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The application of non-orthogonal multiple access (NOMA) to multi-layer multicast video streaming is envisioned to address the explosively growing demand for capacity which is dominated mostly by multimedia content. In this paper, a joint power allocation and subgrouping scheme is developed to enhance the performance of NOMA-based multi-layer multicast systems. An optimization problem is formulated to maximize the overall sum multicast rate whilst satisfying the maximum transmission power and proportional rate constraints. Due to the complexity of the optimization problem, we first derive two power allocation techniques for the 2-layer case considering arbitrary subgrouping which are based on the iterative implementation and closed-form analysis, respectively. We then generalize the low-complexity closed-form solution for the general multi-layer case. This scheme successively allocates power to each layer stream while assuring that the minimum target rate and proportionality are guaranteed, particularly for the transmission rate of the high-priority base layer stream. A sub-optimal joint power allocation and subgrouping scheme is also designed by incorporating the power allocation scheme into the proposed iterative subgrouping techniques. Simulation results show the effectiveness of the power allocation and subgrouping schemes in enhancing the sum multicast rate performance. In addition, the proposed power allocation scheme ensures substantially higher rates for the base layer stream, which is crucial in robust delivery of standard quality video to all users. [ABSTRACT FROM AUTHOR]

With low-cost energy consumption, the reconfigurable intelligent surface (RIS) technique is a potential solution to the real-time data processing for intelligent transportation systems (ITSs). In this paper, an intelligent transmissive surface is introduced into the vehicular communications, enabling vehicle-to-infrastructure (V2I) signals to penetrate the intelligent RIS to access the base station (BS) on the opposite side of the vehicle. Considering that the vehicle-to-vehicle (V2V) communication reuses the spectrum spanned for V2I link, we investigate the ergodic capacity optimization problem for the vehicle performing V2I communications with the assistance of RIS, while meeting the low-latency and high-reliability requirements of the V2V link. The RIS transmission coefficients and power allocation of vehicles are jointly optimized, for the management of the desired and undesired vehicular communication links. Moreover, the expression of optimal phase shifts is derived in a closed-form, which reveals that the performance gain brought by RIS is proportional to the number of intelligent elements, while inversely proportional to the distance from vehicle-to-BS, in a quadratic form. Moreover, in the case of discrete phase shifts, an intelligent algorithm is proposed for the beamforming design at RIS. Afterwards, with the objective to maximize the ergodic capacity of the V2I link, the optimal power allocation is also proposed. Simulation results confirm the accuracy of the proposed resource allocation strategy, and that the system performance in terms of the ergodic V2I capacity can be significantly improved by the RIS. [ABSTRACT FROM AUTHOR]

Conventional direction-of-arrival (DOA) estimation algorithms are sensitive to array imperfections and outliers, making it challenging to realize accurate estimates in real applications. Facing the challenge, we propose a robust variational Bayesian inference based DOA estimation algorithm using the linear sparse array in this paper, where accurate DOA estimation with increased number of degrees of freedom (DOFs) is realized. With the mixture of von Mises model, a prior-grid scheme is further proposed to alleviate the computational burden introduced by the Bayesian variational inference framework. Since there is no restriction on the prior knowledge of the number of sources, the proposed algorithm is friendly to actual scenarios. Simulation results demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we consider an energy efficient resource allocation technique for a hybrid time division multiple access (TDMA) - non-orthogonal multiple access (NOMA) system. In such a hybrid system, the available time for transmission is divided into several sub-time slots, and a sub-time slot is allocated to serve a group of users (i.e., cluster). Furthermore, signals for the users in each cluster are transmitted based on the NOMA approach. With NOMA, multiple users can be served simultaneously through utilizing power domain multiplexing at transmitter and successive interference cancellation (SIC) at receiver. In this paper, to maximize the energy efficiency (EE), we jointly allocate both the available time slots and the available transmit power in the hybrid TDMA-NOMA system. In particular, we formulate an EE maximization (EE-Max) problem aiming to maximize the overall EE of the system with a per-user minimum rate and transmit power constraints. However, this joint optimization problem is non-convex in nature, and thus, cannot be solved directly. Therefore, we develop an iterative algorithm by approximating the original problem into a convex one with sequential convex approximation (SCA) and a novel second-order cone (SOC) approach. Simulation results demonstrate that the performance of the proposed hybrid TDMA-NOMA system with joint resource allocation outperforms the system with equal time allocation in terms of the overall EE. Simulation results further confirm that the proposed iterative approaches with SCA and SOC techniques converge within a few number of iterations while yielding the solution to the original non-convex problem. [ABSTRACT FROM AUTHOR]

Efficient connectivity in cellular-connected unmanned aerial vehicles (UAV)s is limited by scarcity of the radio spectrum and strong inter-cell interference (ICI). To address these issues, we propose an aerial-terrestrial network non-orthogonal multiple access (ATN-NOMA) scheme. In this proposed scheme, we pair the aerial user (AU) and terrestrial user (TU) in a NOMA setting to leverage their asymmetric channel gains and rate demands in downlink communications. In ATN-NOMA, the strong ICI issue at the AU receiver is further managed by an elevation-angle based user association, equipping the AU with an adjustable beamwidth directional antenna, and forming a beamforming among the coordinated terrestrial base stations (BS)s. We then obtain the optimal beamwidth and suboptimal power allocation so that the TUs’ sum-rate is maximized subject to the AU’s Quality-of-Service (QoS) requirement. The corresponding optimization problem is non-convex in which we exploit the structure of the problem and apply successive convex approximation (SCA) to obtain a suboptimal solution. We then derive the statistical properties, which consequently enable us to estimate the aggregated ICI. In cases where no interfering BSs have the same elevation angle as the coordinated BSs, we further approximate the AU’s outage probability. We then compare the TUs’ sum-rate and the outage probability of the ATN-NOMA with multiple existing schemes. Extensive simulation results show that our proposed ATN-NOMA scheme outperforms existing schemes by 52-91% in terms of the sum-rate, and its analytical outage probability can be as low as the order of $10^{-17}$. Furthermore, we show that the pairing of AU and TU in multi-cell networks remains beneficial, subject to effective mitigation of ICI. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) assisted non-orthogonal multiple access (NOMA) transmission can effectively improve the energy/spectrum efficiency in wireless networks. This paper designs a low-complexity scheme to achieve the balanced tradeoff between the sum-rate and power consumption in a RIS-assisted NOMA system, which can be measured by energy efficiency. To solve the formulated problem effectively, the original non-convex problem is first decomposed into two subproblems, i.e., beamforming optimization and phase shift optimization. Alternating optimization is proposed to solve these two subproblems iteratively. In particular, successive convex approximation (SCA) is utilized to convert the non-convex constraints to convex ones. The provided simulation results demonstrate that the proposed scheme can achieve superior performance on energy efficiency compared to the random phase shifts and orthogonal multiple access (OMA) schemes. [ABSTRACT FROM AUTHOR]

