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In concurrent spectrum sharing scenarios between radars and wireless communication systems, one strict approach to protect the radar from undesired interference is locating the base stations outside a guard (or exclusion) zone of the radar. As a result, users inside that zone experience bad communication coverage. This paper uses Reconfigurable Intelligent Surfaces (RISs) to improve the base station coverage of users in the radar exclusion zone. The paper shows, through analysis and simulation, that joint optimization of base station and RIS locations improves the probability of coverage in the exclusion zone over the shared spectrum without disturbing the radar operation. [ABSTRACT FROM AUTHOR]

In this study, we investigate the operation of a user-number threshold-based base station (BS) on/off control, in which the BS turns off when the number of users is less than a specific threshold value. This paper presents a space-based analysis of the BS on/off control system to which a stochastic geometric approach is applied. In particular, we derive the approximated closed-form expression of the coverage probability of a homogeneous network (HomNet) with the user-number threshold-based BS on/off control. Moreover, the optimal user-number threshold for maximizing coverage probability is analytically derived. In addition to HomNet, we also derive the approximated closed-form expression of the coverage probability and the optimal user-number thresholds for a heterogeneous network (HetNet). The results show that HetNet, the analysis of which seems intractable, can be analyzed in the form of a linear combination of HomNets with weighted densities. In addition, the optimal user-number threshold of each tier is obtained independently from other tiers. The modeling and analysis presented in this paper are not only limited to the case of user-number threshold-based on/off control, but also applicable to other novel on/off controls with minor modifications. Finally, by comparing the analytical results with the simulated results, the theoretical contributions of this study are validated. [ABSTRACT FROM AUTHOR]

This paper considers the $\mathscr{L}_{2}$ string stability analysis and controller synthesis for vehicle platooning under jamming attacks and interferences from other communication channels. Jamming attacks and interferences for vehicle platooning systems are modeled as periodic denial of service attacks. Further, the vehicle platooning with denial of service attacks is modeled as a distributed switching system where an average dwell time approach is adopted for the stability analysis. Under the distributed switching system framework, this paper presents a co-design paradigm for the vehicle platooning. The distributed event-triggered method (ETM) and controllers are presented to guarantee $\mathscr{L}_{2}$ string stability, which can ensure that the output cannot be amplified along the vehicle platooning. Sufficient conditions for $\mathscr{L}_{2}$ string stability are then provided to guide the co-design of the ETM and controllers, which can be efficiently obtained by solving LMIs. Simulation results are presented to demonstrate the efficacy of the proposed co-design approach in addressing the denial of service attacks for vehicle platooning systems. [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]

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]

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]

This article studies the transmit beamforming security in the dual-functional radar-communication (DFRC) system, where the radar beam also serves as the artificial jamming to suppress potential eavesdropper channels. Unlike previous researches, which assumed that the lone target might be a potential eavesdropper on the adversary side, this paper analyses a more generic scenario in which the eavesdroppers’ channel state information (CSI) is unknown. The eavesdropping rate should be limited to guarantee transmission confidentiality, which is intractable owing to the unknown CSI. To address this issue, we present the long-term eavesdropping signal-to-interference-plus-noise ratio (SINR) as a more tractable security metric. Based on the long-term eavesdropping SINR, the sum rate maximization (SRM) and jamming power maximization (JPM) transmission scheme are investigated. For the SRM scheme, we propose a zero-forcing (ZF) suboptimal algorithm to solve the non-convex fractional programming (FP) problem, and for the JPM scheme, the resultant problem is solved via the semidefinite relaxation (SDR) technique. Finally, numerical results validate the effectiveness of the proposed beamforming approaches. [ABSTRACT FROM AUTHOR]

The terahertz (THz) waves with enormous bandwidth can be used along with the existing sub-6GHz and millimeter wave (mmWave) bands to achieve the ever evolving ecosystem of applications that need to be supported by the modern wireless networks. This paper investigates a user-centric dynamic base station (BS) clustering design for a hybrid network where THz, mmWave, and sub-6GHz BSs coexist. Invoking the proposed clustering model, the BS cooperation within each band is made possible by considering long term channel variations and all the surrounding BSs within a cluster with tunable size. A typical user is associated with the best BS cluster, from either a sub-6GHz, mmWave or THz tier based on the maximum signal-to-interference-plus-noise-ratio (SINR) criterion or the maximum rate criterion. Using tools from stochastic geometry, we assess the performance of the proposed user-centric hybrid system in terms of SINR and rate coverage performances, while accounting for: band specific propagation models, directional beamfroming, and BSs random locations. The accuracy of the analytical results is validated with Monte-Carlo simulations. The obtained results recognize a clear coverage/rate trade-off where a high fraction of THz BSs improves the rate significantly but may degrade the coverage performance. Thus, with carefully planned networks, enabling user-centric BS cooperation for hybrid wireless systems can achieve ultra-high rates while maintaining sufficient coverage in sixth-generation (6G) networks. [ABSTRACT FROM AUTHOR]

In a vehicular ad hoc network (VANET) based on IEEE 802.11p, the performance of the communication link is heavily influenced by interference. To quantify the impact of interference, analytical models usually explicitly or implicitly assumed the interference range beyond which interference is ignored. We find that the potential maximum interference range should be related to the minimum interference power that the device can perceive. However, most previous works on VANET performance modeling simply assumed a fixed interference range. The most recently proposed effective interference range dependent on the signal-to-interference-and-noise ratio (SINR) threshold may appear to exceed the potential maximum interference range, resulting in an overestimation of the impact of interference. This paper proposes the SINR related Effective Distance Constrained by the Maximum interference range-based (SED-CM) model for IEEE 802.11p VANET performance evaluation on the Highway. First, we give the potential maximum interference range setting by studying the empirical distribution of interference distance corresponding to the minimum interference power in NS2 simulation. The performance metrics are then derived. The proposed SED-CM model is further extended to the intersection scenario. We conducted extensive NS2 simulations to evaluate the proposed model and compare it with three typical models. Results show that the SED-CM model presents the best evaluation ability. Moreover, we experimentally analyzed the effect of vehicle speed on the performance of VANET by mapping the vehicle speed to the vehicle density. Results show that a faster beacon rate is required to meet the reliability requirement of safety applications with the increase in vehicle speed. [ABSTRACT FROM AUTHOR]

