogonal multiple access (NOMA)-based Internet-of-Things (IoT) networks, where each IoT device (station: STA) equipped with a single antenna exploits the constellation-rotated space-time line code (CR-STLC) to send signals to an access point (AP) equipped with two receive antennas. The AP decodes the signals transmitted from the STAs with the optimal joint maximum-likelihood (JML) detector. As a main result, we mathematically analyze both the bit-error-rate (BER) performance and the spatial diversity order of each STA in the two-user uplink CR-STLC NOMA system. In particular, it is shown that the two-user uplink CR-STLC NOMA system achieves the optimal diversity order regardless of the constellation rotation angle in the high signal-to-noise ratio (SNR) regime. We also consider two different rotation angle optimization techniques (dynamic rotation & fixed rotation) to improve the BER performance in the practical SNR regime, and found that the fixed rotation approach is simple but yields almost the same performance as the dynamic approach. Finally, we show that the uplink CR-STLC NOMA system achieves the spatial diversity order of 1 even when more than two STAs send packets simultaneously. It is worth noting that all STAs obtain an improved spatial diversity gain compared to that without constellation rotation.

AbstractRecently, to make the best use of limited and precious spectrum resources, spectrum sharing between satellite and cellular networks has received much interest. In this study, we mathematically analyze the success probability of a fixed (satellite) earth station (FES) based on a stochastic geometry framework. Both the FES and base stations (BSs) are assumed to be equipped with a directional antenna, and the location and the number of BSs are modeled based on the Poisson point process. Furthermore, an exclusion zone is considered, in which the BSs are prohibited from locating in a circular zone with a certain radius around the FES to protect it from severe interference from the cellular BSs. We validate the analytical results on the success probability of the cognitive satellite‐terrestrial network with directional antennas by comparing it using extensive computer simulations and show the effect of the exclusion zone on the success probability at the FES. It is shown that the exclusion zone‐based interference mitigation technique significantly improves the success probability as the exclusion zone increases.

In military applications, mobile ad hoc networks are commonly used due to the autonomy, self-configuration, and flexibility. In addition, spectrum sharing-based communication protocols are being actively considered due to spectrum shortage. We propose a cooperative phase-steering (CPS) technique for a spectrum sharing-based military mobile ad hoc network which consists of a single secondary source (SS) node, multiple secondary relay (SR) nodes, a single secondary destination (SD) node, and multiple primary destination (PD) nodes. In the proposed technique, the SR nodes that succeeded the packet decoding cooperatively adjust the phase of their transmit signals such that the received signals at the SD node from the SR nodes are aligned to a certain angle, while the SR nodes control the transmit power such that the received power at all PD nodes is lower than a certain threshold. Through extensive computer simulations, it is shown that the proposed technique outperforms the conventional cooperative relaying scheme in terms of outage probability.

In this paper, we propose a cooperative maximum-ratio transmission (C-MRT) technique with multi-antenna relay nodes for tactical mobile ad-hoc networks (MANETs) where both the location and the number of antennas of relay nodes are arbitrary. Each relay node is assumed to know both the wireless channel coefficient from the source node to itself and the wireless channel from itself to the destination node, which is known as local channel state information (CSI) assumption. Maximum-ratio combining (MRC) and MRT techniques are used for beamforming the transmit and receive signals of the relay node, respectively. In addition, we mathematically analyze the overall outage probability of the proposed technique with moment generating function (MGF). It is shown that the mathematical analysis on the overall outage probability of the proposed C-MRT technique is matched well with the simulation results especially in high transmit power regimes. It is also observed that the proposed technique outperforms other schemes such as phase steering (PS) and optimal relay selection (ORS) in terms of outage probability.

