Reconfigurable Intelligent surface (RIS) has emerged as a candidate technology for enhancing coverage in millimeter wave wireless networks at a lower energy and cost footprint. RIS has several antenna elements that can each be configured to reflect impinging electromagnetic waves after imparting a chosen phase shift with possibly some amplitude attenuation (a.k.a. chosen reflection coefficient). Over the canonical RIS-enabled communications scenario, an optimal choice of reflection coefficients (or optimal RIS pattern) can be efficiently determined for an ideal unit-amplitude unconstrained phase alphabet. However, for most practical RIS that entail finite alphabets with amplitude imbalance and per-group-of-elements control, efficiently determining optimal patterns remain open problems. In this paper we resolve two such open problems by designing optimal and efficient pattern determination algorithms for binary and quaternary alphabets. We show that our algorithms can noticeably improve over the state-of-art conventional heuristic, especially in the presence of high amplitude imbalance and more restrictive per-group control. The designed algorithms also yield companion sets, which we show offer very significant advantages in RIS pattern selection under interference limit (leakage suppression) constraints.

We investigate a transmission mechanism aiming to improve the data rate between a base station (BS) and a user equipment (UE) through deploying multiple relaying UAVs. We consider the effect of interference incurred by another established communication network, which makes our problem challenging and different from the state of the art. We aim to design the 3D trajectories and power allocation for the UAVs to maximize the data flow of the network while keeping the interference on the existing communication network below a threshold. We utilize the mobility feature of the UAVs to evade the (un)-intended interference caused by (un)-intentional interferers. To this end, we propose an alternating-maximization approach to jointly obtain the 3D trajectories and the UAVs transmission powers. We handle the 3D trajectory design by resorting to spectral graph theory and subsequently address the power allocation through convex optimization techniques. We also approach the problem from the intentional interferer’s perspective where smart jammers chase the UAVs to effectively degrade the data flow of the network. We also extend our work to the case for multiple UEs. Finally, we demonstrate the efficacy of our proposed method through extensive simulations.

Physical layer security (PLS) techniques can help to protect wireless networks from eavesdropper attacks. In this paper, we consider the authentication technique that uses fingerprint embedding to defend 5G cellular networks with unmanned aerial vehicle (UAV) systems from eavesdroppers and intruders. Since the millimeter wave (mmWave) cellular networks use narrow and directional beams, PLS can take further advantage of the 3D spatial dimension for improving the authentication of UAV users. Considering a multi-user mmWave cellular network, we propose a power allocation technique that jointly takes into account splitting of the transmit power between the precoder and the authentication tag, which manages both the secrecy as well as the achievable rate. Our results show that we can obtain optimal achievable rate with expected secrecy.

The demand of massive access to the same multimedia content at the same time is one major challenge for next-generation cellular networks in densely-packed urban areas. The content-aware multicast transmission strategies provide promising solutions to such use cases involving many mobile users trying to fetch the same data. In this work, we consider multigroup multicast transmission with a common message (e.g., multimedia content), in which different multicast groups are interested along with their private multicast messages. We further assume that a relay helps the cellular base station (BS) disseminate multicast content to the users experiencing high path loss and/or blockage. We propose superposition and concatenated coding schemes, denoted by SC and CC, respectively, to transmit the common and private multicast messages. In order to maximize max-min fair (MMF) rates, we design a novel low-complexity alternating-optimization algorithm to compute transmit and relay precoders. We also propose rate-splitting (RS) alternatives of SC and CC schemes together with an iterative algorithm to derive dedicated transmit and relay precoders so as to maximize MMF rates. We rigorously evaluate the performance of the proposed transmission schemes and precoders, and verify the superiority of RS-based schemes in overloaded scenarios without any saturation with increasing signal-to-noise ratio.