This paper investigates the capacity gain of full duplex (FD) self-backhauling over the half duplex (HD) counterpart in downlink cellular systems, and then proposes an opportunistic FD scheme. The first step is to derive the capacity gain of FD self-backhauling over the HD counterpart as a function of the system parameters in a computationally tractable form. Unlike previous studies on the capacity of FD self-backhauling, a practical constraint is imposed so that the end-to-end link achieves a target signal-to-interference-plus-noise ratio (SINR) for a successful link connection. Also, a condition under which FD is more beneficial than HD is derived. Specifically, the minimum allowable self interference cancellation factor and the maximum allowable cell radius for the benefit of FD are derived as an explicit function of system parameters. Their dependencies on the system parameters are investigated and compared with counterparts derived for single-hop point-to-point links. Lastly, to overcome the weak points of FD and HD, this paper proposes a user-wise opportunistic FD (OFD) self-backhauled scheme. To this end, an instantaneous channel gain-based FD/HD switching rule is derived from a condition under which FD cannot instantaneously satisfy the target SINR. We confirm the substantial capacity gain of the proposed user-wise instantaneous OFD over a cell-wise static duplex switching scheme, as well as the fixed duplex (HD or FD) schemes. When compared to the static duplex switching scheme, the proposed OFD is most beneficial at the boundary of HD-preferred and FD-preferred regions. Based on this, a system-level guideline is proposed for selecting the most practical scheme among OFD, FD, and HD by trading off capacity gain and switching overhead. Extensive simulation results are provided to confirm the correctness of the derivations and the related investigations. [ABSTRACT FROM AUTHOR]

The technical challenges, e.g. the mobility management and the offloading process, hinder the conventional cellular systems to meet the huge data traffic requirements of the next generation mobile communications. The traditional system (e.g dual-connectivity (DC)) has been proposed to improve the mobility management, however, it will inherit the big trade-off in the offloading process between the energy consumption for the small cell (SC) discovery (SCD) process and the efficiency of utilizing the system resources (e.g. frequency and signaling). In this paper, we present a framework to model the potential offloading opportunities as well as the offloading loss when a typical user equipment (UE) performs the inter-frequency (IRF) scan periodically. The proposed framework also studies the impact of the SCD on the energy efficiency. To improve the system performance and reduce the power consumption at the UEs, a new scheme, trio-connectivity (TC), is proposed in this paper to tackle the aforementioned challenges. The TC includes three planes: control-plane (C-plane), user-plane (U-plane) and indication-plane (I-plane). The I-plane works as an indicator to help the UE to identify and discover the SCs in the system prior to offloading. The role of the I-plane is to keep the SCD on one frequency channel regardless of the number of frequency channels in the system. In the proposed offloading mechanism, some of the energy consumption is transferred from the UE to the network. By using the proposed framework, UE energy efficiency and system energy efficiency as well as the total energy consumption are derived as performance metrics to compare between the TC and the DC. The results show that the TC can outperform the DC in dense cellular systems. [ABSTRACT FROM AUTHOR]

Recently, model-free power control approaches have been developed to achieve the near-optimal performance of cell-free (CF) massive multiple-input multiple-output (MIMO) with affordable computational complexity. In particular, deep reinforcement learning (DRL) is one of such promising techniques for realizing effective power control. In this paper, we propose a model-free method adopting the deep deterministic policy gradient algorithm (DDPG) with feedforward neural networks (NNs) to solve the downlink max-min power control problem in CF massive MIMO systems. Our result shows that compared with the conventional convex optimization algorithm, the proposed DDPG method can effectively strike a performance-complexity trade-off obtaining 1,000 times faster implementation speed and approximately the same achievable user rate as the optimal solution produced by conventional numerical convex optimization solvers, thereby offering effective power control implementations for large-scale systems. Finally, we extend the DDPG algorithm to both the max-sum and the max-product power control problems, while achieving better performance than that achieved by the conventional deep learning algorithm. [ABSTRACT FROM AUTHOR]

The proliferation of IEEE 802.11 or WiFi networks, and the explosive growth in traffic demands call for solutions to maximize the capacity of WiFi networks. Hence, maximizing the spatial reuse of WiFi networks is critical as doing so allows multiple concurrent transmissions. In this respect, a critical network parameter, Clear Channel Assessment (CCA) threshold, plays a vital role as it dictates whether a node is allowed to transmit after sensing the channel. In this paper, we propose to use Deep Q-network (DQN) under two learning patterns to select the CCA threshold of devices. We further consider Transmit Power Control (TPC) in conjunction with CCA threshold selection to improve the capacity of a WiFi network. The simulation results show that our approach is capable of selecting the optimal CCA threshold for each device. As a result, the average throughput is 62.4% higher than that of a legacy Dynamic Sensitivity Control (DSC) algorithm. [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]

The coexistence of multiple types of users in vehicular networks results in diversified service requirements and multiscale content differences, which poses new challenges to reliable content transmission. This paper proposes a hierarchical coded caching framework coupled with coded caching, vehicle-to-everything communications, and non-orthogonal multiple access techniques. We quantify the user request hit ratio under different communication modes and study the hit ratio maximization problem under the constraint of limited communication and caching resources. We propose a two-layer matching based optimization algorithm, including a user association layer in distributed content sharing and a user grouping layer in centralized content requesting. Simulation results verify that the proposed scheme can achieve a balance between hit ratio and transmission time, and meet the requirements of the content sharing scenario with multiscale content files and scalable user density. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is considered as a multiple access technique for supporting massive number of devices with high spectral efficiency. Simultaneous wireless information and power transfer (SWIPT) is an efficient solution for fully autonomous and sustainable communication networks. In this paper, application of SWIPT in networks employing cooperative NOMA (CNOMA) is investigated with imperfect channel state information (CSI). Performance of the CNOMA network with SWIPT is investigated in a multi-tier downlink scenario with macro-base stations (MBSs) and femto-base stations (FBSs). The distribution of MBSs and FBSs follow Poisson point process model. Unlike solution in the existing literature, instead of using only the superimposed signal for energy harvesting (EH), in this work, the cooperating node/user employs EH using interference from the adjacent base stations. Expressions for outage probability and throughput are derived at the user pair (comprising a cell-center user and a cell-edge user) served using NOMA. Comparison of the proposed EH system with the existing solutions is highlighted. Monte Carlo simulations are carried out to validate the analytical results. [ABSTRACT FROM AUTHOR]