Recently, there has been a rapid increase in the number of (small-cell) base stations (BSs) to support the massive amount of mobile data traffic and rapidly increasing number of mobile devices in beyond 5G (B5G) wireless communication systems or Internet of Things (IoT) networks. However, many of these BSs tend to waste a considerable amount of energy to support such data traffic and mobile devices. Therefore, the development of an efficient BS status control algorithm is important for realizing energy-efficient IoT networks. To reduce network energy consumption, we herein propose a density clustering-based BS control algorithm for energy-efficient IoT networks (DeCoNet). DBSCAN (Density-Based Spatial Clustering of Applications with Noise) and OPTICS (Ordering Points To Identify the Clustering Structure) are utilized for partitioning high and low user-density regions. To find the effective number of BSs and their appropriate locations considering user-density differences, we utilize parameters obtained after applying density clustering algorithms to derive the thinning radius that is used to adjust the status of BSs in overall cellular IoT networks. Specifically, the average reachability-distance of each cluster in OPTICS and the distance between the outermost border users of each cluster in DBSCAN are used to obtain the radius of each cluster region. Through extensive computer simulations, we show that the proposed algorithms outperform the conventional algorithms in terms of average area throughput, energy efficiency, energy per information bit, and power consumption per unit area.

Time-division multiple access (TDMA)-based medium access control (MAC) protocol has been widely used for avoiding access conflicts in wireless multi-hop ad hoc networks, where the time synchronization among wireless nodes is essential. In this paper, we propose a novel time synchronization protocol for TDMA-based cooperative multi-hop wireless ad hoc networks, which are also called barrage relay networks (BRNs). The proposed time synchronization protocol is based on cooperative relay transmissions to send time synchronization messages. We also propose a network time reference (NTR) selection technique for improving the convergence time and average time error. In the proposed NTR selection technique, each node overhears the user identifier (UID) of other nodes, hop count (HC) from them to itself, and network degree, which denotes the number of 1-hop neighbor nodes. Then, the node with the minimum HC from all other nodes is selected as the NTR node. If there are multiple nodes with the minimum HC, the node with the larger degree is selected as the NTR node. To the best of our knowledge, the proposed time synchronization protocol with the NTR selection is introduced for the first time for cooperative (barrage) relay networks in this paper. Through computer simulations, we validate the proposed time synchronization protocol in terms of the average time error under various practical network scenarios. Furthermore, we also compare the performance of the proposed protocol with the conventional time synchronization methods. It is shown that the proposed protocol significantly outperforms the conventional methods in terms of the average time error and convergence time. The proposed protocol is shown to be more robust against packet loss as well.

In this paper, we propose a novel interference alignment (IA) technique for an in-band full-duplex (IBFD) multiple-input multiple-output (MIMO) cellular network where a base station (BS) and user equipment (UE) are equipped with multiple antennas, and the local channel state information (CSI) is available at all nodes. Considering a practical IBFD MIMO cellular network, it is assumed that only the BS operates with full-duplex (FD) communication while UE operate in half-duplex (HD) mode. These IBFD networks introduce a new type of interference called cross-link interference (CLI), in which uplink UE affects downlink UE. The proposed IA technique consists of two symmetric IA schemes according to the number of antennas in the uplink and downlink UE, and both schemes effectively mitigate CLI in the IBFD MIMO network. It is worth noting that both IA schemes are adaptively applicable according to the network’s quality-of-service (QoS) requirements, such as uplink and downlink traffic demands. Furthermore, we theoretically characterize and prove the achievable sum-degrees-of-freedom (DoF) of the proposed IA technique. Simulation results show that the proposed IA technique significantly improves the sum rate performance compared to conventional HD communications (multi-user MIMO) while achieving the same achievable DoF as the interference-free IBFD MIMO network.