In this paper, we give performance analysis in an unmanned-aerial-vehicle (UAV) assisted ground short-packet communication system, which adopts a UAV as a wireless relay to accomplish ultra-reliable and low-latency communications (URLLC) between a base station and a user equipment (UE). Both large-scale fading, which is modeled as the free space path loss or the classic 3-Dimensional channel, and small-scale fading, which follows Nakagami- $m$ distribution, are considered in our system model. We first derive the closed-form expressions for the average overall block error ratio (BLER) at the UE by adopting Gasssian-Legendre quadrature (GLQ) method. Then, under the reliability and latency constraints at the UE, we apply both bisection search and one-dimensional search algorithms to jointly optimize blocklength, transmit power and UAV flying height for maximizing the energy-efficiency (EE) of UAV. Finally, Monte-Carlo simulations are provided to verify our analytical results. [ABSTRACT FROM AUTHOR]

The combination of time division multiple access (TDMA) and non-orthogonal multiple access (NOMA), referred to as hybrid TDMA-NOMA system, is considered as a potential solution to meet the unprecedented requirements for future wireless networks. While recent resource allocation techniques aiming to individually maximize either spectral efficiency (SE) or energy efficiency (EE), this paper considers an SE-EE trade-off based technique for a hybrid TDMA-NOMA system. This design offers an additional degree of freedom in resource allocation. The proposed design is formulated as a non-convex multi-objective optimization (MOO) problem. The MOO framework is reformulated as a single-objective optimization (SOO) problem by combining the multi-objectives through a weighted-sum objective function. With this, each of the original objectives is assigned with a weight factor to reflect its importance in the design. Then, the sequential convex approximation (SCA) and a second-order cone (SOC) approach are jointly utilized to deal with the non-convexity issues of the SOO problem. Simulation results reveal that the proposed trade-off based design strikes a good balance between the objective functions, while meeting the instantaneous requirements of the system. [ABSTRACT FROM AUTHOR]

Due to the scarcity of channel availability in IEEE 802.11p standard, applications related to infotainment and multimedia services are vulnerable to suffer from delays and connectivity. Cognitive radio (CR) has the potential to overcome the issue of spectrum scarcity. By making use of the CR technology, secondary users (SU) can access a radio frequency spectrum other than 802.11p through spectrum sensing. Majority of low complex existing algorithms are based on energy detection that are considering the static environment of SUs. In practice, the algorithms, which considers mobility are mainly focused on low vehicle speed. However, the combined effect of primary user (PU) activity statistics and SU mobility has not been tackled while evaluating the performance of opportunistic spectrum access. In particular, this work considers the joint impact of PU activity and vehicle mobility on spectrum sensing performance by considering single lane and double lane vehicular scenarios. We also evaluate the impact of traffic densities on sensing performance. The main contribution of this work is to show the impact of PU activity statistics on sensing performance by deriving analytical expressions for miss-detection probability. These expressions are used for analysis and simulation of cognitive radio enabled vehicular communications. From our observations, it is noted that the probability of vehicle connectivity is improved approximately by 50 $\%$ for initial distance of SU when spectrum sensing is employed under PU activity. [ABSTRACT FROM AUTHOR]

Orthogonal space-time block coding (OSTBC) in multiple-antenna wireless systems has recently emerged as one of the most promising reliability-enhancing technologies for high-speed, high-quality data services. In this paper, we propose a technique to achieve joint channel estimation and symbol detection for OSTBC in frequency-selective fading channels. The key observation is that a multiple-input-single-output system, which is using OSTBC, can be transformed into an equivalent single-input-multiple-output system using the implicit redundancy in OSTBC. This allows a probabilistic method, known as the Baum-Welch algorithm, to be applied at each output branch. As each output branch is a function of the same input, redundant information may be exchanged between the multiple branches to improve detection performance. The proposed technique does not require multiple antennas at the receiver and only has moderate computational complexity. Furthermore, the Cramer-Rao lower bound (CRB) is also developed to facilitate performance analysis. Simulation results are provided to demonstrate the performance of the proposed algorithm. Index Terms--Channel estimation, Cramer-Rao lower bound (CRB), iterative receivers, orthogonai space-time block coding (OSTBC), symbol detection.