In this paper, we propose a cost-efficient beamforming optimization algorithm for multi-user wireless communication systems associated with the intelligent reflecting surface (IRS). From the baseline successive refinement algorithm, which gives a sub-optimal solution for the power minimization problem under the signal-to-interference-plus-noise-ratio (SINR) constraint at each user, several optimization techniques are proposed to reduce the computation complexity while maintaining the algorithm-level performance. To reduce the number of required multiply-accumulate (MAC) operations, we first simplify the complicated matrix inversion by utilizing the channel hardening effect. We also present the two-phase refinement process for the group-level optimization of phase-shift elements, further relaxing the computation complexity as well as the processing latency. Applying the proposed optimization techniques, as a result, numerical results show that the fully-optimized algorithm can reduce the computational costs by up to 89.4% while showing less than 1 dB power loss, leading to the practical solution for the next-generation IRS-aided communication. [ABSTRACT FROM AUTHOR]

In Multiple-input multiple-output (MIMO) broadcast channels (BCs), the transmitter simultaneously broadcasts signals to multiple receivers at same frequency band, resulting in that the communication capacity is affected by both interference, channel fading and random noise. Although channel fading can be mitigated by transceivers, the signal-to-noise-ratio (SNR) of the practical communication system is still dynamically changing due to the randomly changing noise. Traditional MIMO transceiver optimization algorithms can not flexibly adapt to the dynamic changes of SNR, resulting in large performance degradation. In this paper, we comprehensively consider signal power and signal space dimensions of the received signal in MIMO BCs, and propose two transceiver optimization algorithms which can dynamically adapt to the variance of SNRs. In the proposed algorithms, SNR is adopted to be an adjustment factor to cope with its variance. When SNR is low, i.e, large noise, the algorithm parameters are automatically adjusted so that the signal power is preserved as much as possible to combat the loss of communication capacity caused by large random noise. Correspondingly, under the condition of high SNR environment, the algorithm parameters are adjusted automatically to effectively compress the inter-user-interference (IUI) and intra-user-inter-stream-interference (ISI) by optimizing signal space dimensions. Simulation results show that in different SNR environments, the proposed algorithms can automatically adjust the focus of optimization, so that the optimization of signal power and signal space dimensions can automatically adapt to different SNRs. Compared with traditional transceiver optimization algorithms, the proposed algorithms can improve the communication capacity within a large dynamic range of SNR. [ABSTRACT FROM AUTHOR]

The large spectral bandwidth at millimeter-wave (mmWave) frequencies provides a mean to achieve very high data rates in wireless communication systems. A unique characteristic of mmWave is that mmWave links are very sensitive to blockage and have large propagation path loss, which exhibits low line-of-sight (LoS) probability, unstable connectivity and unreliable communication. This paper studies the influence of the blockage in pedestrian scenario, explains in detail how blockage affects the mmWave propagation characteristics. In particular, we study the behavior of the blockage due to human mobility and how it affects the timescale for outage due to blockage using knife-edge diffraction model (KED). One of the existing solutions to overcome the influence of blockage, is to associate the user equipment (UE) with other available base stations (BSs) by handover (HO) if the serving BS is blocked. In this paper, for a pedestrian scenario, we propose two reinforcement learning (RL) based user association algorithms, which accounts for the past experience of the blockage on the position of the UE. One focuses on the reward to increase the sum LoS probability and is named as blockage-aware user association (BAUA). The other focuses on the reward to balance the trade-off between the throughput and the LoS probability and is named as modified BAUA. We compare the proposed algorithm with the conventional user algorithms such as the maximum throughput based algorithm and the maximum SINR based algorithm. Simulation results show that to increase the sum LoS probability BAUA would be suitable, and to increase the average throughput maximum throughput based method would be suitable. [ABSTRACT FROM AUTHOR]

This paper deals with the joint design problem of transmit waveform and receive filter for the robust detection of ground moving target with multiple-input multiple-output Space time adaptive processing (MIMO- STAP) radar in the presence of target and clutter uncertainties. With the prior knowledge of target and clutter statistics, the averaged signal-to-interference-plus-noise ratio (SINR) is formulated as a figure of merit to maximize. The robust joint design problems for the continuous and discrete phase cases, respectively, are formulated with the constant-modulus and similarity constraints. Then, an efficient iterative algorithm is developed for improving the SINR. Specifically, each iteration of the proposed algorithm involves the generalized eigenvalue decomposition to optimize the receive filter, while a nested iterative procedure involving Dinkelbach’s framework and alternating direction penalty method (ADPM) algorithm to design transmit waveform. The proposed algorithm can achieve higher SINR with reduced computational load compared to the recently developed ones. Numerical examples demonstrate the effectiveness of the proposed method for the robust detection of moving target in MIMO-STAP radar. [ABSTRACT FROM AUTHOR]

In ultra-dense cellular networks (UDNs) with user/control plane(U/C) splitting, frequent handovers in user planes are unavoidable, which seriously degrades the transmission control protocol (TCP) throughput of mobile station (MS). To enhance the TCP throughput in UDNs, this paper proposes an intelligent recommendation-based user plane handover scheme. Firstly, based on intelligent recommendation algorithms, a mobility prediction algorithm called content-based collaborative hybrid filters (CCHF) is proposed to predict the target small base station (SBS). When the MS moves into the cell-edge of the source SBS, it can pre-access the predicted target SBS and set up connections to the predicted target SBS and the source SBS simultaneously. This is the proposed CCHF-dual-handover scheme. With an accurate prediction and a simultaneous connection, CCHF-dual-handover can present enhanced signal to interference and noise ratio (SINR) at cell-edge, reduced handover interruption ratio (HIR), and improved MS’s TCP throughput. Moreover, TCP throughput of CCHF-dual-handover is analyzed to show the impact of various key parameters (such as MS’s velocity and pre-access threshold). Finally, simulations are carried out to evaluate the performance of the proposed CCHF-dual-handover. Given random trajectory, the prediction accuracy using CCHF is increased by more than 100% compared with existing prediction algorithms. Given accurate prediction, the CCHF-dual-handover can improve the TCP throughput by up to 150% compared with that of existing handover schemes. [ABSTRACT FROM AUTHOR]

