Cooperative control of mobile autonomous agents relies on interagent communication, while most existing studies are concerned with local information exchange between neighbors. In addition to local information exchange, global information exchange, e.g., via communication routing, is also an important approach, that might have the advantage of accelerating the convergence of cooperative control. However, there are few works on the joint design and analysis of cooperative control and communication routing for mobile autonomous agents. In this paper, we propose a technique which realizes the cooperative control of mobile autonomous agents by incorporating communication routing. To be specific, we first design a control law combining local and global information exchange. Then, considering the delay caused by routing, we analyze the convergence performance of above control law by using a frequency-domain method for time-delay systems, which shows that the convergence rate of the control law we designed is faster than that only with distributed control or routing. Finally, simulations are provided to validate the theoretical results.

As an important area of machine learning, re-inforcement learning has specific applicability in multi-agent systems (including UAV swarms). In this article, we use re-inforcement learning algorithm (i.e., the QMIX algorithm) to resolve the problem of UAV swarm confrontation, considering the condition of asymmetric confrontation under which the adversary's combat power is much stronger than our own. First, after constructing the system model, we develop the QMIX algorithm by designing the state space, action space, and reward function. Second, we propose a confrontation strategy that integrates decisions made by the QMIX algorithm and the artificial potential field method for UAV swarm confrontation. Finally, the experimental results show that our proposed confrontation strategy has a 72% higher win rate compared to the QMIX algorithm under asymmetric confrontation conditions.

Within a number of compressed sensing (CS) problems, support recovery of sparse signals is the primary task that needs to be performed. In this paper, we propose a Q-learning based algorithm of support recovery (QSR) for sparse signals, which treats the atomic selection in traditional greedy CS algorithms as Markov Decision Process (MDP) in reinforcement learning (RL). We adopt parallel computing to address "the curse of dimensionality" in Q-learning, dividing the overall RL problem into multiple subproblems. The computational complexity can thus significantly decrease, which grows linearly with the increase of signal length. Experiments show that the proposed algorithm performs closely to other CS algorithms when dealing with high sparsity level signals and it has better performance when dealing with low sparsity level signals.

This article addresses the problem of identifying disconnected agents in multiagent systems via external estimators. Specifically, we employ external estimators with an appropriately designed decision rule to identify the disconnectedness (i.e., the status of being disconnected) between two arbitrarily chosen agents in formation-control multiagent systems. The design of the decision rule is inspired by the unit-root testing problem of autoregressive time series. To make the best possible decision, a best-effort procedure is also proposed. Then, by introducing the concept of connected components (or just components) in graph theory, and using the methods of consensus analysis and time-series analysis, we develop an analytical framework to show the theoretical performance of the designed decision rule. A particularly important result shown by our analysis is that the miss probability of the decision rule can converge to 0 as the number of data samples increases. Finally, simulation results validate the performance of the decision rule and the best-effort procedure, showing that they can perform well even in small samples.

How to ensure the reliability of mixed communication between vehicle to vehicle and vehicle to road, and how to ensure seamless handover during communication in the Internet of Vehicles, is a research hotspot in 5G cellular Internet of Vehicles. This paper proposes a 5G cellular Internet of Vehicles communication handover strategy model for V2V (Vehicle to Vehicle) and V2I (Vehicle to Infrastructure) scenarios, which combines fuzzy logic and user satisfaction for obtaining quality of service, and can make intelligent decisions on handover trigger timing and handover targets based on various parameters in the wireless network, so that the vehicle can handover to the best service target in the process of vehicle terminal handover. The experimental study shows that the proposed method outperforms other common methods in terms of handover metrics such as handover trigger rate, handover times and quality of service compared to existing studies.

Asymptotic analysis plays an important role in the performance evaluation and technology design of large multiple-input multiple-output (MIMO) systems. This paper investigates an asymptotic property of large MIMO systems, called distance hardening. It involves distance metrics defined in terms of many factors, such as the channel matrix and the difference matrix of two arbitrary transmitted codewords. The asymptotic property is revealed by the use of the Chernoff bounding method and expressed in an analogous way to the well-known channel hardening. More specifically, we first derive Chernoff bounds on the tail probabilities of distance metrics, in which we are interested. Then, we formulate the asymptotic property based on a generalized definition of the hardening phenomena by referring to a formal definition of the channel hardening. The distance hardening is shown to have implications for space-time code design, MIMO detection, and millimeter wave MIMO systems. Numerical simulations are conducted to verify our theoretical development.