Air ground integrated mobile cloud computing (MCC) provides unmanned aerial vehicles (UAVs) the capability to act as an aerial relay with more flexibility and resilience. In the cloud computing architecture, the data generated by ground users (GUs) can be offloaded to the remote server for fast processing. However, the heterogeneity of mobile tasks makes the data size distributed among GUs unbalanced. Besides, the energy efficiency of UAVs movement should be carefully considered for sustainable flight and obstacle avoidance. In general, such a joint trajectory issue can hardly be formulated as a convex optimization in unpredictable and dynamic environments. This paper proposes a potential game combined multi-agent deep deterministic policy gradient (MADDPG) approach to optimize multiple UAVs' trajectory with the consideration of GUs' offloading delay, energy efficiency as well as obstacle avoidance system. In specific, we first model the issue as a mixed integer non-linear problem (MINP), in which the service assignment between multi-user and multi-UAV is solved by potential game. The convergence to a Nash Equilibrium (NE) can be achieved by distributive service assignment update with infinite iteration. Then, we optimize the trajectory with obstacle avoidance at each UAV by MADDPG approach, which has a great advantage of centralized-training and decentralized-execution to reduce the global synchronized communication overhead. UAVs movement can be optimized in continuity rather than other deep reinforcement learning (DRL) approaches generating discrete simple actions. Experiments demonstrate the proposed game-combined learning algorithm can minimize the offloading delay, enhance UAVs’ energy efficiency and avoid the obstacles at the same time. [ABSTRACT FROM AUTHOR]

In this paper, we present the delay-constrained performance analysis of a multi-antenna-assisted multiuser non-orthogonal multiple access (NOMA) based spectrum sharing system over Rayleigh fading channels. We derive analytical expressions for the sum effective rate (ER) for the downlink NOMA system under a peak interference constraint. In particular, we show the effect of the availability of different levels of channel state information (instantaneous and statistical) on the system performance. We also show the effect of different parameters of interest, including the peak tolerable interference power, the delay exponent, the number of antennas and the number of users, on the sum ER of the system under consideration. An excellent agreement between simulation and theoretical results confirms the accuracy of the analysis. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is considered as a potential multiple access technique for supporting massive number of devices with high spectral efficiency for the 5 G and beyond networks. Simultaneous wireless information and power transfer (SWIPT) is considered as an efficient solution for fully autonomous and sustainable communication networks. In this paper, application of SWIPT in heterogeneous networks (HetNets) employing cooperative NOMA (CNOMA) is investigated. The HetNets consists of macro-base stations (MBS) under-laid by small-base stations (SBS). The distribution of MBSs follow Poisson point process model, while the SBS tier supports NOMA and carrier sensing for its transmission. Carrier sensing helps in reducing interference by blocking the base stations within a specific range from transmitting. In this work, the analysis at SBS tier is carried out in two phases. In the direct phase transmission, the SBS transmits the superimposed signal to a user pair, comprising of a cell-centre user (CCU) and a cell-edge user (CEU), using NOMA principle. The CCU acts as a cooperative relay to forward information to the CEU in the cooperative phase. Unlike existing literature, instead of using only the superimposed signal for energy harvesting (EH), in this work, the cooperating user (i.e. CCU) employs EH using interference from the adjacent base stations along with the EH from the superimposed signal. Expressions for outage probability and throughput are derived at the user pair served using NOMA. Comparison of the proposed EH system with existing solutions are highlighted and useful insights are drawn. Monte Carlo simulations are carried out to validate the analytical results. [ABSTRACT FROM AUTHOR]

The effective combination of physical layer security communication and intelligent reflecting surface (IRS) technology has recently attracted extensive attention to improve the system security. Unlike existing works that mostly focus on single-carrier systems, we consider an IRS-assisted multi-carrier MIMO wireless physical layer security communication system, which consists of a legitimate transmitter, a legitimate receiver, an IRS node and an eavesdropper. With the aim of maximizing the sum secrecy rate, the multi-carrier transmit beamforming and IRS reflecting coefficient matrix are jointly optimized under the constraints on the transmit power budget and unit modulus of IRS reflecting coefficients. Since the formulated problem is non-convex, an alternate optimization (AO) algorithm is proposed to deal with it. Specifically, for the given IRS reflecting coefficient matrix, the minorization-maximization (MM) scheme is adopted to approximate the objective function of the subproblem and following that, the closed-form solution of the multi-carrier transmit beamforming is obtained through the Lagrange multiplier method. Then, for the given multi-carrier beamforming, the IRS reflecting coefficient matrix is also optimized through the MM scheme and a suboptimal closed-form solution that satisfies the KKT conditions is derived. Moreover, the discussion is extended to the discrete IRS phase shift case and a heuristic projection method (HPM) is then proposed. Finally, the simulation results validate the effectiveness of the proposed AO based algorithm. [ABSTRACT FROM AUTHOR]

This paper investigates a novel joint content caching and energy harvesting scheme to enhance unmanned aerial vehicle (UAV) communications in Internet of Things non-orthogonal multiple access (NOMA) network, where a UAV is acted as an aerial relay to serve users on demand. In particular, a neoteric gravitational search-based multi-constraint optimization algorithm is designed to maximize the throughput of the served users by jointly optimizing power allocation, energy harvesting, and time scheduling schemes. The algorithm engages two main characteristics: 1) classification of multiple constraints, which is for reducing the complexity of the problem solving process due to multiple iterations, and 2) design of force sets, which aims to enhance the global search for the optimal solution at the feasible region boundary. Finally, simulations are provided to show the effective convergence and superiority of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is an important technology for the forthcoming 5 G and beyond. However, its privacy often suffers from adversarial eavesdropping, especially for the users with higher transmit power. In this paper, we propose a jamming-aided secure transmission scheme for cooperative NOMA networks with a full-duplex (FD) relay. In this scheme, two pairs of users perform secure transmission with the help of a decode-forward (DF) relay, which forwards information and generates artificial jamming to counteract eavesdropping. The precoding vectors are designed to zero-force the artificial jamming at legal receivers. Then, the channel statistics are calculated, based on which the secrecy rates of legitimate signals are analyzed and the expressions of secrecy outage probability (SOP) are derived. Furthermore, three benchmark schemes are also presented with their performance analyzed to verify the advantage of the proposed scheme. Simulation results show the accuracy of our analysis, and demonstrate that the proposed scheme can effectively reduce the SOP and improve the effective secrecy throughput via artificial jamming and FD relaying. [ABSTRACT FROM AUTHOR]

