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The integration of antennas into disposable paper drones using inkjet printing technology is presented. These drones or unmanned aerial vehicles (UAVs) are developed using origami folding structures. Two vertical monopole antennas based on the same design concept are proposed and their performance assessed for two different conditions. The conditions relate to the placement of the other electronic components and circuits on the origami drones as reported in the literature. The first is when the electromechanical components and corresponding metallic layers are located in the wings. In this case, the effect of the possible location of the antenna as well as the deformation of the wings on S11 is discussed. The second is a more general case scenario which includes when the components and motors are placed at the tail and lower part of the body of the drone. The antenna elements are directly printed onto a photo paper substrate using silver nanoparticle conductive ink. Subsequently, the substrate is folded to create a paper drone. Low-cost desktop inkjet printing equipment is used to deposit the metallic tracks of the antenna. The designs target the current frequency bands employed in the control and wireless communication of commercial drones (2.4 GHz and 5 GHz bands). The purpose of this work is to investigate potential antenna scenarios for disposable drones which may one day be fully fabricated using inkjet printing technology. All antenna designs and studies have been simulated using CST Microwave Studio and compared well with experimental results. [ABSTRACT FROM AUTHOR]

In this paper, we study the average throughput performance of energy beamforming in a multi-antenna wireless-powered communication network (WPCN). The considered network consists of one hybrid access point (AP) with multiple antennas and a single-antenna user. The user has no constant power supply and, thus, needs to harvest energy from the signals broadcast by the AP in the downlink (DL) before sending its data back to the AP with the harvested energy in the uplink (UL). We derive closed-form expressions of the average throughput and their asymptotic expressions at a high SNR for both delay-limited and delay-tolerant transmission modes. The optimal DL energy harvesting time, which maximizes the system throughput, is then obtained for high SNR. All analytical expressions are validated by numerical simulations. The impact of various parameters, such as the AP transmit power, the energy harvesting time, and the number of antennas, on the system throughput is also investigated. [ABSTRACT FROM AUTHOR]

The use of unmanned aircraft systems (UAS) is expanding rapidly. For safe and reliable integration of UAS into the National Airspace System (NAS), control and nonpayload communication (CNPC) system requirements are being developed. The air-to-ground (AG) channel characteristics essentially determine CNPC link performance. The National Aeronautics and Space Administration (NASA) Glenn Research Center has sponsored a comprehensive AG channel measurement campaign in 2013 in both the L- and C-bands recently allocated for UAS. These measurements covered nearly all typical ground site (GS) local environments, including over water, hilly, mountainous, suburb, and near urban. As a continuation of results reported for the over-water scenarios, a description of the measurement campaign, measured results, and complete AG channel models for hilly and mountainous terrains are provided in this paper. The path loss is modeled by a modified log-distance path loss model with a correction for flight direction; path loss results are close to those of free space. A strong ground reflection was observed only for some small portions of some of the flight paths. The small-scale fading is well modeled by the Ricean distribution with a $K$-factor of 29.4 dB in the C-band and 12.8 dB in the L-band. The interband signals are uncorrelated. The spatial correlation for the two intraband channels with an aircraft antenna separation of 1.8 m is greater than 0.85. The C-band root-mean-square delay spread (RMS-DS) is 10 ns most of the time, with a maximum of 1 \mu\text{s} in hilly terrain and 180 ns in mountainous terrain. Tapped delay line (TDL) models accounting for the line of sight (LOS) and up to seven intermittent multipath components (MPCs) were developed, including the MPCs' probability of occurrence, relative power, phase, duration, and excess delay. [ABSTRACT FROM PUBLISHER]

This paper analyzes the performance of the recently proposed quadrature spatial modulation (QSM) multiple-input–multiple-output (MIMO) system over Nakagami- $m$ fading channel. In the analysis, the general distribution of the Nakagami- m$ channel phase is considered. In the literature, performance analysis of spatial modulation (SM) over Nakagami- m$ channel with uniform phase is conducted. However, apart from the very special case of , where Nakagami- $m$ fading corresponds to Rayleigh fading, the phase of the Nakagami- $m$ distribution is not uniformly distributed. It is shown in this paper that the phase of the channel has major impact on the performance of spatial multiplexing MIMO systems such as SM and QSM systems. A general upper bound expression for the average bit error ratio (ABER) performance of QSM is derived, and the impact of different channel parameters is studied. Monte Carlo simulation results are provided to corroborate the exactness of the derived analysis. [ABSTRACT FROM PUBLISHER]

Multiple signal classification (MUSIC) has been widely applied in multiple-input multiple-output (MIMO) receivers for direction-of-arrival (DOA) estimation. To reduce the cost of radio frequency (RF) chains at millimeter-wave bands, hybrid analog-digital structure has been adopted in massive MIMO transceivers. In this situation, received signals at the antennas are unavailable to the digital receiver, and as a consequence, the spatial covariance matrix (SCM), which is essential in MUSIC algorithm, cannot be obtained using traditional sample average approach. Based on our previous work, we propose a novel algorithm for SCM reconstruction in hybrid massive MIMO systems with multiple RF chains in this paper. By switching the analog beamformers to a group of predetermined DOAs, SCM can be reconstructed through the solutions of a set of linear equations. Furthermore, a low-complexity algorithm, as well as a careful selection of the predetermined DOAs, will be also presented in this paper. Simulation results show that the proposed algorithms can reconstruct the SCM accurately so that MUSIC algorithm can be well used in hybrid massive MIMO systems with multiple RF chains. [ABSTRACT FROM AUTHOR]

Millimeter-wave vehicle-to-vehicle communication systems with multiple-input multiple-output antenna array have drawn significant attention because it is expected to satisfy the growing bandwidth requirements for the cooperative intelligent transportation systems. However, maintaining high-quality communication links between communicating vehicles without high overhead is a challenging problem due to the high mobility of vehicles. In this paper, we propose a beam management algorithm with spatially distributed antenna subarrays instead of a single co-located antenna array. Unlike existing methods, we use distributed antenna subarrays to exploit the geometric relationship of the beam directions and the relative distance between communicating vehicles. We reduce the beam alignment errors by minimizing the sum of squared errors between the estimated beam direction after the beam training process and the refined beam direction derived from the measured position and velocity data. Additionally, a position data request protocol is devised to reduce the beam refining errors. Numerical results demonstrate that the proposed beam management algorithm successfully reduces the beam alignment errors and it is robust to position and velocity measurement errors. [ABSTRACT FROM AUTHOR]