This paper studies the integration of the newly-emerged intelligent reflecting surface (IRS) technology into non-orthogonal multiple access (NOMA)-based wireless powered communication networks (WPCNs). We consider two WPCNs which communicate with a common hybrid access point (HAP), where there exists two types of devices in each WPCN, namely information receiving device (IRD) and harvest-then-transmit device (HTTD). Downlink communication from the HAP to IRDs, downlink energy transfer (ET) from the HAP to HTTDs, and uplink information transmission (IT) from the HTTDs to the HAP are assisted by two IRSs, one in each WPCN. Under this setup, we propose efficient algorithms to optimize reflection coefficients, beamforming vectors, and resource allocation for the sake of uplink sum-rate maximization, taking into account the minimum rate requirement at the IRDs. Numerical results show the considerable performance gain of the proposed NOMA-based scheme as compared to the conventional orthogonal multiple access (OMA)-based counterpart. [ABSTRACT FROM AUTHOR]

In this paper, we present the case of utilizing interference temperature (IT) as a dynamic quantity rather than as a fixed quantity in an orthogonal frequency division multiple access (OFDMA) based spectrum sharing systems. The fundamental idea here is to reflect the changing capacity demand of primary user (PU) over time in setting the interference power threshold for secondary user (SU). This type of dynamic IT will allow the SU to opportunistically have higher transmit power during relaxed IT period, thereby resulting in higher network capacity. The cognitive radio network (CRN) considered in this paper has an underlay network configuration in which the available spectrum of the PU is accessed concurrently by SU provided that the interference power at the PU receiver from SU is under a certain power threshold. This power threshold is set to maintain and guarantee a certain level of quality of service (QoS) for PU network. Theoretical expressions for outage probability and mean capacity for SU network are derived, and validated with simulation results, and it is observed that utilizing dynamic IT results in high network performance gains as compared to utilizing a fixed IT in cognitive radio system. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel unified framework to protect multi-function wireless systems from jamming attacks. Examples of such multi-function system include joint radar and communication (JRC) systems and simultaneous wireless information and power transfer (SWIPT) systems. By abstracting the system functionalities as a joint optimization problem of multiple queues, we achieve effective resistance against jammers for the multi-functions simultaneously. We incorporate different anti-jamming techniques into one framework. Deception mechanism is adopted to lure the jammer to attack and make its actions more predictable, and ambient backscatter technology is used to leverage the jamming signals. Since conventional Markov decision process (MDP) has only one decision epoch at every time slot, it cannot be used to model the deception strategy which needs two decision epochs to leverage the jamming signals. We therefore formulate the problem using an advanced two-step MDP. After that, a deep reinforcement learning algorithm with a prioritized double deep Q-Learning architecture is proposed to learn optimal strategies in different system states. We show that by jointly considering the multi-functions of the system with potential jamming attacks during design phase, significant improvement can be achieved for both of the system functionalities. [ABSTRACT FROM AUTHOR]

In typical wireless heterogeneous networks (HetNets), users are clustered around known hotspots, e.g., shopping centers or schools, but such a non-uniform distribution of nodes is difficult to analyze. This paper explicitly models this scenario, with macro base stations (MBSs) modeled by a homogeneous Poisson point process (PPP), and millimeter-wave small base stations (mmWave SBSs) and users clustered around the hotspot centers, forming two Poisson cluster processes (PCPs), respectively. Fractional frequency reuse (FFR) and coordinated multi-point transmission (CoMP) are assumed since they help to limit the co-tier interference and enhance the coverage and capacity of the network. We present a distance-based approach for grouping macro user equipments (MUEs) from the cell center (CC) and cell edge (CE) regions for FFR analysis. We first derive some distance distributions, including joint distance distribution from the typical user to the cooperative open-access mmWave SBS and distance distribution from the typical user to the non-cooperative open-access mmWave SBS. We obtain expressions for various performance metrics, including association probability, signal to interference-plus-noise ratio (SINR) coverage probability, and ergodic capacity, under these conditions. Due to the complexity of the exact expressions, we derive novel approximations, using Alzer's lemma, to obtain the lower bounds on coverage and ergodic capacity, which are shown to be accurate through Monte Carlo simulation. Simulation results analyze the effect of different parameters on the network performance to give some guidance for the design of future networks. Numerical optimization of a key parameter, in terms of association probability, coverage probability, and ergodic capacity, is enabled by our analysis. [ABSTRACT FROM AUTHOR]

Due to transmission of train control and dispatch commands, the ultra high reliability is required for railway wireless communication systems (RWCS). However, the quality of service (QoS) of RWCS is affected by external interference and jamming seriously in railway transportation. The external interference and jamming generated from intentional and/or unintentional sources can disturb the transmission of RWCS and be extremely dangerous for the trains’ safety. In this paper, a reconfigurable intelligent surface (RIS) approach is proposed to suppress the interference and jamming in RWCS. By taking the signal-to-interference-plus-noise (SINR) as the QoS metrics, the interference suppression problem with RIS is transformed into a maximizing receiving SINR problem. Two optimum solutions, which one is based on Charnes-Cooper transformation and the other is based on single linear programming, are provided. In order to deploy the RIS in RWCS practically, two low-complexity sub-optimum solutions, which one is to bypass the channel estimation for interference links and the other is to maximize the receiving desired power, are also discussed. The simulations results show that the RIS can be employed in RWCS with considerable anti-interference gain. [ABSTRACT FROM AUTHOR]

This paper presents a non-orthogonal multiple access (NOMA) scheme with group detection for uplink multiple-input multiple-output (MIMO) systems, for which an effective precoder design is developed. In the scheme, users are divided into groups in accordance with their locations for detection at the base station. The inter- and intra-group interferences are mitigated by successive interference cancellation (SIC) and transceivers, respectively. Based on a derived approximate signal-to-interference-plus-noise ratio (SINR) for using zero-forcing detection, an iterative power and beamforming update procedure is developed for obtaining the user precoders. The precoder design effectively mitigates the intra-group-inter-user correlation making the adopted approximate SINR represent the original SINR accurately. The proposed multi-group MIMO-NOMA scheme can work under more practical transmit-receive antenna configurations and is shown to outperform upon existing cluster-based MIMO-NOMA schemes in terms of total transmit power for various system configurations. The impact of SIC residuals on the multi-group MIMO-NOMA scheme is investigated. Feasibility conditions for the design under imperfect SIC based on the fractional cancellation error model are developed. [ABSTRACT FROM AUTHOR]