In cognitive radio networks (CRNs), secondary users (SUs) can opportunistically access the licensed bands through spectrum sensing while primary users (PUs) are inactive. While collaborative spectrum sensing (CSS) exploits the benefits of cooperation, the spectrum sensing data falsification (SSDF) attackers are subsequently introduced, which aim at undermining the performance of CRNs. We thus are motivated to maximize the throughput of the CRNs under SSDF attacks. First, to better discern SSDF attackers, we designate a double reputation based algorithm to differentiate the SSDF attackers and honest secondary users (HSUs). Then the trade off problem is formulated to find the optimal network parameters including, sensing duration, global decision threshold, energy detection threshold, reputation thresholds for maximizing the throughput of the secondary users network (SUN) subject to limited interference with the PUs. To address the non-convexity of the optimization problem, dummy variables are introduced and the alternative optimization method is adopted. Numerical results show that the proposed algorithm is effective in increasing throughput of the SUN with sufficient protection to the PUs. [ABSTRACT FROM AUTHOR]

This paper studies the application of network non-orthogonal multiple access (N-NOMA) to vehicular communication networks, modeled by a Poisson line Cox point process (PLC). Particularly, the road infrastructure is modeled by a Poisson line point process (PLP), whereas base stations (BSs) and users are located according to 1D homogeneous Poisson point processes (HPPPs) on each road. In the considered N-NOMA scheme, there are two types of users, i.e., coordinated multi-point (CoMP) users which are far from their BSs and NOMA users which are close to their BSs, where the CoMP users and the NOMA users are served simultaneously by applying the principle of NOMA. Specifically, the BSs collaborate with each other to provide reliable transmission for the CoMP user by applying Almouti coding, while each BS employs superposition coding to opportunistically serve an additional NOMA user. Compared to a conventional OMA based scheme, where only a CoMP user is served, the proposed N-NOMA scheme significantly improves the performance in terms of outage sum rates and user connectivity, since more users are served in the same resource block. A comprehensive analytical framework is developed to characterize the system level performance of the proposed N-NOMA scheme by applying PLC. Closed form expressions for the outage probabilities achieved by the CoMP and NOMA users are obtained. Computer simulation results are provided to show the superior performance of the proposed scheme and also validate the accuracy of the developed analytical results. [ABSTRACT FROM AUTHOR]

The combination of non-orthogonal multiple access (NOMA) and intelligent reflecting surface (IRS) is an efficient solution to significantly enhance the energy efficiency of the wireless communication system. In this paper, a downlink multi-cluster NOMA network is considered, where each cluster is supported by one IRS. This paper aims to minimize the transmit power by jointly optimizing the beamforming, the power allocation and the phase shift of each IRS. The formulated problem is non-convex and challenging to be solved due to the coupled variables, i.e., the beamforming vector, the power allocation coefficient and the phase shift matrix. To address this non-convex problem, an alternating optimization based algorithm is proposed. Specifically, the primal problem is divided into two subproblems for beamforming optimization and phase shifting feasiblity, where the two subproblems are solved iteratively. Moreover, to guarantee the feasibility of the beamforming optimization problem, an iterative algorithm is proposed to search the feasible initial points. To reduce the complexity, a simplified algorithm based on partial exhaustive search for this system model is also proposed. Simulation results demonstrate that the proposed alternating algorithm can yield a better performance gain than the partial exhaustive search algorithm, NOMA with random IRS phase shift scheme and OMA-IRS scheme. [ABSTRACT FROM AUTHOR]

This paper investigates unmanned aerial vehicle (UAV) data collection systems with different multiple access schemes, where a rotary-wing UAV is dispatched to collect data from multiple ground nodes (GNs). Our goal is to maximize the minimum UAV data collection throughput from GNs for both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) transmission, subject to the energy budgets at both the UAV and GNs, namely double energy limitations. 1) For OMA, we propose an efficient algorithm by invoking alternating optimization (AO) method, where each subproblem is alternately solved by applying successive convex approximation (SCA) technique. 2) For NOMA, we first handle subproblems with fixed decoding order using SCA technique. Then, we develop a penalty-based algorithm to solve the decoding order design subproblem. Numerical results show that: i) The proposed algorithms are capable of improving the max-min throughput performance compared with other benchmark schemes; and ii) NOMA yields a higher performance gain than OMA when GNs have sufficient energy. [ABSTRACT FROM AUTHOR]

To support ultra-reliable and low-latency communication (URLLC) in vehicular networks, the virtual cells, where multiple access points (APs) cooperatively serve one mobile node, have been proposed to reduce the end-to-end latency in the downlink. The latency can be further reduced by eliminating the need for retransmission and feedback control, i.e., open-loop communications. However, it is difficult to achieve a high reliability of the uplink via virtual cells, because of multiple access interference and collisions from other virtual cells nearby. In this paper, we formulate the proactive radio resource allocation in the open-loop uplink of vehicular networks as a stochastic optimization problem with the objective to maximize the uplink reliability while ensuring the network stability. The optimal resource allocation policies are obtained solving the optimization problem using the Lyapunov optimization technique in a distributed manner. To reduce the computational and to improve the challenges of the Lyapunov optimization, we propose a virtual resource slicing algorithm that maps radio resource units to virtual resource blocks. Simulation results exhibit that both ultra-low latency and ultra high reliability are guaranteed in the open-loop uplink of vehicular networks. Based on the theoretical performance analysis and simulations, the uplink radio access procedure is summarized for the URLLC in vehicular networks. [ABSTRACT FROM AUTHOR]

The cooperative non-orthogonal multiple access (NOMA) networks with one pair primary user and one pair cognitive user share the same spectrum resource via a common relay is considered in this paper. We propose a dynamic power transmission scheme for both uplink and downlink NOMA transmission in cognitive relay networks, which preserves the quality of service for the primary user. The closed-form expressions of overall outage probability and average sum rate for the proposed dynamic power transmission scheme of cognitive relay NOMA networks are derived. Both developed analytical results and Monte Carlo simulations show that the proposed dynamic power control scheme can dramatically enhance performance gain for the proposed networks, compared to other existing NOMA power allocation schemes. [ABSTRACT FROM AUTHOR]