In this paper, we revisit a two-user space-time line coded uplink non-orthogonal multiple access (STLC-NOMA) system for Internet-of-things (IoT) networks and propose a novel low-complexity STLC-NOMA system. The basic idea is that both IoT devices (stations: STAs) employ amplitude-shift keying (ASK) modulators and align their modulated symbols to in-phase and quadrature axes, respectively, before the STLC encoding. The phase distortion caused by wireless channels becomes compensated at the receiver side with the STLC, and thus each STA’s signals are still aligned on their axes at the access point (AP) in the proposed uplink STLC-NOMA system. Then, the AP can decode the signals transmitted from STAs via a single-user maximum-likelihood (ML) detector with low-complexity, while the conventional uplink STLC-NOMA system exploits a multi-user joint ML detector with relatively high-complexity. We mathematically analyze the exact BER performance of the proposed uplink STLC-NOMA system. Furthermore, we propose a novel expectation-maximization (EM)-based blind energy estimation (BEE) algorithm to jointly estimate both transmit power and effective channel gain of each STA without the help of pilot signals at the AP. Somewhat interestingly, the proposed BEE algorithm works well even in short-packet transmission scenarios. It is worth noting that the proposed uplink STLC-NOMA architecture outperforms the conventional STLC-NOMA technique in terms of bit-error-rate (BER), especially with high-order modulation schemes, even though it requires lower computation complexity than the conventional technique at the receiver.

In this paper, we model and characterize interference of directional unmanned aerial vehicle (UAV) networks based on stochastic geometry, where each UAV is equipped with a directional antenna and it communicates with another UAV that is located in the three dimensional (3D) space. In particular, the 3D location of UAVs is assumed to be uniformly distributed in a certain volume, which is modeled by Poisson point process. Given a beamwidth, we first design an ideal 3D directional antenna beam pattern with a constant gain of both main-lobe and side-lobe. To model the interference in the UAV network, we analyze the effect of elevation and azimuth between a typical UAV receiver and an interfering UAV transmitter with spherical coordinate system. Then, we investigate distribution of the aggregate interference at a typical UAV receiver from multiple UAVs in terms of side-lobe gain, beamwidth, height of UAV, and distance of a UAV transmitter–receiver pair. Keywords: UAV networks, Poisson point process (PPP), 3D directional antenna, Interference, Stochastic geometry

In this paper, we consider an unmanned aerial vehicle (UAV)-assisted downlink cellular network consisting of a single base station (BS), two mobile stations (MSs) with N antennas, and K UAV relay stations (RSs). We assume that there exists no direct link between the BS and the MSs due to unexpected blockages such as obstacles and disasters. We propose a UAV-assisted cooperative downlink non-orthogonal multiple access (NOMA) with virtual full-duplex (VFD) operation for improving spectral efficiency in such an environment. In the proposed VFD technique, a single UAV-RS is selected among multiple UAV-RS. Through computer simulations, we verify that the proposed cooperative NOMA technique with VFD operation significantly outperforms the conventional cooperative NOMA technique with half-duplex operation in terms of outage probability. Keywords: Unmanned aerial vehicle (UAV), UAV-assisted cooperative communications, Outage probability, Non-orthogonal multiple access (NOMA), Relay selection algorithm

In this paper, we propose four transmit power control strategies for the underlay device-to-device (D2D) communications, in which the spectral efficiency (SE) of the D2D communications is maximized while the amount of interference caused to a base station (BS) is kept less than a predefined threshold. To this end, we first propose a centralized power control strategy based on instantaneous and global channel state information (CSI) by formulating a convex optimization problem. Then, three distributed power control strategies are taken into account in which each D2D pair adjusts its transmit power in a distributed manner based on interference price and its local CSI, which significantly reduces the signaling overhead. In the distributed strategies, the interference price can be determined based on (1) the instantaneous local CSI; (2) the statistics of the local CSI (average power); and (3) the number of the D2D pairs without any CSI knowledge. Through extensive computer simulations, we show that the performances of the proposed strategies optimally adjust the transmit power of the D2D communications. Especially, we find that the distributed power control strategies can achieve almost the same SE with the centralized strategy with much lower signaling and control overhead.