Drones will have extensive use cases across various commercial, government, and military sectors, ranging from delivery of consumer goods to search and rescue operations. To maintain safety and security of people and infrastructure, it becomes critically important to quickly and accurately detect non-cooperating drones. In this paper we formulate a received signal strength (RSS) based detector, leveraging the existing wireless infrastructures that might already be serving other devices. Thus the detector should be able to detect the presence of a drone signal buried in radio frequency (RF) interference and thermal noise, in a mixed line-of-sight (LOS) and non-LOS (NLOS) environment. We develop analytical expressions for the probability of false alarm and the probability of detection of a drone, which quantify the impact of aggregate interference and air-to-ground (A2G) propagation characteristics on the detection performance of individual sensors. We also provide analytical expressions for the average network probability of detection, which captures the impact of sensor density on a network's detection coverage. Finally, we find the critical sensor density that maximizes the average network probability of detection for a given requirement of probability of false alarm.

The integration of unmanned aerial vehicles (UAVs) into the terrestrial communications networks with a variety of tasks is viewed as a key technology for 5G and beyond. In this work, we consider the uplink millimeter-wave (mmWave) transmission between a set of UAVs and a base station (BS), where the UAVs deploy uplink non-orthogonal multiple access (NOMA) in multiple clusters. Furthermore, the BS also serves its own desired ground user equipment (UE) in the presence of many other ground UEs associated with other cells, which share the same frequency band. Considering the limited energy budget of UAVs, we formulate an energy efficiency (EE) problem, and propose a solution aided by the Dinkelbach's algorithm and successive convex approximation (SCA). Using realistic air-to-ground (A2G) and terrestrial channel models, we assess the performance of the proposed algorithm under various circumstances (maximum transmit power for UAVs, quality-of-service (QoS) constraint for the desired UE, etc.), and identify the best use cases.

The spectrum scarcity at sub-6 GHz spectrum has made millimeter-wave (mmWave) frequency band a key component of the next-generation wireless networks. While mmWave spectrum offers extremely large transmission bandwidths to accommodate ever-increasing data rates, unique characteristics of this new spectrum need special consideration to achieve the promised network throughput. In this work, we consider the off-grid targets (basis mismatch) problem for mmWave communications. The off-grid effect naturally appears in compressed sensing (CS) techniques adopting a discretization approach for representing the angular domain. This approach yields a finite set of discrete angle points, which are an approximation to the continuous angular space, and hence degrade the accuracy of related parameter estimation. In order to cope with the off-grid effect, we present a novel parameter-perturbation framework to efficiently estimate the channel and the covariance for mmWave networks. The proposed algorithms employ a smart perturbation mechanism in conjunction with a low-complexity greedy framework of simultaneous orthogonal matching pursuit (SOMP), and jointly solve for the off-grid parameters and weights. Numerical results show a significant performance improvement through our novel framework as a result of handling the off-grid effects, which is totally ignored in the conventional sparse mmWave channel or covariance estimation algorithms.

The spectrum-efficient millimeter-wave (mmWave) communications has recently attracted much attention as a viable solution to spectrum crunch problem. In this work, we propose a novel non-orthogonal multiple access (NOMA) framework, which makes use of the directional propagation characteristics of mmWave communications so as to improve the spectral efficiency through non-orthogonal signaling. In particular, we consider one-bit quantized angle information as a limited yet effective feedback scheme describing the channel quality of user equipment (UE) in mmWave bands. The UE pairs for NOMA transmission are then established using not only the one-bit distance feedback as a classical approach, but also the one-bit angle feedback. The proposed strategy is therefore referred to as two-bit NOMA. We also propose a novel hybrid strategy, called combined NOMA, for the circumstances with no UE pair through two-bit NOMA. Whenever no UE pair is available through any NOMA strategy, we resort to single user transmission (SUT) with proper UE selection schemes. The hybrid outage sum-rate performance is also analyzed thoroughly with the respective outage and rate expressions. The numerical results verify that the proposed strategy outperforms one-bit NOMA schemes with either angle- or distance-only feedback, and has a very close outage sum-rate performance to that for the optimal full-resolution feedback.