This paper studies the performance of unmanned aerial vehicle (UAV)-enabled NOMA networks with selective incremental relaying and imperfect channel state information (CSI). In particular, an access point transmits a superposed signal based on NOMA principle to an UAV terminal (UT) which can act as a relay to assist the information transmission for a ground terminal (GT). Different from the conventional relaying protocol requiring UT to relay the message all the time no matter how the received signal quality of two terminals are, we propose a novel NOMA-based selective incremental relaying protocol that allows relay to forward messages on the condition of the received signal with satisfied quality at UT and the unsatisfied quality signal at GT. The closed-form solutions of outage probabilities for the two terminals are characterized with the elevation angle-based path loss exponent and small-scale fading. Moreover, the benchmark schemes are provided to exhibit the superiority of the proposed protocol. Finally, simulation and theoretical results validate the correctness of the outage analysis, demonstrate the advantage of the proposed relaying protocol over its counterparts, and show that the stronger impact of channel estimation error on GT than UT in terms of outage probability. [ABSTRACT FROM AUTHOR]

In this paper we investigate downlink performance in a non-orthogonal multiple access (NOMA) based vehicular communication network. In contrast to the previous works wherein the vehicles are simply assumed to be located anywhere in the coverage area, we consider practical cases where vehicles are located on a system of roads. We then adopt a system model based on Poisson Line Cox Point (PLC) processes, where the road system is represented through a Poisson Line (PL) Process. Vehicles ordered according to their distances to their corresponding roadside units (RSUs) are then served by using power domain NOMA. Adopting analytical tools from the stochastic geometry, we then analyse the outage performance of the system. Numerical results corroborate our analysis and demonstrate how the system settings influence the considered NOMA based V2X network. [ABSTRACT FROM AUTHOR]

Combining intelligent reflecting surface (IRS) and non-orthogonal multiple access (NOMA) is an effective solution to enhance communication coverage and energy efficiency. In this paper, we focus on an IRS-assisted NOMA network and propose an energy-efficient algorithm to yield a good tradeoff between the sum-rate maximization and total power consumption minimization. We aim to maximize the system energy efficiency by jointly optimizing the transmit beamforming at the BS and the reflecting beamforming at the IRS. Specifically, the transmit beamforming and the phases of the low-cost passive elements on the IRS are alternatively optimized until the convergence. Simulation results demonstrate that the proposed algorithm in IRS-NOMA can yield superior performance compared with the conventional OMA-IRS and NOMA with a random phase IRS. [ABSTRACT FROM AUTHOR]

In this paper, weighted sum energy efficiency (WSEE) in uplink and downlink of a multi-user non-orthogonal multiple access (NOMA) system is considered. we adopt a more realistic power consumption model where signal processing power is modeled as a linear function of transmit power. Rather than the well-known network-centric global energy efficiency (GEE) metric, which is a pseudo-concave (PC) function, the weighted sum energy efficiency metric is considered, which is not PC in general. To find the optimum user power allocation Dinkelbach-like algorithm is adopted, by which each individual fractional EE function is converted to a parametric function where under some conditions on the weights falls into a class of convex optimization problems and it is solved in the dual domain. The dual variables are updated using a sub-gradient and cutting plane-based algorithm, which here ellipsoid method is used. Since the optimum solution restricts user weights, a low complexity suboptimum algorithm that does not consider any condition on user's weights is proposed. The problem is non-convex in general; hence, epigraph form followed by successive convex approximation (SCA) is used to deal with that problem. Results demonstrate that with the user-oriented metric, one can provide different priorities to users, and by choosing proper weights entail fairness among users. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) aided unmanned aerial vehicle (UAV) is becoming a promising technique for future wireless networks. However, its security remains a great challenge due to the line-of-sight in UAV communications and high transmit power for weak users in NOMA. Thus, in this paper, we propose a power allocation (PA) scheme for NOMA-UAV networks with circular trajectory, to maximize the sum rate of common users while guaranteeing the security for a specific user. To achieve this, we consider three cases based on the distance from the UAV to the secure user. Specifically, the lowest transmit power is assigned to the secure user in each time slot to guarantee its security, with the remaining power allocated to common users to maximize their sum rate. Due to the non-convexity of the problem, we analyze its monotonicity and derive the closed-form solutions for these three cases. To further improve the transmission rate of the secure user, we also derive the upper bound for its decoding threshold, and analyze the linear relationship between the secure decoding threshold and the sum rate of common users. Simulation results are demonstrated to evaluate the effectiveness of the proposed secure PA scheme in NOMA-UAV networks. [ABSTRACT FROM AUTHOR]

The drone has been applied in various areas due to its small size, high mobility and low price. However, illegal uses of drones have posed huge threats to both public safety and personal privacy. There is an urgent demand for technologies that can timely detect and counter the drones. In this paper, we propose an adaptive switching spatial-temporal fusion detection method for remote flying drones in the airspace using electrical-optical cameras, which can enhance the contrast between the target and background as well as suppressing the noises and clutters simultaneously. For each incoming video frame, a dark-attentive interframe difference method and a row-column separate black-hat method are proposed to generate temporal feature maps (TFM) and spatial feature maps (SFM), respectively, in parallel. Inspired by the phenomenon that the features in TFMs and SFMs both go strong at the regions of the intended target while they do not at other regions where noises and clutters locate, we design an adaptive switching spatial-temporal fusion mechanism to fuse the SFMs and TFMs, generating adaptive switching spatial-temporal feature maps (ASSTFM). Finally, an adaptive local threshold mechanism is used in ASSTFMs to segment the targets from backgrounds. In order to validate the effectiveness of our method, we conduct both offline experiments and field tests. The experiment results manifest that our method is superior to the other seven baseline methods and works more stably for different backgrounds and various types of drones. [ABSTRACT FROM AUTHOR]