In this paper, we investigate two user scheduling algorithms (optimal user and threshold-based user scheduling algorithms) when we consider potential eavesdroppers in an uplink wiretap network. The optimal user scheduling (OUS) algorithm selects the user who has the maximum secrecy rate, based on channel feedback from all users. On the other hand, the threshold-based user scheduling (TUS) algorithm first considers the information leakage from the users to potential eavesdroppers and then selects the user among candidates who satisfy a threshold criterion on the information leakage. The OUS algorithm shows an optimal performance in terms of secrecy rate, but the TUS algorithm can achieve secrecy rate comparable with the OUS algorithm with reduced feedback overhead. For main contributions, we mathematically analyze the asymptotic behavior of the achievable secrecy rate of two scheduling algorithms when the signal-to-noise ratio (SNR) approaches to infinity. Further, we derive the approximated secrecy rate of the TUS algorithm and propose criteria to determine threshold values which maximize the achievable secrecy rate of the TUS algorithm. We verify our analytical results through simulations. We perform an extra simulation to investigate the effect of channel estimation error in the wiretap links on the average secrecy rate. Due to different scheduling principles in OUS and TUS schemes, the TUS scheme yields robustness against the channel estimation error in the wiretap links, compared with the OUS schemes.

Grant-free multiple access (GFMA) protocol has been regarded as a key element to support sporadic traffic generated from massive internet-of-things (IoT) networks. In GFMA protocol, each IoT device transmits data packets without grant from a base station (BS) via pre-reserved uplink resources. Packet collisions inherently occur when multiple IoT devices transmit packets by using the same radio resource, but the collision effect can be alleviated with multi-packet reception (MPR) capability of the BS. Since a number of studies have focused on improving the physical layer performance such as bit error rate, they may be hard to provide intuitions from the MAC layer perspective when a number of IoT devices sporadically generate uplink packets and attempt the GFMA. In this paper, we thoroughly investigate the GFMA from the MAC layer perspective. We provide an analytical framework based on a Markov chain to capture the performance of the GFMA in terms of packet transmission success probability, ergodic throughput, and access delay. Through simulations, we validate our analytical framework and verify the necessity of adopting MPR technique for supporting a massive number of IoT devices generating sporadic traffic.

For the next generation of manufacturing, the industrial internet of things (IoT) has been considered as a key technology that enables smart factories, in which sensors transfer measured data, actuators are controlled, and systems are connected wirelessly. In particular, the wireless sensor network (WSN) needs to operate with low cost, low power (energy), and narrow spectrum, which are the most technical challenges for industrial IoT networks. In general, a relay-assisted communication network has been known to overcome scarce energy problems, and a spectrum-sharing technique has been considered as a promising technique for the radio spectrum shortage problem. In this paper, we propose a phase steering based hybrid cooperative relaying (PSHCR) technique for the generic relay-assisted spectrum-shared WSN, which consists of a secondary transmitter, multiple secondary relays (SRs), a secondary access point, and multiple primary access points. Basically, SRs in the proposed PSHCR technique operate with decode-and-forward (DF) relaying protocol, but it does not abandon the SRs that failed in decoding at the first hop. Instead, the SRs operate with amplify-and-forward (AF) protocol when they failed in decoding at the first hop. Furthermore, the SRs (regardless of operating with AF or DF protocol) that satisfy interference constraints to the primary network are allowed to transmit a signal to the secondary access point at the second hop. Note that phase distortion is compensated through phase steering operation at each relay node before second-hop transmission, and thus all relay nodes can operate in a fully distributed manner. Finally, we validate that the proposed PSHCR technique significantly outperforms the existing best single relay selection (BSR) technique and cooperative phase steering (CPS) technique in terms of outage performance via extensive computer simulations.