For large-scale antenna array multiple-input multiple-output (MIMO) systems, a typical solution often put forward for uplink detection consists in applying low-complexity linear receivers such as zero-forcing (ZF) and minimum mean-square error (MMSE) combiners. In this paper, the performance of uplink MMSE detection has been analyzed in the context of a multi-cell multiuser MIMO system. An approximate expression for the signal-to-interference-plus-noise ratio (SINR) is proposed, which is in simple form and becomes exact in the low SNR regime. This approximate SINR applies to systems where the base station (BS) has the statistical information of the out-of-cell interfering signals, and systems where the BS ignores the presence of such interfering signals. This approximate SINR is tight for arbitrary user powers, arbitrary number of antennas at the base station, and arbitrary channel correlation matrix associated with any particular user. Approximate expressions for capacity and bit-error rate/symbol-error rate have also been derived. Particularly, it can be proven that, when the MMSE receiver ignores the presence of out-of-cell interfering signals, the performance gap between ZF and MMSE vanishes in the high SNR regime. [ABSTRACT FROM AUTHOR]

Complex building structures constrain indoor wireless communications. The significant dependence between the indoor wireless network performance and the building structures can be considered as an intrinsic property of a building, which means that the building has to be designed to achieve desirable indoor wireless network performance. The power gain (PG) and the interference gain (IG) have been defined as the figures of merit (FoMs) to evaluate the wireless performance of a building. Employing open space as the benchmark, the PG and the IG respectively quantify the effective change of the intended signal power and the undesired power, i.e., the interference and thermal noise power, received in a targeted user equipment (UE) location due to the presence of the building. In this paper, a tractable approach is proposed to obtain the PG and the IG with a partition-based path gain model. It enables the PG and the IG to capture the impact of both building materials and the building layout on indoor wireless network performance. Numerical results show that the analytical models in closed-form expressions facilitate the wireless performance assessment to a given building computational-efficiently. This work is a critical complement to the initial framework of the building wireless performance (BWP) evaluation. The proposed method can be employed in future wireless-friendly building design. [ABSTRACT FROM AUTHOR]

Cache-enabled small base stations (SBS) are capable of relieving the heavy burden of the backhaul link and reducing the transmission latency. The hit probability depends on the coverage probability and caching placement probabilities. However, the interference in the small-cell networks may significantly degrade the coverage probability. In this paper, for MIMO small-cell networks consisting of SBS and users, where both of them are equipped with multiple antennas, a joint interference alignment (IA) and probabilistic caching (JIA-ProbC) scheme is proposed. Using tools from stochastic geometry, the $K$ -th order Voronoi cells are constructed to form clusters, where $K$ SBSs cooperatively serve users within each of the $K$ -th order Voronoi cells. Then, the IA scheme for MIMO interference channel (IC) is employed to cancel the intra-cluster interference within each $K$ -th order Voronoi cell. By exploiting the advantage of multiples antennas at users, the IA scheme can simultaneously support more users interference-free than both the zero forcing (ZF) based interference cancellation scheme for MISO systems and SISO systems without interference management, as more interference can be canceled. Furthermore, the coverage probability is analytically approximated by the a closed-form expression. Moreover, the optimal caching placement probability is analytically derived. Numerical Simulation results show that the proposed JIA-ProbC can significantly outperform the existing joint ZF and probabilistic caching (JZF-ProbC) scheme for MISO systems and SISO probabilistic caching (SISO-ProbC) scheme as well as the joint IA and most popular caching (JIA-MPC) caching scheme. [ABSTRACT FROM AUTHOR]

Power control is becoming increasingly essential for the fifth-generation (5G) and beyond systems. An example use-case, among others, is the unmanned-aerial-vehicle (UAV) communications where the nearly line-of-sight (LoS) radio channels may result in very low signal-to-interference-plus-noise ratios (SINRs). The authors in (Chiang et al., 2007) proposed to efficiently and reliably solve this kind of non-convex problem via a series of geometrical programmings (GPs) using condensation approximation. However, it is only applicable for a small-scale network with several communication pairs and practically infeasible with more (e.g., tens of) nodes to be jointly optimized. We therefore in this paper aim to provide new insights into this problem. By properly introducing auxiliary variables, the problem is transformed to an equivalent form which is simpler and more intuitive for condensation. A novel condensation method with linear complexity is also proposed based on the form. The enhancements make the GP-based power control feasible for both small- and especially large-scale networks that are common in 5G and beyond. The algorithm is verified via simulations. A preliminary case study of uplink UAV communications also shows the potential of the algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a flexible pilot assignment method to jointly optimize the uplink and downlink data transmission in multi-cell Massive multiple input multiple output (MIMO) systems with correlated Rayleigh fading channels. By utilizing a closed-form expression of the ergodic spectral efficiency (SE) achieved with maximum ratio processing, we formulate an optimization problem for maximizing the minimum weighted sum of the uplink and downlink SEs subject to the transmit powers and pilot assignment sets. This combinatiorial optimization problem is solved by two sequential algorithms: a heuristic pilot assignment is first proposed to obtain a good pilot reuse set and the data power control is then implemented. Numerical results manifest that the proposed algorithm converges fast to a better minimum sum SE per user than the algorithms in previous works. [ABSTRACT FROM AUTHOR]