In this paper, we tackle channel estimation in millimeter-wave hybrid multiple-input multiple- output systems by considering off-grid effects. In particular, we assume that spatial parameters can take any value in the angular domain, and need not fall on predefined discretized angles. Instead of increasing the number of discretized points to combat off-grid effects, we use implicit Dirichlet kernel structure in the Fourier domain, which conventional compressed sensing methods do not use. We propose greedy low-complexity algorithms based on orthogonal matching pursuit (OMP); our core idea is to traverse the Dirichlet kernel peak using estimates of the discrete Fourier transform. We demonstrate the efficacy of our proposed algorithms compared to standard OMP reconstruction. Numerical results show that our proposed algorithms obtain smaller reconstruction errors when off-grid effects are accounted for.

The deployment of the unmanned aerial vehicle (UAV) has been foreseen as a promising technology for the next generation communication networks. The distance limitation imposed by the line of sight RF connection can be removed by using RF coverage from existing commercial cellular service. In this work, we consider a transmission mechanism that aims to improve the data rate between a terrestrial base station (BS) and user equipment (UE) through deploying multiple UAVs relaying the desired data flow. Considering the coexistence of this network with other established communication networks, we take into account the effect of interference, which is incurred by the existing nodes. Our primary goal is to optimize the three-dimensional (3D) trajectories and power allocation for the relaying UAVs to maximize the data flow while keeping the interference to existing nodes below a predefined threshold. An alternating-maximization strategy is proposed to solve the joint 3D trajectory design and power allocation for the relaying UAVs. To this end, we handle the information exchange within the network by resorting to spectral graph theory and subsequently address the power allocation through convex optimization techniques. Simulation results show that our approach can considerably improve the information flow while the interference threshold constraint is met.

We consider a downlink multiuser visible light communications (VLC) network where users randomly change their location and vertical orientation. The non-orthogonal multiple access (NOMA) strategy is adopted to serve multiple users simultaneously, and, hence, to improve spectral efficiency. We propose two novel user scheduling schemes for NOMA, which are referred to as individual and group-based. In order to further reduce the computational complexity and link overhead, novel limited-feedback schemes (on channel quality) are also proposed, which basically involve mean vertical angle (instead of its instantaneous value). Moreover, a two-bit feedback scheme is proposed for group-based user scheduling, which relies on not only distance but also vertical angle (in contrast to conventional one-bit feedback with distance only). The outage probability and sum-rate expressions are derived analytically, which show a very good match with the simulation data. Numerical results verify that the practical feedback scheme with the mean vertical angle achieves a near-optimal sum-rate performance, and the two-bit feedback significantly outperforms the one-bit feedback.

Using radio frequency (RF) coverage from the existing cellular networks is an attractive option to maintain beyond visual line-of-sight (BVLOS) connectivity with drones. These cellular drones can connect with a ground control station (GCS) for control and data delivery wherever cellular service is available. However, RF coverage for these cellular networks has been optimized for the ground users and while they do leak upwards, reliable RF coverage exists to only about 400 feet high. As the drones are becoming more commonly used for activities ranging from emergency responses to aerial deliveries, the base stations covering users both on the ground and in the air with RF transmission cannot scale to the capacity needed to support increasing number of drones. Use of directional beams that are necessary for millimeter wave (mmWave) transmission in the 5G cellular system can reduce interference among users, and hence increase capacity compared to sector based transmissions used for 4G systems without massive MIMO (mMIMO). In this paper, considering the multiplicative capacity gains needed to support large number of drones, we propose a separate mmWave cellular network with optimized coverage for a ''drone corridor'' in the air. We present our current findings in the following areas critical to validating the effectiveness of this proposed network: 1) RF propagation characteristics towards drones in the air compared with propagation towards users on the ground; 2) use of multiple access (MA) technology for increased spectral efficiency for a swarm of drones; 3) optimal design of protected zones and beamforming to secure drone specific wireless communications.