To enhance the secrecy of wireless transmission, we propose a cooperative user relaying NOMA scheme, in which the near user works in full-duplex mode by transmitting jamming signals and receiving desired signals in the first phase, and the base station sends jamming signals in the second phase. Two power allocation (PA) schemes between the legitimate and jamming signals are designed based on different knowledge of the eavesdropping channel state information (ECSI). The first scheme aims to jam the eavesdropping with highest power while meeting rate requirements without ECSI. In the second scheme, the closed-form expressions of secrecy outage probability (SOP) are first derived using the statistical ECSI. Then, the sum secrecy rate is maximized by optimizing the PA and redundant rate with SOP constraints. Simulation results are provided to show the effectiveness of the proposed schemes. [ABSTRACT FROM AUTHOR]

Precise estimation of transmission input&output shaft torque and wheel speed is significant to the development of torque distribution and coordinated control method for the power split hybrid powertrain system. This paper studies an estimation method of transmission input and output torque as well as drive wheel speed using an unknown input observer in different operating modes for a compound power split hybrid powertrain system. Firstly, the configuration and dynamic characteristic of power split transmission is analyzed. Then, state equations in different operating modes are established, and a Takagi-Sugeno (T-S) fuzzy model is utilized to deal with the nonlinearities of load resistance torque. Furthermore, an unknown input reduced-order observer is designed to estimate the transmission input&output shaft torque and wheel speed. The asymptotical stability of the developed observer is verified based on Lyapunov theory. Finally, the performance of the unknown input observer is assessed by comparing with the Luenberger observer based on Matlab/Simulink simulation platform and test bench. Simulation and experiment results show that, the proposed observer can estimate the transmission input&output shaft torque and wheel speed more effectively in different operating modes. [ABSTRACT FROM AUTHOR]

In this article, we investigate the cellular assisted mobile edge computing (MEC) via non-orthogonal multiple access (NOMA), where a group of edge-computing users (EUs) exploit NOMA to simultaneously offload their computation-workloads to an edge-server (ES), and conventional cellular-user (CU) allows the EUs to reuse its authorized frequency channel for the NOMA-transmission. We firstly characterize the transmit-powers of the CU and EUs and then formulate a joint optimization of the EUs’ offloaded computation-workloads, offloading-duration (i.e., how long for reusing the CU's channel), as well as the ES's computation-resource allocations (for processing different EUs’ offloaded workloads), with the objective of minimizing the overall-latency in completing all EUs’ computation-requirements, subject to the CU‘s and EUs’ limited power and energy capacities as well as the ES's limited computation-resource capacity. Despite the strict non-convexity of the formulated joint optimization problem, we propose an efficient algorithm to compute the optimal offloading solution. With the optimal offloading solution for the scenario of one CU, we further investigate the scenario of multiple CUs and investigate the optimal pairing of the EUs for reusing different CUs’ channels for computation-offloading. Taking into account the coupling effect due to the ES's limited computation-resource, we formulate a joint optimization of the EU-pairing and the ES's capacity allocation of the computation-resource for accommodating different EU-pairs. Despite the difficulty due to the mixed binary and non-linear non-convex programming of the formulated problem, we propose an efficient layered algorithm for solving the problem. Numerical results are provided to validate the accuracy of our proposed algorithms. We also show the performance advantage of our NOMA-assisted offloading in comparison with conventional orthogonal multiple access (OMA) based computation offloading. [ABSTRACT FROM AUTHOR]

This paper proposes a novel probabilistic buffer-aided (BA) relay selection (RS) scheme for cooperative relay networks. Different from most existing BA RS schemes that are determined by the wireless channel condition and the buffer state, the proposed scheme also utilizes additional randomness to decide the link selection outcome. In particular, we first select the strongest available source-to-relay and relay-to-destination links, respectively, and then probabilistically select one from these two links. Some previously proposed BA RS schemes can be viewed as special cases of the proposed scheme, such as the max-link scheme and the scheme with reduced packet delay. Then, the outage probability and average packet delay are analyzed. Both the analytical and simulation results show that different tradeoffs between the outage probability and average packet delay can be easily achieved by adjusting a single corresponding parameter. [ABSTRACT FROM AUTHOR]

The secrecy outage probability (SOP) performance is investigated for a cooperative non-orthogonal multiple access system under eavesdropping attack, where a base station transmits signals to a far user via a full-duplex relay, and to a near user directly at the same time, in the presence of an eavesdropper. All nodes are configured with multiple antennas and antenna selection is adopted by the base station and relay to enhance the security performance. The exact and asymptotic closed-form SOP expressions are derived, which incorporate the impact of imperfect channel state information and apply to general cases considering the quality of service of the far and near users, whether or not the wiretap channel is known, and the location of the eavesdropper. Monte Carlo simulations corroborate the analysis and the superiority of the proposed system over the single-antenna system and the one without antenna selection. It is also revealed that the asymptotic SOP performance of the near user is nearly independent of the power allocation. [ABSTRACT FROM AUTHOR]

Due to cost reduction and device miniaturization, amateur drones are now widely used in numerous civilian and commercial applications. However, the abuse of amateur drones has resulted in emerging threats to personal privacy and public security. To alleviate these threats, we design an acoustic-based surveillance system, which can achieve the capacity of amateur drones detection and localization with 24/7 (24 hours per day and 7 days per week under normal circumstances) availability. In the designed system, a detection fusion algorithm and a TDOA estimation algorithm based on the Bayesian filter are applied to improve the performance of drone detection and localization. Field experiments are carried out, and the results demonstrate that the designed system can detect and locate an amateur drone in real time with high accuracy and 24/7 availability. [ABSTRACT FROM AUTHOR]