The wound-field doubly salient generator (WFDSG) is receiving consideration for the field of industrial and aerospace/aviation, since it has the advantages of high robustness with simple structure and adjustable output voltage. In this paper, upon the analysis of generator structures, the features of three rectifiers that are suitable for WFDSG are analyzed in detail. The comparative research of WFDSG with hybrid half-bridge rectifier (HHBR), full-bridge rectifier (FBR), and half-bridge rectifier is presented by the finite-element method (FEM). Then, the load and no-load characteristics of WFDSG under the three rectifiers mentioned above are researched comparatively. The commutation overlap angles and total commutation output voltage losses of three rectifiers are deduced. The experiments of a 12/8-pole single armature-winding WFDSG (SAW-WFDSG) with an FBR and a 12/8-pole dual-armature-winding WFDSG (DAW-WFDSG) with HHBR prototypes have been performed. The FEM and experiment results shows that the SAW-WFDSG with FBR and the DAW-WFDSG with HHBR both have a good application prospect.

This paper presents the asymptotic analysis of random lattices in high dimensions to clarify the distance properties of the considered lattices. These properties not only indicate the asymptotic value for the distance between any pair of lattice points (with and without noise corruption) in high-dimension random lattices, but also describe the convergence behavior of how the asymptotic value approaches the exact distance. Besides, we provide a discussion on further extensions and potential applications of the derived results regarding the lattice theory and multiple-input multiple-output (MIMO) technology.

The recent concept of beamspace multiple-input-multiple-output (MIMO) enables the millimeter-wave (mmWave) MIMO system to reduce the radio-frequency chains by utilising beam selection and yet achieve near-optimal sum-rate performance. In this work, we study the lens antenna array as the transmit antenna at the base station for mmWave multiuser MIMO (MU-MIMO) system. Due to the direction-based energy focusing property of the array, the beam selection is able to reduce to antenna selection without significant performance degradation as that using traditional antenna selection. For this mmWave MU-MIMO system, direction-based antenna selection method is proposed, where the inter-user interference, resulting from the case that the same antenna is selected for different users with high probability, is considered and solved by a re-selection based on minimization of sum-rate loss. Simulation results show that spectral and energy effectiveness of the proposed antenna selection method for the mmWave MU-MIMO using lens antenna array.

This paper presents an approach to identifying the full-diversity solution of MIMO detection, which can verify whether a solution obtained by MIMO detection is full-diversity. The approach is called fine-grained because it is able to individually identify the full-diversity performance for each solution of MIMO detection. To verify the theoretical properties of the developed approach, the conditional probability of missing the correct solution and false alarm, as well as the conditional error probability are analyzed. Besides, a numerical example and practical applications are provided.

This paper presents a novel approach of direction-of-arrival (DoA) estimation for the electronically steerable parasitic array radiator (ESPAR) antennas, using only a single radio-frequency (RF) chain. Starting from the problem formulation in the Bayesian compressive sensing (BCS) framework, the CS measurements are projected onto the beamspace of the unique configuration of the ESPAR antenna. In this work, measurements collected at multiple snapshots are considered. First, we propose to solve the sparse recovery problem by the multi-task BCS [1]. Then, the DoAs are estimated by employing a noise filter on the recovered sparse signal. In this method, the number of sources need not be known a priori, and computation complexity is reduced by avoiding computing the correlation matrix of measurements unlike the traditional DoA estimation techniques. Simulations show that the proposed method can recover closely spaced sources using a small number of noisy snapshots, and it performs better with more sources than other state-of-the-art algorithms.