This study is motivated by the fact that localization in millimeter wave(mmWave) Vehicle-to-Vehicle communication becomes a more critical problem because both the terminals of the communication link are in motion. The positional awareness merely based on GPS or local sensors has an error margin of around 10 meters, which can worsen in uncertain real-time conditions such as road topology and highway traffic. The paper analyses the relation between vehicle dynamics, beamforming, and beam alignment for highly directive antennas. When the subsystem models presented in this paper are taken into consideration, the joint vehicle dynamics-beamforming approach will optimize the link connectivity and SNR. The vehicle dynamics model is designed to be more realistic considering the non-linear acceleration based on the throttle-brake jerks due to induced noises. The Unscented Kalman Filter based prediction subsystem predicts the alignment values even during non-linear acceleration and jerks. The feasibility of antenna design for the beamforming strategies is supported by the requirements of phase shifters and the number of elements. [ABSTRACT FROM AUTHOR]

Horizontal antenna sectorization has been used within all generations of cellular radio networks to improve both the coverage and capacity of such networks. This paper evaluates the potential coverage and capacity gains of sectorization through extensive simulation and real-world trials of deployments of higher order horizontal sectorization (three, six, nine, 12, and 15 sectors) when applied to a Third-Generation (3G) Evolved High-Speed Packet Access (\mbox3\mboxG/\mboxHSPA+) network. Simulation results are presented for idealized homogeneous networks based upon a standardized 3G Partnership Project HSPA/Long-Term Evolution (LTE) network model to find the theoretical downlink capacity gains and the optimum horizontal antenna beamwidth to maximize capacity without significantly reducing coverage and other cellular-network key performance indicators (KPIs). Further simulations have also been performed to assess the potential gain seen within Telefonica UK's central London \mbox3\mboxG/\mboxHSPA+ network, and these results have also been verified using live network field results from the deployment of six-sector sites into Telefonica UK's network. Finally, trial results from the deployment of what is believed to be the industry's first 15-sector 3G site are presented, showing further gains are possible well beyond the six sectors per site. [ABSTRACT FROM AUTHOR]

Channel predictions are important to achieve high spectral efficiency for high-mobility vehicles. Channel extrapolation, used by many prediction methods, suffers from a limited prediction horizon in difficult radio environments. The predictor antenna (PA) concept provides the prediction horizons required for efficient transmission to fast-moving vehicles by measuring the channel ahead of time with an extra antenna placed on the vehicle. This paper presents a general framework that addresses the practical signal processing challenges of the PA concept. It is adaptable to a vast variety of vehicular deployment, mobility, and communication scenarios. A new theoretical prediction normalized mean-squared error (NMSE) expression is derived based on the presented framework. The framework is demonstrated by applying it to extensive channel measurements and comparing the PA predictions to Kalman-based channel predictions and outdated channel estimates. By studying the impact of vehicular velocity and radio environment on the prediction performance, it is shown that PA prediction is weaker at low velocities, where Kalman prediction methods are sufficient, but is uncontested at high velocities in environments without a dominating path. At high velocities in dominating path environments, the Kalman predictor provides usable predictions, but it is still outperformed by the PA predictions. [ABSTRACT FROM AUTHOR]

As the number of antennas increases, the massive multiple-input multiple-output (MIMO) system can precisely point to user equipments (UEs) with narrow beams. Accurate and timely channel state information (CSI) feedback is crucial to keep UEs in service. Mobile UEs, however, may suffer from the narrow beam nature of the massive MIMO system since UEs can move out of the beam coverage. When intelligent reflecting surface (IRS) is applied to the massive MIMO system, the adjustment of the IRS cannot be frequent as the IRS is controlled remotely by the base station (BS). Limiting the number of CSI feedback and the number of both BS and IRS adjustments significantly reduces the overhead of transmission and computation to the system. In this paper, we consider the UEs’ mobility adaptation problem in an IRS assisted multiuser massive MIMO downlink system with infrequent CSI feedback. We propose a beam control method that adapts to UEs’ mobility. The problem is constructed as a sum rate problem where both the BS and IRS are taken into account to jointly optimize the beamforming matrices. Simulation results show that our proposed algorithm can converge quickly and provide satisfactory performance for mobile UEs. At the same time, our proposed algorithm reduces the frequency of updating the beamforming matrices effectively both at the BS and at the IRS. [ABSTRACT FROM AUTHOR]

This paper proposes a framework to construct 3-D complementary codes (3DCCs), which enable chip-level space–time coding to integrate multiantenna and multiple-access techniques in a unified platform. The 3DCCs are generated based on an extension method with the help of traditional complementary codes and well-designed matrices. The relationship between the correlation properties and flock size of the constructed 3DCCs is analyzed, and the proposed framework provides a generic way to construct different families of 3DCCs with a controllable tradeoff between their correlation properties and flock sizes. As examples, three families of 3DCCs with different characteristic features are constructed using the framework, and their correlation properties are simulated to validate their properties. The general architecture of the 3DCC-based multiple-input multiple-output (MIMO) system is also proposed in this paper. The simulated bit-error-rate (BER) performance of the corresponding system over both flat and multipath fading channels show that the constructed 3DCCs can eliminate both multiuser and multipath interferences in multiuser MIMO communications. The property to provide both transmit diversity and multiplexing with its uniquely flexible tradeoff between the two also makes it particularly well suited for futuristic wireless communications to fit to varying channel conditions and application requirements. [ABSTRACT FROM PUBLISHER]

In this paper, we study the multiuser detection in a millimeter-wave (mm-wave) wireless communication system using hybrid beamformers, where uplink transmissions are considered under limited scattering. For a base station, with the condition that the number of radio-frequency (RF) chains is relatively smaller than that of users, we consider opportunistic beamforming with analog beams for multiple-signal detection and derive a closed form expression for system sum rate. By applying the minimum mean square error (MMSE)-filter with the proposed opportunistic hybrid beamforming algorithm, the system performance can be further improved. Through simulation results, it is shown that the proposed MMSE-based multiuser detection approaches are attractive for hybrid mm-wave systems to support a large number of users with a small number of RF chains. [ABSTRACT FROM AUTHOR]