Visible light communications (VLC) has been studied thoroughly in recent years as an alternative or complementary technology to radio frequency communications. The reliability of VLC channels highly depends on the availability and alignment of line of sight links. In this paper, we study the effect of random receiver orientation for mobile users over VLC downlink channels, which affects the existence and quality of line of sight links. Based on the statistics of the receiver location and relative orientation with respect to the transmitter LED, we develop an analytical framework to characterize the statistical distribution of VLC downlink channels, which is then utilized to obtain the outage probability and the bit error rate. Our analysis is generalized for arbitrary distributions of relative orientation and location for a single transmitter, and extended to multiple transmitter case for some certain scenarios. Extensive Monte Carlo simulations show a perfect match between the analytical and the simulation data in terms of both the statistical channel distribution and the resulting bit error rate. Our results also characterize the channel attenuation due to random receiver orientation and location for various scenarios of interest.

Unmanned aerial vehicle (UAV) base stations (BSs) can be a promising solution to provide connectivity and quality-of-service guarantees during temporary events and after disasters. In this paper, we consider a scenario where UAV-BSs are serving a large number of mobile users in a hot spot area (e.g., in a stadium). We introduce non-orthogonal multiple-access (NOMA) transmission at UAV-BSs to serve more users simultaneously considering user distances as the available feedback for a user ordering during NOMA formulation. With millimeter-wave transmission and multi-antenna techniques, we assume that UAV-BS generates directional beams and multiple users are served simultaneously within the same beam. However, due to the limitations of physical vertical beamwidth of the UAV-BS beam, it may not be possible to cover the entire user region at UAV altitudes of practical relevance. During such situations, a beam scanning approach is proposed to maximize the achievable sum rates. We develop a comprehensive framework over which outage probabilities and respective sum rates are derived rigorously and we investigate the optimal operational altitude of UAV-BS to maximize the sum rates using our analytical framework. Our analysis shows that NOMA with distance feedback can provide better outage sum rates than orthogonal multiple access.

Visible light communications (VLC) is an emerging technology with a promise of viable solution to spectrum crunch problem in conventional radio-frequency (RF) bands. In this paper, we consider a downlink multiuser VLC network where users randomly change their location and vertical orientation. In order to increase the spectral efficiency, we consider the non-orthogonal multiple access (NOMA) transmission to serve multiple users simultaneously. In particular, we propose individual and group-based user ordering techniques for NOMA with various user feedback schemes. In order to reduce the computational complexity and link overhead, feedback on the channel quality is proposed to be computed using a mean value of the vertical angle (instead of the exact instantaneous value), as well as the distance information. In addition, a two-bit feedback scheme is proposed for the group-based user scheduling, which relies on both the distance and the vertical angle, and differs from the conventional one-bit feedback of the distance only. The outage probability and sum-rate expressions are derived analytically, which show a very good match with the simulation data. Numerical results verify that the practical feedback scheme with the mean vertical angle achieves a near-optimal sum-rate performance, and the two-bit feedback significantly outperforms the one-bit feedback.

In this paper, we consider the outage performance of the M-BLAST symbol detection algorithm over uncoded quasistatic MIMO channels with spatial multiplexing. The M-BLAST algorithm is known to achieve a superior error performance over its predecessor V-BLAST with a signal-to-noise ratio (SNR) improvement of as large as 2 dB. We evaluate this performance improvement analytically, which has not been studied before, by deriving the outage probability expression over generalized complex binary alphabets with two transmitting and unlimited number of receiving antennas. Although the underlying successive interference cancellation (SIC) receiver introduces a high non-linearity which complicates the analysis, our analytical and simulation results are shown to have a very good match.