The femtocell networks provide a promising solution to increase system capacity and improve indoor coverage. However, inter-cell interference becomes enormous in femtocells due to dense deployment and cell-size reduction. This paper proposes the interference mitigation method for the downlink of femtocells, using the electronically steerable parasitic array radiator (ESPAR) antenna at both femto-base stations (FBSs) and user terminals (UTs), which relies on a single radio-frequency (RF) chain; thus meets the demanding low-power, low-cost and small-size requirements of modern wireless terminals - FBSs and UTs. We first exploit the ESPAR antenna as a switched-beam array capable of predefining directional beampatterns accessing to different angular sectors. Then each FBS/UT dynamically selects an appropriate beampattern according to its measurement of desired direction. We also consider an optimal way to employ the ESPAR antenna by adaptively designing the beampattern steering to desired direction while placing nulls to interferers. The results show significant gains obtained by using ESPPAR antennas at both FBSs and UTs.

The adaptive beamforming algorithm-minimum variance distortionless response (MVDR) has been studied based on the electronically steerable parasitic array radiator (ESPAR) antenna. The ESPAR antenna uses a single radio-frequency (RF) front end, and its beamforming is achieved by adjusting reactance loads of parasitic elements coupled to the central active element. In the proposed beamforming method, the MVDR beamformer optimizes weights applied to outputs of beams. The optimization problem is formulated as a second-order-cone programming (SOCP) problem including a Euclidean distance metric to approximate the optimal equivalent weight vector to a feasible solution. Then the ESPAR beampattern design strategy iterates between the SOCP problem and a simple projection of reactance loads. The simulations show that the proposed MVDR beamforming method based on an ESPAR antenna gives a beam steering at the desired direction and placing nulls at the interfering directions, and it converges fast. However, when the desired source is close to the interferer, the output signal-to-interference-plus-noise ratio (SINR) degrades and where we use the interference-plus-noise sample covariance matrix to improve the beamforming performance.

Recently, a technique entitled “Blind Interference Alignment (BIA)” was proposed, which allows interference alignment to be achieved without the knowledge of channel state information at the transmitter. The key to realizing the BIA scheme is the use of a receive antenna capable of switching among multiple beampatterns. The ESPAR antenna, which uses only a single RF front-end, is capable of forming different directional beampatterns by the use of circular permutations of the reactive loads of the passive elements. We introduce the ESPAR antenna as a potential solution for the practical implementation of the BIA for broadcast channel as well as cellular. The BIA scheme is accomplished by the transmission strategy jointly coordinating with the ESPAR beampattern switching symbol-wise. The ESPAR beampattern switching provides the necessary channel diversity for receiving users. Simulation results demonstrate that the ESPAR beam steering can be designed to improve the performance of the BIA scheme by enhancing the receive signal-to-noise ratio (SNR). Furthermore, we study the proposed BIA scheme for a simple 1-dimensional cellular setting to illustrate that the ESPAR beamforming can improve the performance of the cell-edge users through further suppressing the remaining inter-cell interference.

Recently, a technique entitled “Blind Interference Alignment (BIA)” was proposed, which allows interference to be aligned within a reduced subspace without knowledge of the channel state information at the transmitter. The key to realizing the BIA scheme is the use of a receive antenna that is capable of switching among multiple channel-states (with channel diversity) in a pre-determined way. In this paper, we exploit the ESPAR antenna, which uses only a single radio frequency chain as the receiver to provide the necessary beampattern switching for the BIA technique. Moreover, in the proposed ESPAR based BIA scheme, beam-steering of each ESPAR receiver is designed according to its position relative to the transmitter to increase the received SNR. Furthermore, we study the proposed BIA scheme by applying the ESPAR antennas to a 2-D cellular setting in order to illustrate the ESPAR beam pattern design and associated improvements in the performance of the BIA scheme. In order to keep the number of coordinating BSs at a reasonable level, we study the case where only three adjacent BSs operate the BIA scheme coordinatively. This is found to be reasonable since the other inter-cell interference is not significant due to the ESPAR beam-steering and the longer propagation distance. The simulation shows that our scheme provides comparable sum rate to that of BIA scheme operated in all cells.