In this paper, we design receivers for filter bank multicarrier-based (FBMC-based) massive MIMO considering practical aspects such as channel estimation and equalization. In particular, we propose a spectrally efficient pilot structure and a channel estimation technique in the uplink to jointly estimate all the users’ channel impulse responses. We mathematically analyze our proposed channel estimator and find the statistics of the channel estimation errors. These statistics are incorporated into our proposed equalizers to deal with the imperfect channel state information (CSI) effect. We revisit the channel equalization problem for FBMC-based massive MIMO, address the shortcomings of the existing equalizers in the literature, and make them more applicable to practical scenarios. The proposed receiver in this paper consists of two stages. In the first stage, a linear combining of the received signals at the base station (BS) antennas provides a coarse channel equalization and removes any multiuser interference. In the second stage, a per subcarrier fractionally spaced equalizer (FSE) takes care of any residual distortion of the channel for the user of interest. We propose an FSE design based on the equivalent channel at the linear combiner output. This enables the applicability of our proposed technique to small and/or distributed antenna setups such as cell-free massive MIMO. Finally, the efficacy of the proposed techniques is corroborated through numerical analysis. [ABSTRACT FROM AUTHOR]

Applying non-orthogonal multiple access (NOMA) in millimeter-wave (mmWave) networks has the potential to significantly enhance the spectral efficiency. In this paper, we propose an opportunistic beam-splitting NOMA scheme to fully exploit the antenna array gain in downlink mmWave networks, where single- and double-beam NOMA transmissions are dynamically enabled according to the spatial angle difference between the paired NOMA users, thereby enhancing the flexibility of applying NOMA in mmWave networks. The base station with a single radio frequency chain implements the double-beam NOMA transmission by adopting the beam-splitting technique. We develop a unified theoretical performance analysis framework for the proposed scheme, while taking into account the spatially random users, link blockage model, and general distance-based user pairing strategy. By using tools from stochastic geometry, we derive the exact expressions of the coverage probability and the sum rate of the proposed scheme under both the LoS exponential and ball models. We further derive the corresponding upper bound to simplify the analytical expressions. Simulations validate the theoretical analysis and demonstrate the performance gains of the proposed scheme in terms of the coverage probability and sum rate over the conventional single-beam NOMA and orthogonal multiple access (OMA) schemes. [ABSTRACT FROM AUTHOR]

This paper studies the impact of unmanned aerial vehicle (UAV) wobbling on the coherence time of the wireless channel between UAVs and a ground user equipment (UE), using a Rician multi-path channel model. We consider two different scenarios for the number of UAVs: (i) single UAV scenario (SUS), and (ii) multiple UAV scenario (MUS). For each scenario, we model UAV wobbling by two random processes, i.e., the Wiener and sinusoidal processes, and characterize the channel autocorrelation function (ACF) which is then used to derive the coherence time of the channel. For the MUS, we further show that the UAV-UE channels for different UAVs are uncorrelated from each other. A key observation in this paper is that even for small UAV wobbling, the coherence time of the channel may degrade quickly, which may make it difficult to track the channel and establish a reliable communication link. [ABSTRACT FROM AUTHOR]

In this paper, we analyse a secure transmission scheme using rateless codes (RC) in a delay constrained system. By using RC, secrecy is achieved if the legitimate receiver can accumulate required number of packets before an eavesdropper does. To achieve this, we employ transmit antenna selection (TAS) at the base station to improve the main channel and, artificial noise (AN) is generated by the use of a cooperative jammer to degrade the eavesdropper's channel. Quality of violation probability (QVP) which consists of both the delay violation probability and the intercept probability is used as a performance metric. A closed-form expression for QVP is derived. We show that using TAS for reducing QVP is effective only at lower signal to noise ratio (SNR). We also observe that on increasing number of antennas at the source ($N_{A}$) while using TAS along with AN, QVP decreases for delay sensitive services, whereas, in case of delay tolerant applications, increasing $N_{A}$ is effective at low SNR. [ABSTRACT FROM AUTHOR]

This paper considers the precoding problem in massive multiuser multiple-input multiple-output (MU-MIMO) systems equipped with low-resolution digital-to-analog converters. In previous literature on this topic, it is commonly assumed that the channel state information (CSI) is perfectly known. However, in practical applications the CSI is inevitably contaminated by noise. In this paper, we propose, for the first time, an eigen-inference (EI) precoding scheme to improve the error performance of the coarsely quantized massive MU-MIMO systems under imperfect CSI, which is mathematically modeled by a sum of two rectangular random matrices (RRMs): $\sqrt{1 - \eta } {{\bf H}} + \sqrt\eta {{\bf E}}$. Instead of performing analysis based on the RRM, using Girkoąŕs Hermitization trick, the proposed method leverages the block random matrix theory by augmenting the RRM into a block symmetric channel matrix (BSCA). Specially, we derive the empirical distribution of the eigenvalues of the BSCA and establish the limiting spectra distribution connection between the true BSCA and its noisy observation. Then, based on these theoretical results, we propose an EI-based moments matching method for CSI-related noise level ($\eta$) estimation and a rotation invariant estimation method for CSI reconstruction. Based on the cleaned CSI, the quantized precoding problem is tackled via the Bussgang theorem and the Lagrangian multiplier method. The prosed methods are finally verified by numerical simulations and the results demonstrate the effectiveness of the proposed precoder. [ABSTRACT FROM AUTHOR]

In this paper, a low complexity massive multiple-input multiple-output technique is studied with a geometry-based stochastic channel model, called COST 2100 model. We propose to exploit the discrete-time Fourier transform of the antenna correlation function to perform user scheduling. The proposed algorithm relies on a tradeoff between the number of occupied bins of the eigenvalue spectrum of the channel covariance matrix for each user and spectral overlap among the selected users. We next show that linear precoding design can be performed based only on the channel correlation matrix. The proposed scheme exploits the angular bins of the eigenvalue spectrum of the channel covariance matrix to build up an “approximate eigenchannels” for the users. We investigate the reduction of average system throughput with no channel state information at the transmitter (CSIT). Analysis and numerical results show that while the throughput slightly decreases due to the absence of CSIT, the complexity of the system is reduced significantly. [ABSTRACT FROM AUTHOR]