In this article, we propose a novel cooperative non-orthogonal multiple access (NOMA) scheme to guarantee the secure transmission of a specific user via two time slots. During the first time slot, the base station (BS) transmits the superimposed signal to the first user and the relay via NOMA. Meanwhile, the signal for the first user is also decoded at the second user from the superimposed signal due to its high transmit power. In the second time slot, the relay forwards the signal to the second user while the BS retransmits the signal for the first user as interference to disrupt the eavesdropping. Due to the fact that the second user has obtained the signal for the first user in the first slot, the interference can be eliminated at the second user. To measure the performance of the proposed cooperative NOMA scheme, the outage probability for the first user and the secrecy outage probability for the second user are analyzed. Simulation results are presented to show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This work focuses on the beamforming design for downlink multiple-input single-output (MISO) nonorthogonal multiple access (NOMA) systems. The beamforming vectors are designed by solving a total transmission power minimization (TPM) problem with quality-of-service (QoS) constraints. In order to solve the proposed nonconvex optimization problem, we provide an efficient method using semidefinite relaxation. Moreover, for the first time, we characterize the optimal beamforming in a closed form with quasi-degradation condition, which is proven to achieve the same performance as dirty-paper coding (DPC). For the special case with two users, we further show that the original nonconvex TPM problem can be equivalently transferred into a convex optimization problem and easily solved via standard optimization tools. In addition, the optimal beamforming is also characterized in a closed form and we show that it achieves the same performance as the DPC. In the simulation, we show that our proposed optimal NOMA beamforming outperforms OMA schemes and can even achieve the same performance as DPC. Our solutions dramatically simplifies the problem of beamforming design in the downlink MISO NOMA systems and improve the system performance. [ABSTRACT FROM AUTHOR]

Crowdsensing has been recognized as a promising data collection paradigm, in which a platform outsources sensing tasks to a large number of users. However, requesting users to report raw data may give rise to many practical concerns, such as a significant overhead of communication and central processing, besides users’ privacy concerns. In many scenarios (e.g, advertising and recommendation), the data collector directly benefits from statistical aggregation of raw data. Thus motivated, we consider the data collection problem based on user's local histograms, which is intimately related to the fundamental trade-off between the platform's accuracy and users’ privacy. Because of users’ social relationship, their data are often correlated, indicating that users’ privacy may be leaked from others’ data. To tackle this challenge, we first utilize Gaussian Markov random fields to model the correlation structure embedded in users’ data. The data collection is modeled as a Stackelberg game where the platform decides its reward policy and users decide their noise levels while taking into account the social coupling among users. For the reward policy design, we first establish the relationship between users’ Nash equilibrium and the payment mechanism, and then optimize the platform's accuracy under a budget constraint. Further, since the noise levels are users’ private information, they may use falsified noise levels to achieve higher payoffs, which in turn impairs the crowdsensing performance. It turns out that with the insight into the correlation structure among users’ data, the information asymmetry can be overcome based on peer prediction. We revisit the payment mechanism to guarantee dominant truthfulness of each user's strategy. Theoretical analysis and numerical results demonstrate the effectiveness of the proposed mechanism. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) technique has been recognized as a promising solution in future wireless connectivity from the sky, and UAV navigation is one of the most significant open research problems, which has attracted wide interest in the research community. However, the current UAV navigation schemes are unable to capture the UAV motion and select the best UAV-ground links in real-time, and these weaknesses overwhelm the UAV navigation performance. To tackle these fundamental limitations, in this paper, we merge the state-of-the-art deep reinforcement learning with the UAV navigation through massive multiple-input-multiple-output (MIMO) technique. To be specific, we carefully design a deep Q-network (DQN) for optimizing the UAV navigation by selecting the optimal policy, and then we propose a learning mechanism for processing the DQN. The DQN is trained so that the agent is capable of making decisions based on the received signal strengths for navigating the UAVs with the aid of the powerful Q-learning. Simulation results are provided to corroborate the superiority of the proposed schemes in terms of the coverage and convergence compared with those of the other schemes. [ABSTRACT FROM AUTHOR]

In this article, a comprehensive strategy of user clustering and power allocation is investigated in downlink hybrid non-orthogonal multiple access (NOMA) networks. More particularly, users in the same cluster can receive signals simultaneously by using NOMA techniques, while time-division multiple access (TDMA) schemes are utilized among different clusters. By employing the weight factor, a weighted sum rate maximization problem is formulated and decoupled into user clustering and power allocation problems, where two different schemes for time slot allocation are proposed. The formulated user clustering problems with user-based and cluster-based time slot allocation schemes are respectively considered as coalitional games in characteristic and partition formations, and solved by two different algorithms, where both low-complexity and global optimal methods are proposed. The properties, including complexity, convergence, stability and optimality, are analyzed. To further improve the system performance, the formulated power allocation problem is solved by a successive convex approximation (SCA) based iterative algorithm. Simulation results reveal that: i) the proposed hybrid NOMA system is capable of achieving promising gains over centralized NOMA-based and conventional TDMA-based frameworks; and ii) the developed algorithms can significantly improve the weighted sum rate compared with the random user structure and the fixed power allocation. [ABSTRACT FROM AUTHOR]

In this paper, resource allocation for a multi-carrier uplink non-orthogonal multiple access (NOMA) system is studied. Unlike the existing works on multi-carrier uplink NOMA, in which each user is assumed to access only one subcarrier, we consider a more general scenario where the number of subcarriers allocated to a single user is not constrained. We first aim to maximize the system's sum rate, which requires selecting the appropriate subcarriers for each user and distribute the transmission power. The formulated non-convex problem is transformed into a convex one, and further, an optimal and low-complexity iterative water-filling solution is proposed. Nonetheless, it is shown that maximum transmit power is employed by each user to maximize the sum rate. Motivated by the fact that the users are power constrained, the energy efficiency (EE) maximization problem is also studied. Based on fractional programming, the EE maximization problem is transformed into a series of sum rate maximization subproblems, and the proposed iterative water-filling solution is applied to each subproblem. The proposed schemes are compared with other NOMA-based and orthogonal multiple access based algorithms, and its superiority is fully validated. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is a prospective technology for radio resource constrained future mobile networks. However, NOMA users far from a base station (BS) tend to be more susceptible to eavesdropping because they are allocated more transmit power. In this paper, we aim to jointly optimize the precoding vectors at the BS to ensure the legitimate security in a downlink multiple-input single-output (MISO) NOMA network. When the eavesdropping channel state information (CSI) is available at the BS, we can maximize the sum secrecy rate by joint precoding optimization. Owing to its non-convexity, the problem is converted into a convex one, which is solved by a second-order-cone-programming-based iterative algorithm. When the CSI of the eavesdropping channel is not available, we first consider the case that the secure user is not the farthest from the BS, and the transmit power of the farther users is maximized via joint precoding optimization to guarantee its security. Then, we consider the case when the farthest user from the BS requires secure transmission, and the modified successive interference cancellation order and joint precoding optimization can be adopted to ensure its security. A similar method can be exploited to solve the two non-convex problems when the CSI is unknown. Simulation results demonstrate that the proposed schemes can improve the security performance for MISO NOMA systems effectively, with and without eavesdropping CSI. [ABSTRACT FROM AUTHOR]