Recently, reconfigurable intelligent surfaces (RISs) have received much interest from both academia and industry due to their flexibility and cost-effectiveness in adjusting the phase and amplitude of wireless signals with low-cost passive reflecting elements. In particular, many RIS-aided techniques have been proposed to improve both data rate and energy efficiency for 6G wireless communication systems. In this paper, we propose a novel RIS-based channel randomization (RCR) technique for improving physical-layer security (PLS) for a time-division duplex (TDD) downlink cellular wire-tap network which consists of a single base station (BS) with multiple antennas, multiple legitimate pieces of user equipment (UE), multiple eavesdroppers (EVEs), and multiple RISs. We assume that only a line-of-sight (LOS) channel exists among the BS, the RISs, and the UE due to propagation characteristics of tera-hertz (THz) spectrum bands that may be used in 6G wireless communication systems. In the proposed technique, each RIS first pseudo-randomly generates multiple reflection matrices and utilizes them for both pilot signal duration (PSD) in uplink and data transmission duration (DTD) in downlink. Then, the BS estimates wireless channels of UE with reflection matrices of all RISs and selects the UE that has the best secrecy rate for each reflection matrix generated. It is shown herein that the proposed technique outperforms the conventional techniques in terms of achievable secrecy rates.

In this paper, a novel beamforming technique is proposed as the over-the-air computation (AirComp) framework in a multiple-input multiple-output (MIMO) Internet-of-things (IoT) network consisting of multiple IoT sensors (STAs) and a single access point (AP). We assume that each IoT device has the channel state information (CSI) from itself to the AP and the AP has the global CSI of all IoT devices. We consider the mean squared error (MSE), which represents the reliability of function computation, as a performance metric. In short, each IoT device exploits maximum-ratio transmission (MRT) as a transmit beamforming technique to improve MSE performance by taking full advantage of multiple transmit antennae. Moreover, for the receive beamforming, we first consider a receive antenna selection (RAS) technique as the simplest beamforming method at the AP. Then, a semi-definite relaxation (SDR) method and a successive convex approximation (SCA) algorithm are considered and compared with each other in terms of MSE. Finally, we propose a novel two-step beamforming algorithm to further improve the MSE performance of the aforementioned techniques. We have numerically verified through computer simulations that the proposed framework has an improved MSE performance of about 6dB compared to the conventional single-input multiple-output (SIMO) AirComp, even with only two transmit antennae, and the modified MRT outperforms the other transmit beamforming techniques. Furthermore, the proposed receive beamforming technique, a two-step algorithm, shows the best performance in terms of MSE compared to prior studies.

In this paper, we propose a novel opportunistic interference alignment technique for spectrum-shared radar and uplink cellular communication systems where both systems are equipped with multiple antennas. In the proposed OIA technique, the radar system sends its signal so that the radar signal is received into interference space at base stations (BSs) of the cellular system, while each uplink user (UE) generates its transmit beamforming vector so that communication signals are received within interference space at the radar receiver. Moreover, to achieve better sum-rate performance of the cellular communication system, the BS selects the UEs which results in sufficiently small interference to other cells for the uplink communication. With the proposed OIA technique, detection performance of the radar system is protected, while the communication system achieves satisfactory sum-rate performance. Through extensive computer simulations, we show that the performances of both radar and communication systems with the proposed technique significantly outperform a conventional null-space projection based spectrum sharing scheme.

With the growth of the number of Internet of Things (IoT) devices, a wide range of wireless sensor networks (WSNs) will be deployed for various applications. In general, WSNs are constrained by limitations in spectrum and energy resources. In order to circumvent these technical challenges, we propose a novel cooperative phase-steering (CPS) technique with a simple on-off power control for generic spectrum sharing-based WSNs, which consists of a single secondary source (SS) node, multiple secondary relay (SR) nodes, a single secondary destination (SD) node, and multiple primary destination (PD) nodes. In the proposed technique, each SR node that succeeds in packet decoding from the SS and for which its interference power to the PD nodes is lower than a certain threshold is allowed to transmit the signal to the SD node. All SR nodes that are allowed to transmit signals to the SD node adjust the phase of their transmit signal such that the phase of received signals at the SD node from the SR nodes is aligned to a certain angle. Moreover, we mathematically analyze the outage probability of the proposed scheme. Our analytical and simulation results show that the proposed technique outperforms the conventional cooperative relaying schemes in terms of outage probability. Through extensive computer simulations, it is shown that the analytical results match well with the simulated outage probability as a lower bound.