In this paper, we study the three-dimensional (3D) path planning problem for cellular-connected unmanned aerial vehicle (UAV) taking into account the impact of 3D antenna radiation patterns. The cellular-connected UAV has a mission to travel from an initial location to a destination. In this process, there is a trade-off between the flight time and the expected communication outages duration, which requires planning a suitable route to avoid the weak coverage region. However, as the existing cellular networks are primarily designed for ground coverage, the communication coverage in the sky tends to be intermittent and irregular due to the potential for severe interference and obstructions (such by buildings), which brings great challenges to 3D path planning. To address this challenge, we first construct a 3D coverage map that stores the expected outage probability over each locations. We then propose a multi-step dueling DDQN (multi-step D3QN) based algorithm to design the local optimal UAV path by leveraging the constructed coverage map. In this algorithm, the UAV acts as the agent to learn the appropriate action to complete the flight mission. Numerical results show the effectiveness of the proposed algorithm for connectivity-aware UAV path planning and the superiority of 3D path design over its 2D counterparts. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel generalized space-code index modulation (GSCIM) scheme for spectrum-efficient and energy-saving transmission. In our proposed scheme, the input information bits are transmitted not only by modulated symbols, but also by the activated transmit antennas pattern and the selected spreading code patterns for the in-phase and quadrature components. Due to the increase of the index dimension, more information bits can be implicitly transmitted, which can improve energy efficiency and have a higher data rate compared with spatial modulation (SM), generalized SM (GSM), generalized CIM-aided SM (GCIM-SM) and CIM-aided quadrature spatial modulation (CIM-QSM). In order to further reduce the complexity of despreading-based maximum likelihood (ML) detection, we propose an enhanced low-complexity detector that can achieve near-ML error performance. An analytical upper bound on the average bit error probability associated with the optimal ML detection is derived, which is verified by simulation results. Simulation results also show that the proposed GSCIM scheme outperforms SM, GSM, GCIM-SM and CIM-QSM schemes in terms of error performance. [ABSTRACT FROM AUTHOR]

This paper presents an optimization approach for a system consisting of multiple bidirectional links over a two-way amplify-and-forward relay. Improvement to the fairness of the system is desired. All user pairs exchange information over one relay station (RS) with multiple antennas. Due to the joint transmission to all users, the users are subject to mutual interference. A mitigation of the interference can be achieved by max–min fair precoding optimization where the relay is subject to a sum power constraint. The resulting optimization problem is nonconvex. This paper proposes a novel iterative low-complexity approach based on a modified Levenberg–Marquardt (LM) method to find near optimal solutions. The presented method finds solutions close to the standard convex-solver-based relaxation approach. [ABSTRACT FROM PUBLISHER]

This paper addresses energy efficiency (EE) optimization problems for uplink multiuser multiple-input–multiple-output (MIMO) systems with zero-forcing (ZF) transceivers, subject to a joint power and rate constraint for each user. As the optimization problem considered in this paper is quite different from the traditional one, directly applying the Dinkelbach method to the new EE optimization problem cannot bring an advantage of low complexity. Hence, we try to propose a novel approach inspired by the homotopy algorithms, where we concentrate our attention on the solution path for the EE optimization. Making use of the piecewise-defined property between power allocations and the overall transmission power, we fit the entire path of solution for every value of the overall transmission power by replacing the search variable with a specially selected parameter. By checking only a finite number of breakpoints, we then try to propose a new homotopy-type algorithm to obtain the maximum EE in an exact closed form to reduce the computational complexity significantly. Simulation results verify the performance of the new method. [ABSTRACT FROM PUBLISHER]

In this paper, an antenna synthesis process is investigated for Intelligent Transportation System (ITS) application. The wireless communication between Road Side Units (RSUs) and On Board Units (OBUs) located in the vehicles enables smart mobility. However, to support high speed vehicles and high data rates, a wider coverage area by the RSU antennas projected on the highway is required. This is defined by the radiation patterns of the RSU antennas. On a multi-lane highway, interference from the adjacent lanes is a critical issue which determines the communication reliability in terms of Single-to-Interference plus Noise Ratio (SINR). Hence, in this paper, an interference-aware antenna synthesis process is proposed and a planar array is optimized based on the objective function of obtaining a wide coverage area in terms of SINR distribution for a given modulation scheme. The proposed antenna array enhances the reliable communication area and provides improved SINR distribution across the lane for misaligned vehicles from the center of the lane. The results indicate that the proposed antenna array performs better than the existing designs in terms of communication reliability. [ABSTRACT FROM AUTHOR]

In this paper, we study the effects of joint transmit and receive antennas’ selection on full-duplex (FD) multiple-input-multiple-output (MIMO) networks’ performance. The antennas’ selection problem is, in general, a combinatorial problem whose complexity grows exponentially with the number of antennas. To fully understand the effects of antennas’ selection, we study the sum rate maximization problem in a single-cell network with an FD-MIMO base-station (BS). First, we consider a system with a normal-scale MIMO full-duplex BS, i.e., a normal-scale FD MIMO system. The sum rate maximization problem is studied for two different scenarios; in the first scenario, we consider jointly optimizing the transmit and receive antennas’ selection with the precoder and the receiver weights. A Generalized Bender's Decomposition based algorithm is proposed to solve the mixed-integer nonlinear sum rate maximization problem. In the second scenario, we consider self-interference cancellation via zero-forcing (ZF) transmission. A heuristic algorithm is proposed to solve the sum rate maximization problem by optimizing the selection of the transmit antennas, receive antennas, and the receive antennas at which self-interference is nulled. Second, in a very-large scale, i.e., massive MIMO system, we derive lower bounds for the uplink and downlink rates with ZF receiver and precoder, respectively. The sum rate is maximized by jointly optimizing the transmit to receive antennas ratio and the ratio of the receive antennas at which self-interference is nulled. Finally, via numerical analysis, we evaluate the performance of the formulated sum rate maximization problems. [ABSTRACT FROM AUTHOR]

In this paper, we study the beam synthesis and management methods for the phased antenna array-based wireless communications systems, e.g., 5 G mmWave communications. First, we propose a novel on-off beam synthesis method that can synthesize any given on-off beam pattern. The proposed method maximizes the beam power towards a given set of on-directions while suppressing the power towards all off-directions. Second, by using a set of beams synthesized by the proposed on-off beam synthesis method, we design a non-interactive hierarchical beam management algorithm that can greatly reduce the radio resource usage, feedback overhead, and the latency of the beam discovery, compared to the exhaustive beam search algorithms. Since the proposed beam management algorithm is non-interactive, it can be applied to the initial access as well as the beam tracking, and is especially useful for supporting a massive number of devices. Finally, we show the validness of the proposed beam synthesis and management methods by conducting experiments on a phased antenna array experimental testbed. [ABSTRACT FROM AUTHOR]

In wireless communication systems, the correlation among the antennas of diversity systems can hardly be neglected. To the best of our knowledge, no previous studies have attended to address, thoroughly, this problem for the cross-correlation-based detectors. This will be the topic of this paper. Namely, in this paper, we consider the performance assessment of a second-order decision metric that is based on the cross correlation of antenna's output. The detector performance analysis has been made concerning the receiver operating characteristic curves, the robustness to estimation uncertainty, and the design parameters. This last introduces the minimum required sample number that guarantees a given detection performance. To this end, the probability distribution of the inner product of two complex non-zero-mean partially correlated random vectors is investigated. Next, we exhibited the relevance of our results through the analytical performance derivation of the cross-correlation-assisted sensing approach in terms of design parameters, spectral efficiency, and decision reliability. Monte Carlo simulations are achieved to prove the tightness of our derived results. [ABSTRACT FROM AUTHOR]