Terahertz (THz) wireless technology is envisioned to enable terabit-per-second (Tbps) and secure transmissions in sixth-generation (6G) communication networks and has attracted attention from academia and industry in recent years. Because the transmission range of THz radios is restricted compared to that of microwave radios, frequency reuses in the THz band become much more flexible and even possible among transceiver pairs in close proximity. However, without appropriate spatial arrangement and coordination, the frequency reuse in the THz band can also lead to severe co-channel interference and result in a low signal-to-interference-plus-noise ratio (SINR) or a signal-to-interference ratio (SIR), which finally degrades signal detection and network reliability. To thoroughly study the co-channel interference in the THz band, we model the co-channel interference by the compound channel model and analyze it in detail. The adopted channel model captures the key features of THz communication, such as, spreading loss, molecular absorption loss, and dynamic shadowing, which is much different and complicated than those used in the low-frequency band. The resulted SINR and SIR are investigated by approximating the sum of co-channel interference as a gamma distribution. The generalized analytical results are also reduced to specialized forms for two special cases, i.e., the single-interferer case and the case of multiple independent and identically distributed (i.i.d.) interferers. Due to the generalized nature of the THz interference model constructed in this paper, the results play a meaningful role in practical implementation and can be easily extended to advanced performance analyses for THz communication systems. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is an enabling and key wireless technology for the next generation of mobile communications. Generally, previous works focus on the performance in NOMA networks, based on some assumptions. For instance, the number of users in a NOMA group, is two-category: 1) only two users; 2) any number of users without restriction. And just a certain factor of channel gain, e.g., the propagation path loss or the small scale fading, is subjectively considered to be dominant. Besides, there is lack of the closed-form expression for the probability density function (PDF) of ordered channel gain. In this paper, we investigate a downlink cellular NOMA network with the directional beamforming and the upper limit for user number (ULFUN) in a NOMA group. Meanwhile, the path loss and the Rayleigh fading are taken into account as a whole for ordering channel gains. Based on the derived closed-form PDF of ordered channel gain, we analyze the performance for an arbitrary user in the network and derive closed-form expressions for the outage probability, the approximate meta distribution of conditional success probability (CSP) and the ergodic data rate. The provided simulations demonstrate that the proposed analytical results are accurate and reasonable. Moreover, it illustrates that the existence of ULFUN can have a positive impact on the performance gain in low SINR environments, while in terms of the outage probability, ULFUN would become a non-negligible and negative factor in the improvement of performance for high SINR environments. [ABSTRACT FROM AUTHOR]

This paper considers an intelligent reflecting surface (IRS)-aided simultaneous wireless information and power transfer (SWIPT) network, where multiple users decode data and harvest energy from the transmitted signal of a transmitter. The proposed design framework exploits the cost-effective IRS to establish favorable communication environment to improve the fair energy efficient. In particular, we study the max-min energy efficiency (EE) of the system by jointly designing the transmit information and energy beamforming at the base station (BS), phase shifts at the IRS, as well as the power splitting (PS) ratio at all users subject to the minimum rate, minimum harvested energy, and transmit power constraints. The formulated problem is non-convex and thus challenging to be solved. We propose two algorithms namely penalty-based and inner approximation (IA)-based to handle the non-convexity of the optimization problem. As such, we divide the original problem into two sub-problems and apply the alternating optimization (AO) algorithm for both proposed algorithms to handle it iteratively. In particular, in the penalty-based algorithm for the first sub-problem, the semi-definite relaxation (SDR) technique, difference of convex functions (DC) programming, majorization-minimization (MM) approach, and fractional programming theory are exploited to transform the non-convex optimization problem into a convex form that can be addressed efficiently. For the second sub-problem, a penalty-based approach is proposed to handle the optimization on the phase shifts introduced by the IRS with the proposed algorithms. For the IA-based method, we jointly optimize beamforming vectors and phase shifts while the PS ratio is solved optimally in the first sub-problem. Simulation results verify the effectiveness of the IRS, which can significantly improve the system EE as compared to conventional benchmark schemes and also unveil a trade-off between convergence and performance gain for the two proposed algorithms. [ABSTRACT FROM AUTHOR]

This paper proposes a stochastic-robust constructive interference (CI) precoding scheme for downlink multi-user MISO systems, assuming that channel state information (CSI) at the transmitter side (CSIT) is contaminated by Gaussian-distributed uncertainties. Our objective is to minimize the total transmit power under users’ quality-of-service constraints: formulating CI at each user with high probabilities for a given target signal-to-noise ratio (SINR). We first analyze the probability of CI under imperfect CSIT. A series of approximations are then developed, transforming the intractable stochastic CI constraints into determined convex constraints. The non-convex stochastic-robust CI power minimization (CIPM) problem is then converted into second-order cone programming. We show that we could create tightened or relaxed approximations by changing the parameters, enabling us to find upper-bounds and lower-bounds for the original stochastic CIPM problem. The best parameter values corresponding to the tightest upper and lower bounds are also discussed and obtained. Simulation results show that the proposed methods reasonably approximate the stochastic CIPM problem. Using the given parameter values, it can guarantee the required probability of CI for each user under acceptable channel uncertainties and outperform the existing robust CI precoding in terms of both transmit power and feasibility rate. The small gap between the upper and lower bounds also shows that the proposed method does not cause too much performance loss. [ABSTRACT FROM AUTHOR]

This paper investigates the benefits of incorporating full-duplex (FD) into an underlaid device-to-device (D2D) cellular network via centralized and distributed power control mechanisms. In the considered system, D2D users operate in an FD mode under the adverse effect of realistic residual self-interference, and their locations are modeled by a homogeneous spatial Poisson point process. By first considering a centralized power control scheme, we first formulate an optimization problem that maximizes the D2D link sum-rate under the constraint on minimum target signal-to-interference-plus-noise ratio (SINR) at each user. Since the problem is nonconvex, we propose a difference of convex based method to transform the problem into a sequence of convex subproblems which can be solved efficiently. The obtained solutions help to calculate the coverage probability of both cellular and D2D links, showing that a very high coverage probability of cellular link can be achieved while successfully supporting a large number of active D2D links. In the second part of the paper, we consider a distributed power control scheme where only the local channel state information of direct link between respective D2D users is needed. By utilizing the tools of stochastic geometry, we derive closed-form approximations of coverage probabilities for both cellular and D2D links. Specifically, we apply Laplace transforms and novel approximations that accurately approximate the expected values of fractional and exponential functions of random variables to obtain the distribution functions of SINRs at the base-station and D2D users in a closed form. By further taking the average over the distributions of cellular and D2D link distances, we then arrive at the closed-form approximations of cellular and D2D coverage probabilities. In addition, based on the approximation of D2D link coverage probability, an analytical expression for the D2D link sum-rate is also obtained, and it can be effectively calculated. [ABSTRACT FROM AUTHOR]