Achieving energy efficiency (EE) fairness among heterogeneous mobile devices will become a crucial issue in future wireless networks. This paper investigates a deep learning (DL) approach for improving EE fairness performance in interference channels (IFCs) where multiple transmitters simultaneously convey data to their corresponding receivers. To improve the EE fairness, we aim to maximize the minimum EE among multiple transmitter−receiver pairs by optimizing the transmit power levels. Due to fractional and max-min formulation, the problem is shown to be non-convex, and, thus, it is difficult to identify the optimal power control policy. Although the EE fairness maximization problem has been recently addressed by the successive convex approximation framework, it requires intensive computations for iterative optimizations and suffers from the sub-optimality incurred by the non-convexity. To tackle these issues, we propose a deep neural network (DNN) where the procedure of optimal solution calculation, which is unknown in general, is accurately approximated by well-designed DNNs. The target of the DNN is to yield an efficient power control solution for the EE fairness maximization problem by accepting the channel state information as an input feature. An unsupervised training algorithm is presented where the DNN learns an effective mapping from the channel to the EE maximizing power control strategy by itself. Numerical results demonstrate that the proposed DNN-based power control method performs better than a conventional optimization approach with much-reduced execution time. This work opens a new possibility of using DL as an alternative optimization tool for the EE maximizing design of the next-generation wireless networks.

In this paper, we propose a pseudo-random beamforming (PRBF) technique for improving physical-layer security (PLS) in multiple input multiple output (MIMO) downlink cellular networks consisting of a legitimate base station (BS), multiple legitimate mobile stations (MSs) and potential eavesdroppers. The legitimate BS can obtain available potential eavesdroppers’ channel state information (CSI), which is registered in an adjacent cell. In the proposed PRBF technique, the legitimate BS pseudo-randomly generates multiple candidates of the transmit beamforming (BF) matrix, in which each transmit BF matrix consists of multiple orthonormal BF vectors and shares BF information with legitimate MSs before data transmission. Each legitimate MS generates receive BF vectors to maximize the receive signal-to-interference-plus-noise (SINR) for all pseudo-randomly generated transmit beams and calculates the corresponding SINR. Then, each legitimate MS sends a single beam index and the corresponding SINR value of the BF vector that maximizes the received SINR for each BF matrix since a single spatial stream is sent to each legitimate MS. Based on the feedback information from legitimate MSs and the CSI from the legitimate BS to eavesdroppers, the legitimate BS selects the optimal transmit BF matrix and the legitimate MSs that maximizes secrecy sum-rate. We also propose a codebook-based opportunistic feedback (CO-FB) strategy to reduce feedback overhead at legitimate MSs. Based on extensive computer simulations, the proposed PRBF with the proposed CO-FB significantly outperforms the conventional random beamforming (RBF) with the conventional opportunistic feedback (O-FB) strategies in terms of secrecy sum-rate and required feedback bits.

In this paper, we consider a 2 × 2 space-time line coded (STLC) system having two-transmit and two-receive antennas. To improve the secrecy rate of the STLC system, in which an illegitimate receiver eavesdrops the information delivered from the STLC transmitter to the STLC receiver, we propose an artificial noise (AN) injection method. By exploiting the STLC structure, a novel AN for the STLC is designed and its optimal power loading factor is derived. Numerical results verify that the proposed secure STLC systems with the designed AN injection and the power control method can significantly improve the secrecy rate compared to the conventional STLC systems. It is observed that the proposed method is more effective if there is a significant gap between the main-channel and the eavesdropper-channel gains.