Next-generation heterogeneous cellular network (HCN) expects more and more deployment of the base stations and spectrum to achieve data rate in gigabits per second with seamless connectivity. Recently, small cell deployment has proven its effectiveness for increasing the coverage and area spectral efficiency (ASE) of the cellular network. Although, dense small cell deployment also increases the deployment cost and cross-tier interference of the network. This paper suggests switching-based mixed millimeter wave (mmW)/ultra high frequency (UHF) cellular network as a possible solution to overcome these challenges. In mixed mmW/UHF cellular network (named as MMUCN), mmW is used as the main transmission link, and UHF band is utilized as a backup link. In this paper, a theoretical framework is developed using tools from the stochastic geometry to analyze the outage performance, ASE, and deployment cost efficiency (DCE) of the MMUCN, which comprises existing macro base stations and mmW base stations. Optimal mmW base station densities constraints by the outage are calculated, which maximizes the ASE and DCE. Furthermore, a multiobjective optimization problem is formulated to maximize ASE and DCE simultaneously. Numerical results show that MMUCN outperforms UHF-based two-tier cellular network and efficiently mitigates the cross-tier interference of the system. [ABSTRACT FROM AUTHOR]

New emerging services, such as real-time video streaming or video on demand, are causing rapid growth in packet transmission over wireless networks. Unlike voice calls, for which the duration is usually not very long, video streaming applications require continuous transmission for a long time. Therefore, video streaming applications in mobile networks consume more energy compared with voice calls. Thus, the task of optimizing data transmission algorithms has become more important during the last few years. Apparently, the majority of multimedia traffic is video transmission. These applications consume much more power, compared with audio or general data transmission, because of higher throughput requirements. This paper addresses the problem of decreasing power consumption due to video transmission applications in Long-Term Evolution (LTE) networks. There are existing solutions for managing power consumption during video transmission. In particular, Third-Generation Partnership Project LTE Advanced (LTE-A) has defined the discontinuous reception/transmission (DRX/DRT) mechanism to allow devices to turn off their radio interfaces and go to sleep in various patterns. Some other similar solutions suggest DRX/DRT optimization to maximize the sleep periods of devices while guaranteeing quality of service in multimedia applications. However, existing solutions for packet transmission optimization are not very effective without physical-layer optimization. However, existing solutions for packet transmission optimization are not very effective without physical-layer optimization. We suggest a new method of modulation for improving energy efficiency of wireless video transmission. Four different schemes of quasi-quadrature modulation using multiple-input–multiple-output (MIMO) techniques with different quality of service performances are proposed in this paper. We simulate H.264/AVC video transmission. Results confirm the theoretical analysis. The proposed approach is able to improve energy efficiency while providing the same packet loss probability. [ABSTRACT FROM PUBLISHER]

Direction-of-arrival (DOA) information is vital for multiple-input-multiple-output (MIMO) systems to complete localization and beamforming tasks. Switched antenna arrays have recently emerged as an effective solution to reduce the cost and power consumption of MIMO systems. Switch-based array architectures connect a limited number of radio frequency chains to a subset of the antenna elements forming a subarray. This paper addresses the problem of antenna selection to optimize DOA estimation performance. We first perform a subarray layout alignment process to remove subarrays with identical beampatterns and create a unique subarray set. By using this set, and based on a DOA threshold region performance approximation, we propose two antenna selection algorithms; a greedy algorithm and a deep-learning-based algorithm. The performance of the proposed algorithms is evaluated numerically. The results show a significant performance improvement over selected benchmark approaches in terms of DOA estimation in the threshold region and computational complexity. [ABSTRACT FROM AUTHOR]

Multi-numerology transmission is a promising multiple access scheme for flexible communication systems, which can simultaneously support users with different service requirements. To this end, both inter- and intra-numerology interference (inter-NI and intra-NI) should be suppressed, which is not straightforward. This paper proposes a novel zero-forcing (ZF) precoding design, which perfectly eliminates all the interference, for massive multiple-input multiple-output (MIMO) systems with multi-numerology. First of all, we express the signal-to-interference-plus-noise ratio (SINR) of the multi-numerology system with spectrum sharing. From the SINR representation, we identify the channels that precoders must nullify to suppress inter-NI. After that, we propose a ZF precoder suppressing both inter-NI and intra-NI perfectly. The lower bound of ergodic achievable rate with perfect channel state information at the transmitter (CSIT) is analyzed. Based on the lower bound of ergodic achievable rate, we present the feasible rate region. Also, we propose two power allocation schemes: user fairness and the ergodic sum rate maximization. The simulation results demonstrate the advantage of the proposed precoding design and verify our analysis results. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the performance of convolutionally coded space-shift keying (SSK) modulation on block-fading channels. We derive the transfer function bound for the conditional error performance of coded SSK modulation. Existing works on SSK error performance focus mostly either on uncoded systems or on coded systems with independent fading between successive symbols. Code performance analysis is complicated by the fact that SSK modulation does not yield a uniform symbol, i.e., the error probability of a bit in a symbol is not independent of the position of the bit in the label. Furthermore, there are no nearest neighbors in the SSK constellation. The code and modulation must be jointly analyzed. We show techniques that can be employed to derive the error transfer function of the convolutional code. The degrees of separation in SSK modulation are accurately represented. The diversity order achieved by the system can be predicted. We also show a technique that can simplify analysis of the coded system. We present simulation results that demonstrate the asymptotic accuracy of the derived transfer function bound. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the ergodic achievable rate of a large uplink multiuser multiple-input–multiple-output (MU-MIMO) system over generalized- $K$ fading channels. In the considered scenario, multiple users transmit their information to a base station equipped with a very large number of antennas. Since the effect of fast fading asymptotically disappears in massive MIMO systems, large-scale fading becomes the most dominant factor for the ergodic achievable rate of massive MIMO systems. Regarding this fact, in our work, we concentrate our attention on the effects of large-scale fading for massive MIMO systems. Specifically, some interesting and novel asymptotic expressions of ergodic achievable rate have been derived with both perfect channel state information (CSI) and imperfect CSI. Simulation results assess the accuracy of these analytical expressions. [ABSTRACT FROM PUBLISHER]