In this paper, secure primary transmission is proposed by using a multi-antenna secondary full-duplex non-orthogonal multiple access (NOMA) relay in cognitive radio (CR) networks. First, the primary signal is transmitted from the primary transmitter to the relay. Artificial noise is generated by using part of the antennas at the relay to disrupt eavesdropping, without affecting the primary transmission. Then, superimposed signals are transmitted from the relay to the primary receiver and secondary receivers via NOMA. The primary security is guaranteed by the modified decoding order and beamforming optimization, which is converted to convex and solved by an iterative algorithm. Simulation results are presented to show the effectiveness of the proposed scheme in guaranteeing the primary security in CR networks. [ABSTRACT FROM AUTHOR]

Based on a hierarchical cloud-fog computing-enabled paradigm, fog radio access networks (F-RANs) can provide abundant resource to support the future mobile artificial intelligent services. However, due to the differences of computation and communication capabilities at the cloud computing center, the fog computing based access points (F-APs), and the user devices, it is challenging to propose efficient computation offloading strategies to fully explore the potential of F-RANs. In this paper, we study the design of computation offloading in F-RANs to minimize the total cost with respect to the energy consumption and the offloading latency. In particular, a joint optimization problem is formulated to optimize the offloading decision, the computation and the radio resources allocation. To solve this non-linear and non-convex problem, an iterative algorithm is designed, which can be proved to converge a stationary optimal solution with polynomial computational complexity. Finally, the simulation results are provided to show the performance gains of our proposed joint optimization algorithm. [ABSTRACT FROM AUTHOR]

This paper studies positioning fundamentals in low-power wide area (LPWA) Internet of Things (IoT), where those devices with locations known operate as anchors. A tractable model is developed to analyze localizability of target devices. A random scenario is investigated, where anchors are randomly distributed. The model first studies the positioning of a target which can be anywhere. Then, from the point of view of system level, target randomness is further considered so that the study can be conducted over the whole network area. The model has no limitations on area shape but can consider any arbitrary polygonal one. It incorporates the ability for participating anchors to coordinate transmissions, and the interference effect on positioning is theoretically investigated. The model is then extensively validated in comparison with simulations, and the effects of a set of parameter settings are investigated. Compared to the existing positioning performance studies targeting deterministic scenarios, the proposed model considers location randomness through distance distributions using a powerful probabilistic distance-based tool from geometric probability. The model considers both interference and system-related parameter settings, investigating anchor transmission coordination and traffic load, which reveals how participating anchors in general impact positioning performance in LPWA IoT. [ABSTRACT FROM AUTHOR]

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

This correspondence considers non-orthogonal multiple access (NOMA) assisted mobile edge computing (MEC), where the power and time allocation is jointly optimized to reduce the energy consumption of computation offloading. Closed-form expressions for the optimal power and time allocation solutions are obtained and used to establish the conditions for determining whether the conventional orthogonal multiple access (OMA), pure NOMA or hybrid NOMA should be used for MEC offloading. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of imperfect channel state information on the performance of the cooperative non-orthogonal multiple access (NOMA) transmission scheme, in which the cell-center user acts as a decode-and-forward relay to assist the information transmission. The cell-center user adopts a simultaneous wireless information and power transfer (SWIPT) technique to harvest energy for information forwarding. Based on two channel error models, a maximization problem is formulated to jointly design the robust beamforming and the power splitting ratio while satisfying the minimum data rate for the far user and the successfully decoding requirement for the information of the far user at the near user. For the worst case design under the deterministic error model, the successive convex approximation and the semidefinite relaxation technique are utilized to approximate the non-convex problem to an iterative convex problem. For the outage-constrained design under the stochastic error model, Bernstein-type inequality-based and large deviation inequality-based approaches are used to safely approximate the probabilistic constraints of the inner-level problem to the deterministic constraints, and a golden section search algorithm is employed to find out the optimal single variable of the outer-level problem. Furthermore, the rank proof is provided to prove that the relaxation is tight. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) has been considered as a key technology in the fifth-generation mobile communication networks due to its superior spectrum efficiency. Since the heterogeneous network has been emerged to satisfy users’ explosive data rate requirements and large connectivity of mobile Internet, implementing NOMA policy in heterogeneous networks (HetNets) has become an inevitable trend to enhance the 5G system throughput and spectrum efficiency. In this paper, we aim to maximize the entire system energy efficiency, including the macrocell and small cells, in a NOMA HetNet via subchannel allocation and power allocation. By considering the co-channel interference and cross-tier interference, the energy efficient resource allocation problem is formulated as a mixed integer nonconvex optimization problem. It is challenging to obtain the optimal solution; therefore, a suboptimal algorithm is proposed to alternatively optimize the macrocell and the small cells resource allocation. Specifically, convex relaxation and dual-decomposition techniques are exploited to optimize the subchannel allocation and power allocation. Moreover, optimal closed-form power allocation expressions are derived for small cell and macrocell user equipments by the Lagrangian approach. Simulations results show that the proposed algorithms can converge within ten iterations and can also attain higher system energy efficiency than the reference schemes. [ABSTRACT FROM AUTHOR]