This study concerns the approximate distribution of the random variable log 2 ( A + χ 2 ) and its applications in the performance analysis of communication systems where A is 0 or 1 and χ 2 a chi‐square distributed random variable. The authors prove that log 2 ( A + χ 2 ) is approximately Gaussian distributed and derive the expressions of the mean and variance of the approximate distribution. The approximate Gaussian distribution provides a new way to simplify the derivation of performance metrics and obtain analytical results. Then the authors utilise the approximate results in two applications, which are the approximation of the Gaussian Q ‐function and capacity analysis, respectively. For one thing, the approximate distribution can be explored to deduce a new approximate equivalent expression of the Q ‐function on the basis of which an accurate approximation of the Gaussian Q ‐function can be developed. For another, the approximate Gaussian distribution provides an intuitive approach to analyse the channel capacity of Rayleigh‐fading multiple antenna systems. The approximate statistical distributions of the channel capacities of orthogonal space‐time block codes, single‐input multiple‐output, multiple‐input single‐output, transmit antenna selection with maximal‐ratio combining and multiple‐input multiple‐output systems are presented. The applicability of the approximate distribution can be demonstrated through simulation results in both applications.

This letter presents the complexity study of multiple-input multiple-output (MIMO) detection in a multiple-user scenario. For variable-complexity MIMO detection in multiple-user systems, the complexity outage probability, defined as the probability of event that the complexity exceeds some complexity constraint, is proved to have a Chernoff-type upper bound that decays exponentially with an increasing number of users. The closed-form expression of such a Chernoff-type upper bound is also derived.

In this paper, we propose admission control and power optimization algorithms for Device-to-Device (D2D) communication which share uplink resources with cellular system in underlay mode. In the presence of quality of service (QoS) protection (both for D2D and cellular users) and transmit power limit, we propose a set-based admission control (SAC) algorithm in which some novel strategies of sets adjustment are presented to handle the violations of constraints. By using SAC, we get a set which contains admitted D2D links (DLs) as many as possible, and other DLs are rejected, but the D2D system capacity is not optimal. Then, we propose a distributed power optimization (DPO) algorithm to maximize the D2D system capacity after implementation of SAC. In DPO, QoS protection is also provided, each DL uses gradient descent method to update its transmit power, and DLs only need to exchange “price” messages which indicate the effect of interference. Through the numerical results, we demonstrate the feasibility and satisfying performance of proposed algorithms compared to traditional algorithms.

In this paper, the early-termination fixed-complexity sphere detector (ET-FSD) that is a channel-adaptive version of FSD, is developed to exploit scale effects for the multiple-antenna system which has to detect signals of multiple users under the constraint of sum complexity (e.g., the base-station systems always encounter the run-time limit of signal detection of all the users). In order to apply the concept of scale effects in microeconomics to the study of ET-FSD, the corresponding mathematic model primarily based on the large deviation principle is established. The key evidence that tells the existence of scale effects in ET-FSD is presented instead of the complete proof due to the space limitation. We also argue that within multiple-user systems the scale effects can be utilized to realize ET-FSD that has both the optimal performance in the point view of diversity order and the polynomial time unit complexity in the worst-case sense (one can think of unit complexity as the complexity per user in multiple-user scenario). Finally, we provide the numerical results to support the theoretical analysis.

In this paper, a novel scheme of multiple-input multiple-output (MIMO) detector is proposed for base-station (BS) system that has to detect signals of multiple users, which is capable of exploiting the scale effects and thus named as the scale effects oriented MIMO detector. The scale effects is the feature that, the unit complexity of MIMO detector decreases as the number of users increases under certain condition while maintaining the full diversity. Through theoretic analysis of error probability, diversity order and complexity, as well as works of computer simulation, we demonstrate that the proposed MIMO detector has the scale effects.

In this paper a framework of analyzing the secrecy capacity of Raleigh fading multi-antenna system in presence of multiple eavesdroppers is presented. The multi-antenna system we concern adopts the transmit antenna selection with maximal-ratio combining (TAS/MRC) diversity scheme. We propose to make use of the closed-form approximations to analyze the secrecy capacity. The simulations validate the analytical results derived by the proposed framework.

In this paper, the theoretical insight into Gaussian approximation of channel capacity for several classes of Rayleighfading multiple-antenna systems is presented. In particular, a theorem, which has not been developed by the former studies of Gaussian approximation, is introduced to these systems. Then guided by this theorem, a new approach of determining the approximate mean and variance for Gaussian approximation is proposed, which is simpler and more intuitive than the existed approach. The simulation results show the availability of such new approach.