Photovoltaic (PV) output power inherently exhibits an intermittent property depending on the variation of weather conditions. Since PV power producers may be charged to large penalties in forthcoming energy markets due to the uncertainty of PV power generation, they need a more accurate PV power prediction scheme in energy market operation. In this paper, we characterize the effect of PV power prediction errors on energy storage system (ESS)-based PV power trading in energy markets. First, we analyze the prediction accuracy of two machine learning (ML) schemes for the PV output power and estimate their error distributions. We propose an efficient ESS management scheme for charging and discharging operation of ESS in order to reduce the deviations between the day-ahead (DA) and real-time (RT) dispatch in energy markets. In addition, we estimate the capacity of ESSs, which can absorb the prediction errors and then compare the PV power producer’s profit according to ML-based prediction schemes with/without ESS. In case of ML-based prediction schemes with ESS, the ANN and SVM schemes yield a decrease in the deviation penalty by up to 87% and 74%, respectively, compared with the profit of those schemes without ESS.

Wireless avionics intra-communication (WAIC) refers to a wireless communication system among electronic components (e.g., sensors and actuators) that are integrated or installed in an aircraft and it is proposed to replace heavy and expensive wired communication cables. Recently, the use of a frequency band (4.2–4.4 GHz) for the WAIC (so-called, WAIC band) has been approved by international telecommunication union (ITU). Accordingly, several existing wireless protocols such as IEEE 802.11 and IEEE 802.15 are being considered as candidate techniques for the intra-avionics sensor network. In this paper, we perform a real field experiment to investigate wireless channel characteristics in intra-avionics sensor networks at the WAIC bands by a software-defined radio platform (universal software radio peripheral, USRP) and self-produced monopole antennas for the WAIC band. Through the experiment, we validated the feasibility of IEEE 802.11 protocol for the intra-avionics sensor network at the WAIC band in real aircraft environments. Furthermore, based on the measurement data, we evaluated the bit error rate (BER) performance of multiple antenna techniques where we considered the maximum ratio combining (MRC) for the multi-antenna receiver and the space-time block coding (STBC) for the multi-antenna transmitter.

In this paper, we propose a novel machine learning (ML) based link-to-system (L2S) mapping technique for inter-connecting a link-level simulator (LLS) and a system-level simulator (SLS). For validating the proposed technique, we utilized 5G K-Simulator, which was developed through a collaborative research project in Republic of Korea and includes LLS, SLS, and network-level simulator (NS). We first describe a general procedure of the L2S mapping methodology for 5G new radio (NR) systems, and then, we explain the proposed ML-based exponential effective signal-to-noise ratio (SNR) mapping (EESM) method with a deep neural network (DNN) regression algorithm. We compared the proposed ML-based EESM method with the conventional L2S mapping method. Through extensive simulation results, we show that the proposed ML-based L2S mapping technique yielded better prediction accuracy in regards to block error rate (BLER) while reducing the processing time.

When multiple mobile sensors and actuators share a common wireless mesh backbone network of defence systems, the channel allocation mechanism must guarantee the heterogeneous link requirements under conditions of uncertainty. In this paper, a robust channel allocation mechanism is proposed by exploiting partially overlapped channels for directional multi-channel wireless mesh networks. The approach relies on a chance-constrained optimization problem, in which the objective is to minimize the spectrum usage of the network, and the constraints are the signal-to-interference-plus-noise ratio requirements of links with uncertainty. We convert the proposed integer non-linear optimization problem into a mixed-integer convex problem by using efficient transition and approximation. The optimal channel allocation is obtained by solving the proposed optimization problem which adapts to the heterogeneous link and robustness requirements. The simulation results show that the proposed method ensures the heterogeneous link requirements under uncertain conditions while minimizing the spectrum usage of the network.