This paper raises the question of whether the secondary user can attain a nonzero achievable rate without causing capacity loss at the primary user, even when it is utilizing the channel in cognitive radio networks (CRNs). It is assumed that secondary nodes are aware of the channel state information (CSI) of primary nodes and of how the primary nodes operate, whereas the primary nodes operate with no prior knowledge about the secondary nodes. We first propose a full-duplex relaying protocol for the cognitive radio (CR) network with a single relay node shared by both the primary and the secondary networks. In this case, the shared relay is assumed to have full CSI of the primary nodes and to know how the primary and secondary nodes operate. The proposed relaying protocol enables the secondary network to achieve nonzero rates without causing capacity loss at the primary network in a certain channel condition. Then, we also propose three half-duplex relaying protocols for the CR network with two relays, each of which is dedicated to the primary or the secondary network, respectively. It is shown that appropriate combinations of the proposed three half-duplex relaying protocols make it always possible for the secondary network to achieve nonzero rates without causing capacity loss at the primary network. Achievable rates of the proposed full- and half-duplex relaying protocols are evaluated through extensive computer simulations. Simulation results show that the proposed relaying protocols provide nonzero achievable rates of the secondary network over a wide range of signal-to-noise ratios (SNRs). [ABSTRACT FROM PUBLISHER]

Whether the current IEEE 802.11p communication system meets the stringent quality of service (QoS) requirements for safety applications or not is still not very clear. Signal-to-interference-plus-noise ratio (SINR) distribution plays a primary role in quantifying the QoS as well as link capacity of IEEE 802.11p in one-dimensional (1-D) highway and two-dimensional (2-D) intersection road. Most of the analytical models based on stochastic geometry assumed ALOHA access to analyze the SINR distribution, while few of the works developed the stochastic geometry based model considering CSMA access but derived the SINR distribution utilizing statistical estimator. On the other hand, the current interference based probability analytic model for the SINR distribution limit the 1-D extension to 2-D, due to the very high numerical computational complexity at 2-D. In this paper, we propose an analytic model under more general non-homogeneous Poisson process (NHPP) node distribution, more general channel fading model (Nakagami) with path loss, and noise, for the study of QoS and capacity of VANET for BSM based safety applications in both 1-D highway and 2-D intersection road. The proposed model derives QoS and capacity of VANET BSM broadcast through evaluation of SINR distribution using probability theory and ordered statistics, which has much lower computational complexity compared with the unordered statistic model. The proposed model is validated by NS2 simulation and extended to the derivation of other QoS metrics such as packet reception probability, packet reception ratio, and broadcast link capacity, etc. The performance comparisons between 1-D and 2-D are implemented, and the QoS sensitivity analyses regarding the extension to multi-intersection as well as enlarging interference range are discussed. [ABSTRACT FROM AUTHOR]

In this paper, we present an analytical model to characterize the average queuing delay for non-orthogonal multiple access (NOMA) downlink system by taking the outage event into account such that the user fails either decoding its own signal or performing SIC for the signals of other users at the receiver when the SINR is lower than a predefined outage threshold. The departure process of the queuing model is characterized by obtaining the first and second moment statistics of the service time that depends on the resource allocation strategy, the packet size and channel distributions. The proposed model is utilized to obtain the optimum power allocation that minimizes the maximum of the average queuing delay (MAQD) for a two-user network scenario. The Monte Carlo simulation experiments are performed to numerically validate the model by providing MAQD results for both NOMA and orthogonal multiple access (OMA) schemes. The results demonstrate that the NOMA achieves lower latency for low SINR outage thresholds while its performance is degraded faster than OMA as the SINR outage threshold increases such that OMA outperforms NOMA beyond a certain threshold. Another important result is that the latency performance of NOMA is significantly degraded when the 5G NR frame types having wider bandwidth are utilized. The results provide powerful insights for queuing delay analysis of 5G services. [ABSTRACT FROM AUTHOR]

The ultra dense deployment of small cells is considered a key technology to achieve the requested capacity in future cellular networks. However, the interference pattern becomes more unpredictable and challenging in these networks. Therefore, a suitable trade-off between spectrum spatial reuse and interference level has to be pursued to achieve good performance in terms of provided throughput. This paper proposes a new method to maximize the achievable throughput of an UDN with a suitable level of spatial spectrum reuse. In particular, the focus is on the small cells tier where the available spectrum is divided into sub-bands and each cell can use some of these to communicate with its associated users. The goal is to find the sub-bands allocation among cells that maximizes the system throughput. However, to limit complexity and signaling overhead that could result unaffordable in an UDN, a new metric to approximate the cell throughput to be optimized is defined. Moreover, the newly defined problem is solved using the Gibbs Sampling approach. The method effectiveness is proven by comparing the achieved results with those of the maximization of the effective system throughput and the optimal solution. [ABSTRACT FROM AUTHOR]

Code division multiplexing (CDM)-based random access, wherein a set of sequences is reserved for random access and a remote station transmits a random access packet using a sequence randomly selected from this set, is employed in numerous practical wireless systems. If multiple remote stations simultaneously transmit random access packets using the same sequence, the performance degrades owing to sequence collision. In addition, the performance is degraded because of interference if multiple remote stations simultaneously transmit random access packets using different sequences. Therefore, the performance of CDM-based random access is dependent on both sequence collision and interference. There have been no previous studies on analyzing the performance of CDM-based random access considering both sequence collision and interference. In this paper, the throughput of CDM-based random access is investigated considering both sequence collision and interference based on a signal-to-interference-plus-noise ratio (SINR) capture model. Analyses and numerical simulations are performed to compare the throughputs of several random access schemes, including conventional and channel-adaptive random access. The results show that channel-adaptive random access can achieve significantly higher throughput than that achieved by conventional random access. Moreover, the results demonstrate that it is possible to analyze the trade-off between the throughput and implementation complexity with the increased the number of sequences. [ABSTRACT FROM AUTHOR]