In this paper, we consider decode-and-forward (DF) relaying of the data of a multiple-antenna-based source Earth station, via a single-antenna-based satellite, to a multiple-antenna-based destination Earth station. The source uses beamforming for transmission of the data, and the destination utilizes the maximal ratio combining for demodulating the transmitted signal. The uplink and downlink satellite channels are assumed to be shadowed-Rician (SR) fading. First, we consider independent and identically distributed SR fading and derive the closed-form expressions of the approximate bit error rate (BER) and probability of outage for the considered scheme. By using the BER expression, the analytical diversity order of the scheme is obtained. It is deduced on the basis of the diversity order analysis that the diversity of the considered DF scheme linearly depends upon the minimum number of antennas at the source and destination nodes. Next, we consider correlated SR fading links and derive power-series-based expression of the approximate BER of the DF satellite relay system. For the correlated SR fading, the diversity order is analytically obtained; it is shown by analysis and simulation that the diversity order of the scheme with correlated channels does not depend upon the antenna correlation matrices of the source and destination nodes. [ABSTRACT FROM PUBLISHER]

This paper considers limited feedback for a two-cell interfering multiple-input–multiple-output multiple-access channel (MIMO-MAC). We propose a QR decomposition-based interference alignment (QRD-IA) scheme for efficient limited feedback and investigate the conditions for the antenna configuration. We characterize the interference leakage caused by quantization error as a function of the number of feedback bits. To minimize the interference leakage, we further propose a quantized-precoder-based IA (QP-IA) scheme by modifying the proposed QRD-IA scheme. By characterizing the interference leakage of the QP-IA scheme, we investigate the number of feedback bits to maintain the degrees of freedom (DOFs) in the two-cell interfering MIMO-MAC and a feedback bit allocation algorithm to improve the sum rate. From simulation results, we demonstrate that our proposed schemes can provide better sum-rate performance than the existing scheme using the same number of feedback bits, and our feedback bit allocation algorithm provides a higher sum rate compared with equal feedback bit allocation. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a full-duplex (FD) relaying system with multi-input multi-output (MIMO) with simultaneous wireless information and power transfer (SWIPT), where the communication from source to destination is assisted by a full-duplex decode-and-forward (DF) relay. The time switching (TS) protocol is used at the relay to harvest the energy of radio-frequency (RF) signals transmitted from the source. To improve both system performance and the amount of harvested energy, multiple antennas are used at source and destination. Transmit antenna selection (TAS) is employed at the source with an assumption that the feedback of channel state information (CSI) is outdated. Meanwhile, both selection combining (SC) and maximal ratio combining (MRC) techniques are applied at the destination. The closed-form expressions of the outage probability (OP), optimal throughput, and symbol error probability (SEP) are derived subject to the outdated CSI over Rayleigh fading channels. We also make a comparison between the performance of the proposed MIMO-FD relaying system with SWIPT and that of MIMO half-duplex (HD) relaying systems with and without SWIPT. The validity of derived mathematical expressions is verified by Monte-Carlo simulations. Numerical results show that the TAS/MRC scheme gives better system performance than the TAS/SC scheme. Moreover, higher energy harvesting time is needed to maximize the throughput than to minimize the OP. [ABSTRACT FROM AUTHOR]

High-speed railway (HSR) has demonstrated tremendous growth worldwide, and is currently attaining a maximum velocity of 575 km/h. Such a high speed makes mobile wireless communications extremely challenging for HSR since the handover (HO) rate increases with speed, resulting in a high call dropping probability. By employing a dedicated distributed antenna system (DAS) along with the two-hop network architecture, in this paper, we propose a frequency switch (FSW) scheme to mitigate the persistent HO issue in conventional HSR wireless communication systems. The proposed scheme significantly alleviates interruption time associated with the traditional HO process, providing an effective scheme when the train moves across small cells covered by remote antenna units (RAUs) belonging to the same central unit (CU). In order to further reduce the HO command failure probability, an enhanced fast predictive HO mechanism is proposed by starting the HO process in advance, when the train moves from one RAU to the next one controlled by the adjacent CU. Analytical results show that compared to the traditional HO scheme, the proposed schemes can improve the system performance substantially by delivering ultra-reliable low-latency communications with a reduced HO/FSW rate. [ABSTRACT FROM AUTHOR]

In recent years, intelligent transportation systems are a vital part of the development of smart cities. In intelligent transportation systems, it is necessary for each vehicle to know the states of all other running vehicles within a range, depends on the road speed limit. The states include location, travelling direction, speed, and possibly other useful information. Knowing the states of surrounding vehicles is critical in high-risk locations, such as traffic intersections and roundabouts. The development of 5G and its technologies, such as massive multiple-input multiple-output antenna, enables a new communication model, termed vehicle-to-infrastructure edge network (V2IEN), to achieve the above communication goal. In this paper, we study the optimization of the data throughput of the proposed V2IENs in 5G with the Time Division Duplex scheme. We show that due to the nature of information flow in the proposed V2IENs, the uplink and downlink traffic loads are asymmetric. This asymmetric characteristic allows maximizing the degrees of freedom of the V2IENs by optimizing the time-slot resources for uplink and downlink transmission. In this work, we present the sum-DoF capacity of the V2IENs with proof. We demonstrate that a significant DoF gain is achieved for the V2IENs by carefully allocate the system transmission time resources. We further propose an iterative algorithm for network sum-rate maximization via the optimization of the vehicle and base station precoders. Numerical results demonstrate that a careful design of the precoders at the base station and at the vehicles can considerably improve the V2IENs performance. [ABSTRACT FROM AUTHOR]

A new approach of channel estimation for multiantenna systems is put forward in this paper, which can be adopted in high-mobility situations such as high speed trains. The channel impulse response is abstracted as three domains to improve the modeling accuracy. Both the time-domain preamble and the frequency-domain pilot are adopted in the orthogonal frequency division multiplexing (OFDM) frame. First, the training in time domain is exploited to obtain the partial common support of the channel. Then, the pilot location optimized by the genetic algorithm is employed to build the framework of structured compressive sensing and recover the channel. A novel compressive recovery algorithm called adaptive support-aware block orthogonal matching pursuit for multiple input multiple output-OFDM systems is proposed to solve the problem. It is manifested in the simulation that the scheme in this paper outperforms the traditional ones in both recovery probability, mean square error, and bit error rate over the doubly selective channel with low computational complexity. [ABSTRACT FROM AUTHOR]