Visible light communications (VLCs) are a promising technology to address the spectrum crunch problem in radio frequency networks. A major advantage of VLC networks is that they can use the existing lighting infrastructure in indoor environments, which may have large number of LEDs for illumination. While LEDs used for lighting typically have limited bandwidth, presence of many LEDs can be exploited for indoor VLC networks, to serve each user by multiple LEDs for improving link quality and throughput. In this paper, LEDs are grouped and assigned to the users based on received signal strength from each LED, for which different solutions are proposed to achieve maximum throughput, proportional fairness, and quality of service. Additionally, power optimization of LEDs for a given assignment is investigated, and the Jacobian and Hessian matrices of the corresponding optimization problem are derived. Moreover, for multi-element receivers with LED grouping at the transmitter, an improved optimal combining method is proposed. This method suppresses interference caused by simultaneous data transfer of LEDs and improves the overall signal-to-interference-plus-noise-ratio by 2-5 dB. Lastly, an efficient calculation of channel response is presented to simulate multipath VLC channel with low computational complexity.

Efficient symbol detection algorithms carry critical importance for achieving the spatial multiplexing gains promised by multi-input multi-output (MIMO) systems. In this paper, we consider a maximum a posteriori probability (MAP)-based symbol detection algorithm, called M-BLAST, over uncoded quasi-static MIMO channels. Relying on the successive interference cancellation (SIC) receiver, the M-BLAST algorithm offers a superior error performance over its predecessor V-BLAST with a signal-to-noise ratio (SNR) gain of as large as 2 dB under various settings of recent interest. Performance analysis of the M-BLAST algorithm is very complicated since the proposed detection order depends on the decision errors dynamically, which makes an already complex analysis of the conventional ordered SIC receivers even more difficult. To this end, a rigorous analytical framework is proposed to analyze the outage behavior of the M-BLAST algorithm over binary complex alphabets and two transmitting antennas, which has a potential to be generalized to multiple transmitting antennas and multidimensional constellation sets. The numerical results show a very good match between the analytical and simulation data under various SNR values and modulation alphabets.

A bidirectional LMS algorithm is considered for estimation of fast frequency-selective time-varying channels with a promise of near optimal tracking performance and robustness to parameter imperfections under various scenarios at a practical level of complexity. The performance of the algorithm is verified by the theoretical steady-state MSE analysis and experimental bit error rate (BER) results.

The iterative channel estimation and tracking problem is considered for time-varying frequency-flat fading multi-input multi-output (MIMO) systems. In order to jointly estimate and track the time-varying multi-antenna channel, the pilot symbol assisted modulation (PSAM) technique is generalized to the multi-antenna systems. By distributing the pilot symbols along the transmitted block, i.e., PSAM transmission, the proposed system gains the ability to track the channel variation with the same amount of pilots whereas the system with all the pilots are employed prior to the data block has no tracking capability. The error performance is further improved by iteratively estimating the channel which employs the optimal MMSE filtering and also makes use of the soft probabilities of the coded symbols provided by the decoder. In order to decrease the computational complexity due to the iterative usage of MMSE filtering, we introduce the low-complexity 2-way LMS algorithm based on the forward-backward operation of conventional forward only LMS algorithm. By simulations, 2-way LMS is shown to have a near optimal error performance and highly better channel tracking ability than the conventional LMS algorithm with no significant complexity increase.

A low-complexity iterative channel estimation (ICE) algorithm is proposed with the promise of improved error performance. The new algorithm operates the LMS filter both in the forward and the backward directions along a block. The feedback from the decoder to the estimator is in the form of soft decisions. The pilot symbol assisted modulation (PSAM) is used as the transmission technique. The effect of code choice on various ICE algorithms is also explored by considering the blockwise concatenated codes initially offered for block-fading channels. The performance of the new estimation algorithm with the proposed coding is shown to outperform the conventional estimation algorithms over a fast time-varying Rayleigh fading channel beside its low complexity structure.

Our main goal in this paper is to construct codes that can perform close to information-theoretic limits in time-varying channels. For this purpose, a new turbo-like code is first proposed for the block-fading channel which achieves the same error performance of a recently introduced blockwise concatenated code but with a lower complexity. The effectiveness of the codes are verified by comparing them with information-outage probability. In order to take the advantage of time diversity in time-varying fading channels, we introduce two new codes which are indeed extensions of the ones for block-fading channels. We report that error performance of the proposed codes is close to information- theoretic limits in time-varying channels set out by information-outage probability.