In multi-user downlink small cell networks, cooperative resource allocation (RA) within a small cell cluster is a key technique to enhance network capacity. However, capacity-maximizing RA in frequency-selective fading channels requires global channel state information (CSI) of users within a small cell cluster, which makes it infeasible in practical networks with limited direct link capacity. To circumvent this global CSI assumption, most of the existing studies on RA have been based on several CSI assumptions such as local CSI and local CSI at the transmitters (CSIT). Nevertheless, cost functions with local CSI or local CSIT in the literature rely on heuristic formulations, because the sum-rate cannot be computed if without global CSI. In this paper, we propose a deep reinforcement learning-based RA algorithm to maximize the sum-rate for any given limited information on instantaneous CSI or sum-rate at the previous period. The proposed scheme is not restricted to certain CSI assumptions, but attempts to find the best RA for any given information such as quantized local CSI and quantized local CSIT; thus, it is applicable to any given direct link capacity. The proposed algorithm is self-adaptive in time-varying channels, since it is not divided into training and test phases. We modify the target neural network (TNN) scheme to enhance the sum-rate and the convergence speed. Numerical simulations confirm that: i) the proposed algorithm outperforms the conventional algorithms even under the same CSI assumption such as local CSI and local CSIT; ii) a flexible trade-off between the amount of CSI and the sum-rate is realizable in practical systems. [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, we study the problem of utility maximization in the uplink of vehicle-to-infrastructure communication systems. The studied scenarios consider four practical aspects of mobile radio communication links: i) Interference between adjacent channels, ii) interference between roadside units along the way, iii) fast and slow channel fadings, and iv) Doppler shift effects. We present first the system model for the IEEE 802.11p standard, which considers a communication network between vehicles and roadside infrastructure. Next, we formulate the problem of utility maximization in the network, and propose a distributed optimization scheme. This distributed scheme is based on a two-loop feedback configuration, where an outer-loop establishes the optimal signal to interference-noise ratio (SINR) that maximizes the utility function per vehicle and defines a quality-of-service objective. Meanwhile, inner-control loops adjust the transmission power to achieve this optimal SINR reference in each vehicle node regardless of interference, time-varying channel profiles and network latency. The computation complexity of the distributed utility maximization scheme is analyzed for each feedback loop. Simulation results indicate that the proposed scheme reaches the objective SINRs that maximize utility and improve energy efficiency in the network with a low time cost. The results also show that the maximum utility is consistently achieved for different propagation scenarios inside the vehicular communication network. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) has been widely considered as a promising technology in the next generation wireless communication systems. Various beam-based directional transmission techniques have been proposed to compensate high pathloss caused by mmWave properties. However, mobility effect of users potentially causes severe inter-beam interferences, which has not been fully-investigated in existing studies. In this paper, we have analyzed different types of mobility-aware beam interference models. Additionally, the theoretical SINR is derived based on channel statistics and the trajectories of users. We propose a mobility-aware subband and beam resource allocation (MSBA) scheme for the mmWave subband-beam massive multi-input multi-output (SB-MMIMO) systems. The proposed MSBA benefits from reduced computation complexity for maximizing system throughput constrained by quality-of-service (QoS) demands of users. The first phase of MSBA scheme is responsible for resource block assignment; while the second phase allocates beamwidth and beam directions according to the analytical derivations. Numerical results show that the proposed MSBA scheme can effectively achieve the highest system throughput and the lowest complexity compared to existing schemes in open literatures. [ABSTRACT FROM AUTHOR]

This correspondence paper studies the impact of nonidentically distributed channel estimation error on performance of a scheduled space-time block coding with mean-value power allocation in cognitive-radio multiple-input multiple-output system. Using the derived probability density function, the exact closed-form expressions of the proposed system for outage probability, ergodic capacity, and symbol-error rate (SER) with both $\rm M$ -ary quadrature amplitude modulation and phase shift keying modulation are derived. Using asymptotic analysis, this paper quantifies the diversity order for both outage probability and SER in the presence of nonidentically distributed error. From the analysis results, this paper shows that the diversity order is enhanced by the multiuser diversity as the number of user terminals increases regardless of outage probability and SER, while the spatial diversity is eliminated. [ABSTRACT FROM AUTHOR]

In this paper, the throughput maximization of millimeter-wave (mm-Wave) ultradense networks (UDN) using dynamic spectrum sharing (DSS) is considered. Most of the existing works only allow temporal-domain access and admit at most one user at each time slot, resulting in significant underutilization of spectrum resource, which will be less attractive to mm-wave UDN applications. A generalized temporal-spatial sharing scheme is proposed in this paper for UDN by exploiting the location information of incumbent devices, where multiple users are allowed to access each channel simultaneously via spatial separations. For distributed applications, the global information exchange among secondary users (SU) tends to be impractical, given the unaffordable signaling overhead and latency. Thus, a noncooperative game with fine-grained two-dimensional reuse is formulated, which leads to a more efficient access strategy. It is then proved to be an ordinary potential game (OPG), which guarantees the existence of the strategy Nash equilibrium (NE). Finally, an improved decentralized reinforcement learning algorithm is designed, with which SUs can learn from wireless environments and adapt toward an NE point, relying on the individual observation and the historical action reward (rather than the global information exchanging). The convergence efficiency of the new scheme is also rigorously proved. Numerical simulations are provided to validate the performances of the proposed schemes. [ABSTRACT FROM AUTHOR]

The next generation of mobile communication has progressed toward the deployment of small cells to meet the growing demands of increased capacity and QoS as compared to the conventional method, where all the computations were performed by the base station (BS)'s only. To reduce burden at the BS side, small cells deployment has been stressed upon, thus resulting in the formation of ultradense networks (UDN) having high concentration of small cells (e.g., picocell, femtocell, hotspots) and as a counter effect of which distance between two small cells is reduced to a greater extent. With such a close association of cells in UDN, the probability of frequent handovers also increases abruptly. As a result, the chances for attacker to spoof the bandwidth also increases many folds. In this paper, we have analyzed SNR, signal-to-interference-plus-noise ratio, and channel quality information channel parameters, such that the position of moving users at which handover is initiated in picocell deployment of UDN can be traced out successfully or region where the probability of attackers presence is high. Through this paper, we have tried to introduce the attacking scenario for the high mobility conditions in UDN. [ABSTRACT FROM AUTHOR]

Vector perturbation (VP) is a nonlinear precoding technique that achieves near-capacity performance in multiuser multiple-input multiple-output systems at the expense of large complexity due to the search for the optimum perturbation vector. In this paper, we present the hybrid Tomlinson–Harashima VP (TH-VP) algorithm, a novel zero-forcing precoding scheme, which combines TH precoding to remove interuser interference, and VP precoding to equalize each user's multiple spatial streams. We show that the two nonlinear techniques can be integrated in a single optimization and that the proposed algorithm has lower computational requirements than any other. The performance of TH-VP is analyzed and simulation results show that TH-VP outperforms conventional zero-forcing VP and approaches the performance of dirty paper coding. [ABSTRACT FROM AUTHOR]