This paper considers multicell scheduling for coordinated multiple-input multiple-output cellular networks. In a multicell scenario, intercell interference, which is the major challenge degrading system performance, can be suppressed via multicell coordination. However, when the number of users is larger than that can be served, user/multimode selection is necessary, and can significantly enhance the performance in such interference-limited environment. Nevertheless, user selection in a multicell scenario incurs high computational complexity and overhead signalling. To this end, in this paper, low complexity greedy algorithms are proposed for user selection. The algorithms are based on the concept of angle between subspaces and intersection of null spaces, and work in partially distributed fashion with limited information exchange. By these algorithms, channel feedback can be greatly reduced with reasonable computational complexity. In addition, multimode scheduling schemes are proposed for this multicell set up, where the spatial streams are adaptively selected. The proposed algorithms are analysed and compared with the optimal solution obtained by exhaustive search. Simulation results show that the algorithms achieve most of the throughput achievable by the optimal solution. [ABSTRACT FROM AUTHOR]

This paper investigates the energy consumption of distributed large-scale MIMO systems made up of a set of remote radio heads (RRHs), each of which is powered by both an independent energy harvesting source and the grid. The grid energy source allows to compensate for the randomness and intermittency of the harvested energy. Hence, the problem of grid power consumption minimization has to be solved by efficiently managing the energy delivered from different sources while satisfying the system requirements in terms of users’ quality of service demands. First, this paper solves the optimal offline version of the problem using linear programming. In fact, the main problem is decomposed and heuristically solved in order to deal with the large number of constraints and variables. Since sometimes all the users cannot be served, an iterative link removal algorithm is devised ensuring the feasibility of the problem. Next, we investigate the online energy management problem. We first propose a dynamic programming approach to obtain the optimal online solution but with high complexity. Then, we develop and propose a low complexity heuristic solution based on using the maximal available energy at the batteries. Taking benefits of the characteristics of large-scale MIMO and the modeling of the harvested energy as Markov chains, we devise an efficient online energy management algorithm based on energy prediction. Finally, we propose a heuristic solution for RRH on/off operation with the objective of improving the system energy efficiency. The performance of the proposed algorithms is evaluated by simulations and it is shown that the proposed energy management approaches offer efficient use of nonrenewable energy to compensate the variability of renewable energy in large-scale MIMO systems. [ABSTRACT FROM PUBLISHER]

Generalized spatial modulation (GenSM) aided millimeter wave (mmWave) multiple-input multiple-output (MIMO) has recently received substantial academic attention. However, due to the insufficient exploitation of the transmitter's knowledge of the channel state information, the achievable rates of state-of-the-art GenSM-aided mmWave MIMO systems are far from being optimal. Against this background, a novel analog precoding scheme is proposed in this paper to improve the spectral efficiency (SE) of conventional GenSM-aided mmWave MIMOs. More specifically, we firstly manage to lower-bound the achievable SE of GenSM-aided mmWave MIMO with a closed-form expression. Second, by exploiting this lower bound as a cost function, a low-complexity iterative algorithm is proposed to design the analog precoder for SE maximization. Finally, numerical simulations are conducted to substantiate the superior performance of the proposed design with respect to state-of-the-art GenSM-aided mmWave MIMO schemes. [ABSTRACT FROM PUBLISHER]

Massive multiple-input multiple-output (MIMO) is considered as a critical technique in 5 G New Radio (NR), due to its capability to significantly improve data rate and link reliability for the radio link. To make it a reality, it is essential to evaluate massive MIMO performance in realistic spatial fading channel conditions. Specifically, dynamic spatial channel emulation is crucial to evaluate the massive MIMO beam operations. Due to the high cost associated with both the traditional conduced testing method and the standardized multi-probe anechoic chamber (MPAC) based Over-the-Air (OTA) testing setup for massive MIMO performance testing, fading channel emulation for massive MIMO testing using a conductive phase matrix setup has been proposed in the literature. However, it is still a challenging problem to emulate dynamic spatial channels in a cost-effective and efficient manner for the conductive phase matrix setup, since traditional algorithms suffer from high computational complexity and system cost. This paper proposes a fast and accurate framework to emulate dynamic spatial channels in the phase matrix setup, where the basic idea is to mimic a virtual MPAC setup. By doing so, we can mimic MPAC setup with flexible probe configurations. Furthermore, a novel successive cancellation strategy and a closed-form algorithm are proposed to determine the probe locations and probe weights, respectively, which can significantly reduce the computational complexity associated with dynamic channel emulation. Simulation results show that the proposed algorithm is highly accurate and computationally efficient, compared to state-of-art solutions. Further, we apply our developed algorithm to emulate measured non-stationary channels and excellent emulation accuracy can be achieved. The proposed method can be employed for emulating dynamic spatial channels, which is of great importance for massive MIMO performance testing. [ABSTRACT FROM AUTHOR]

Providing seamless connectivity to unmanned aerial vehicle user equipment (UAV-UE) is very challenging due to the encountered line-of-sight interference and reduced gains of down-tilted base station (BS) antennas. For instance, as the altitude of UAV-UEs increases, their cell association and handover procedure become driven by the side-lobes of the BS antennas. In this paper, the performance of cellular-connected UAV-UEs is studied under 3D practical antenna configurations. Two scenarios are studied: scenarios with static, hovering UAV-UEs and scenarios with mobile UAV-UEs. For both scenarios, the UAV-UE coverage probability is characterized as a function of the system parameters. The effects of the number of antenna elements on the UAV-UE coverage probability and handover rate are then investigated. Moreover, a lower bound on the handover probability is derived as a function of the number of antenna elements and the UAV-UE mobility speed. Results reveal that the UAV-UE coverage probability under a practical antenna pattern is lower than that under a simple antenna model. Moreover, vertically-mobile UAV-UEs are susceptible to altitude handover due to consecutive crossings of the nulls and peaks of the antenna side-lobes. The effect of altitude handover is also shown to be effectively mitigated by serving UAV-UEs cooperatively from multiple ground BSs. [ABSTRACT FROM AUTHOR]

In this paper, a dual circularly-polarized (CP) multi-beam antenna is proposed for future vehicular radar applications. The antenna is composed of two pillbox reflector beamforming networks (BFNs) and a series-fed microstrip line based dual CP leaky-wave antenna (LWA) array, which has a symmetrical structure and can obtain both left hand circular polarization (LHCP) and right hand circular polarization (RHCP) by switching the exciting current direction of the microstrip line. Besides, a shorted stub is loaded in the LWA to suppress the open-stop band (OSB), and thus achieve the broadside radiation and good impedance matching of the LWA. To realize the dual-polarized radiation characteristic with low-cost passive beam scanning capability, two pillbox BFNs are connected at both sides of the LWA to share the LWA aperture. The two different BFNs can excite different CP radiation patterns. A prototype of the proposed antenna is fabricated in the frequency band 23.5–24.5 GHz, and the measured results approve that the proposed antenna can realize ±36° beam scanning range with −4.0 dB crossover level, and the gain is higher than 17.7 dBi in the operating band. The advantages of the proposed antenna, including low-profile, low-cost, passive beam scanning ability, and dual circular polarization, make it an attractive choice for low-cost millimeter-wave radar applications. [ABSTRACT FROM AUTHOR]