This study considers a ultra-dense network (UDN) in which the enormous number of base stations (BSs) are densely deployed to support the massive amount of data traffic generated by many mobile devices. In this paper, we propose an approximate thinning-based judicious network control algorithm for energy-efficient UDNs (ACEnet) to improve the area throughput while diminishing the network energy consumption. The main idea of the proposed ACEnet algorithm is to judiciously adjust the modes of the BSs according to active-user density based on the thinning operation in stochastic geometry framework. The stochastic geometry framework is exploited to analyze the performance of the proposed algorithm, which includes the signal-to-interference-plus-noise ratio (SINR), average achievable rate of users, area throughput, and energy efficiency. Through intensive simulations, it shows that the proposed algorithm outperforms conventional algorithms. We also demonstrate that the analytical results are well matched with the simulation results.

Laser detection and ranging (LADAR) systems are commonly used to acquire real-time three-dimensional (3D) images using the time-of-flight of a short laser pulse. A static unitary detector (STUD)-based LADAR system is a simple method for obtaining real-time high-resolution 3D images. In this study, a switched 4-to-1 transimpedance combining amplifier (TCA) is implemented as a receiver front-end readout integrated circuit for the STUD-based LADAR system. The 4-to-1 TCA is fabricated using a standard 0.18 μm complementary metal-oxide-semiconductor (CMOS) technology, and it consists of four independent current buffers, a two-stage signal combiner, a balun, and an output buffer in one single integrated chip. In addition, there is a switch on each input current path to expand the region of interest with multiple photodetectors. The core of the TCA occupies an area of 92 μm × 68 μm, and the die size including I/O pads is 1000 μm × 840 μm. The power consumption of the fabricated chip is 17.8 mW for a supplied voltage of 1.8 V and a transimpedance gain of 67.5 dBΩ. The simulated bandwidth is 353 MHz in the presence of a 1 pF photodiode parasitic capacitance for each photosensitive cell.

We introduce a distributed protocol to achieve multiuser diversity in a multicell multiple-input multiple-output (MIMO) uplink network, referred to as a MIMO interfering multiple-access channel (IMAC). Assuming both no information exchange among base stations (BS) and local channel state information at the transmitters for the MIMO IMAC, we propose a joint beamforming and user scheduling protocol, and then show that the proposed protocol can achieve the optimal multiuser diversity gain, i.e., KMlog(SNRlog N), as long as the number of mobile stations (MSs) in a cell, N, scales faster than SNR K M − L 1 − ϵ for a small constant ϵ > 0, where M, L, K, and SNR denote the number of receive antennas at each BS, the number of transmit antennas at each MS, the number of cells, and the signal-to-noise ratio, respectively. Our result indicates that multiuser diversity can be achieved in the presence of intra-cell and inter-cell interference even in a distributed fashion. As a result, vital information on how to design distributed algorithms in interference-limited cellular environments is provided.

Improving energy efficiency (EE) of mobile communication systems (MCSs) has been considered a key aim in recent years, and has been the subject of intense research interest. One of the simplest yet most powerful ways to increase the EE is to turn off redundant communication entities whose operation does not greatly affect the overall performance of the MCS. In this paper, we propose a novel on–off power control scheme for femto-cell base stations (FBSs) considering cooperative transmission in which multiple FBSs collaborate on the same data transmission. In the proposed scheme, the operation of the redundant FBSs is halted in an adaptive manner. For the proper determination of redundant FBSs with low computational complexity, we propose using the level of contribution (LOC), which specifies the importance of a given FBS in the cooperative transmission. Redundant FBSs are chosen based on their LOC value, and these FBSs are turned off in order to reduce the power consumption of MCSs while minimizing the degradation of the overall throughput of cooperative transmissions. The performance of the proposed scheme is verified through extensive simulations, which shows that near-optimal performance can be achieved without excessive computations.