In cellular communication systems, it is conventional to assume the absence of a line of sight (LoS) path between the users and theirassociated access points (APs). This assumption however becomes questionable in the context of recent developments in the direction of cell-free (CF) massive MIMO systems. In the CF massive MIMO, the AP density is assumed to be comparable with the user density, which increases probability of existence of an LoS path between the users and their associated APs. In this paper, we analyze the performance of an uplink CF massive MIMO system, with a probabilistic LoS channel model. Here, we first derive the effective statistics of this channel model, and argue that their behaviour is fundamentally different from that of the conventional rich scattering channels. Utilizing these statistics, we next compare the rates achievable by CF massive MIMO systems, under both stream-wise and joint decoding at the central processing unit. Following this, we also discuss the centralized MMSE based data detection to obtain a complexity/ performance trade-off. Finally, using detailed Monte-Carlo simulations, we validate our analytical results, and evaluate the performance of the three data detection schemes. [ABSTRACT FROM AUTHOR]

Massive multi-user (MU) multiple-input multiple-output (MIMO) is an enabling technology for the next-generation wireless systems as it provides significant improvements in terms of spectral efficiency and per-user peak data rates compared to existing, small-scale MIMO. The presence of increasing antennas at the infrastructure base-station results, however, in high computational complexity for data detection, which requires low-complexity algorithms and efficient hardware designs. Descent search (DS) algorithms have been proposed to reduce complexity of data detection and enable efficient hardware implementations. However, their error-rate performance is not always satisfactory for channels that exhibit correlation or for systems with small base-station to user antenna ratios. In this paper, we propose a linear inequality constraint quadratic programming (LICQP) model, which enables the design of a constrained DS (CDS) detector that outperforms existing DS algorithms. To further improve the performance of CDS in the presence of challenging channel conditions, we propose a universal pre-conditioner. Theoretical analysis and numerical results indicate that CDS with pre-conditioning reduces the complexity over the state-of-the-art (SOA) by $60\%$. We develop a reference Xilinx Virtex-7 FPGA design, which demonstrates that our implementation achieves $1.75\boldsymbol{\times }$ higher throughput (35 Mbps in a 128 antenna, 8 user system) at comparable hardware resource utilization. [ABSTRACT FROM AUTHOR]

Clipping is an effective technique to adjust the peak-to-average power ratio (PAPR) of spatial modulation (SM) orthogonal frequency-division multiplexing (OFDM) systems. In this paper, an iterative soft compensation method is proposed for mitigating the effect of the clipping noise. In the proposed method, the sparsity and relativity of all transmit antennas are exploited, and the mean and power of the clipping noise are estimated based on the a priori information. Furthermore, the attenuation factor in each iteration is updated to yield a more accurate system model. Simulation results show that the proposed method is capable of providing considerable bit error rate (BER) performance gains over conventional compensation methods for both balanced and unbalanced antenna configurations. [ABSTRACT FROM AUTHOR]

Leaky coaxial cable (LCX) is applied broadly for many application scenarios because it can be utilized as antenna for user localization, wireless power transfer (WPT) and wireless coverage. Usually, one LCX can be used as one antenna, and therefore more cables are required for the configuration of an multiple-input and multiple-output (MIMO) system. This paper will provide a simple design that a 4-by-4 MIMO channel can be realized with one composite cable. Therefore the proposal can release the space limitation for MIMO deployment. The results show that, over 5 GHz frequency band, even though the distance between two V-type LCXs is 2 cm, the proposed 4-by-4 LCX-MIMO can have good channel condition which ensures the proposed composite cable can be made as a finer one. In addition, using user's position information (PI), we propose a simple power allocation scheme for the proposed LCX-MIMO system. Compared with the allocation method of equal power, the proposed method using PI can largely improve its capacity with the same level of computational complexity and without requirement of the feedback of channel status information (CSI). [ABSTRACT FROM AUTHOR]

In this paper, we investigate the energy-efficient hybrid precoding design for integrated multicast-unicast millimeter wave (mmWave) system, where the simultaneous wireless information and power transform is considered at receivers. We adopt two sparse radio frequency chain antenna structures at the base station (BS), i.e., fully-connected and subarray structures, and design the codebook-based analog precoding according to the different structures. Then, we formulate a joint digital multicast, unicast precoding and power splitting ratio optimization problem to maximize the energy efficiency of the system, while the maximum transmit power at the BS and minimum harvested energy at receivers are considered. Due to its difficulty to directly solve the formulated problem, we equivalently transform the fractional objective function into a subtractive form one and propose a two-loop iterative algorithm to solve it. For the outer loop, the classic Bi-section iterative algorithm is applied. For the inner loop, we transform the formulated problem into a convex one by successive convex approximation techniques and propose an iterative algorithm to solve it. Meanwhile, to reduce the complexity of the inner loop, we develop a zero forcing (ZF) technique-based low complexity iterative algorithm. Specifically, the ZF technique is applied to cancel the inter-unicast interference and the first order Taylor approximation is used for the convexification of the non-convex constraints in the original problem. Finally, simulation results are provided to compare the performance of the proposed algorithms under different schemes. [ABSTRACT FROM AUTHOR]

The self-healing function in self-organizing networks can not only detect the presence of fault conditions but also diagnose the root causes in a fully autonomous fashion. In this paper, we propose a machine learning based diagnosis algorithm that uses network condition indicators such as key performance indicators and performance management counters for network condition diagnosis. The proposed algorithm judiciously combines the classical supervised softmax neural network (SNN) and support vector machine (SVM), and therefore can be efficiently implemented by off-the-shelf tools while achieving promising diagnosis performance. In particular, the proposed algorithm combines the features extracted from SNN and SVM, and is able to robustly diagnose fault conditions with different levels of severity. Besides, the proposed algorithm can also handle complex scenarios where there is more than one fault condition present at the same time. Considering that data with labels of multiple faults are not available in general, we further propose a simple retraining procedure which allows the proposed algorithm to perform multi-fault diagnosis even when the training data are only single labeled. Simulation results demonstrate that the proposed algorithms provide desired diagnosis performance in both single-fault and multi-fault scenarios and outperform the traditional scoring based methods. [ABSTRACT FROM AUTHOR]