Search

The explosive growth of Internet-of-Things (IoT) applications such as smart cities and Industry 4.0 have led to drastic increase in demand for wireless bandwidth, hence motivating the rapid development of new techniques for enhancing spectrum utilization needed by new generation wireless communication technologies. Among others, dynamic spectrum access (DSA) is one of the most widely accepted approaches. In this paper, as an enhancement of existing works, we take into consideration of inter-node collaborations in a dynamic spectrum environment. Typically, in such distributed circumstances, intelligent dynamic spectrum access almost invariably relies on self-learning to achieve dynamic spectrum access improvement. Whereas, this paper proposes a DSA scheme based on deep reinforcement learning to enhance spectrum and access efficiency. Unlike traditional Q-learning-based DSA, we introduce the following to enhance the spectrum efficiency in dynamic IoT spectrum environments. First, deep double Q-learning is adopted to perform local self-spectrum-learning for IoT terminals in order to achieve better dynamic access accuracy. Second, to accelerate learning convergence, federated learning (FL) in edge nodes is used to improve the self-learning. Third, multiple secondary users, who do not interfere with each other and have similar operation condition, are clustered for federated learning to enhance the efficiency of deep reinforcement learning. Comparing with the traditional distributed DSA with deep learning, the proposed scheme has faster access convergence speed due to the characteristic of global optimization for federated learning. Based on this, a framework of federated deep reinforcement learning (FDRL) for DSA is proposed. Furthermore, this scheme preserves privacy of IoT users in that FDRL only requires model parameters to be uploaded to edge servers. Simulations are performed to show the effectiveness of theproposed FDRL-based DSA framework. [ABSTRACT FROM AUTHOR]

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]

Fixed Satellite Services (FSS) used to be alone at the C-Band spectrum in most countries. Since the deployment of 5G in many countries (i.e., 3.3–3.6 GHz), FSS is not the exclusive system in the C-Band anymore. In order to minimize the detrimental interference for the FSS to allowable levels, regional exclusion zones of maximum radiated power in 5G base stations (BS) are proposed and evaluated. In this paper, a measurement campaign has been carried out, and an analysis of the interference has been studied. A filtering model, namely Filter to Remove Broadband Interference 5G (FIREBRING), is proposed and analyzed concerning the carrier-to-noise ratio (C/N). Moreover, this paper focuses on the evaluation of the 5G interference into the FSS. The proposed solution deployed an Low-Noise Block (LNB) with a band frequency of 3.7 to 4.2 GHz to test the satellite down-conversion signal at the receiver. The paper offered a complete analysis of the 5G signal, taking into account the implications of out-of-band emissions, potentially LNB saturation into FSS receiver, and the repercussions of the deployment of the 5G BS active antenna systems. With the LNB and down-converter in place, it can be found that the signal interference between 1.450 GHz and 1.550 GHz, is nearly 18 dB. [ABSTRACT FROM AUTHOR]

In this paper, we explore the different per-user bandwidths available for each tier of heterogeneous networks (HetNets) and the corresponding downlink range expansion (RE, a key measure to boost small cell association). Based on the practical case of tier-specific path loss exponents, we derive the local delay of HetNets under the random discontinuous transmission scheme (DTX, employed to manage the interference and reduce energy consumption). Using such a new expression for local delay, we then analyze the corresponding energy efficiency (EE). These delay and EE expressions reveal that there exists an optimal value for both the RE bias factor and for the DTX mute probability. A closed-form optimum solution for the RE bias factor is also derived for the low-rate regime. [ABSTRACT FROM AUTHOR]

The heterogeneous fog radio access networks (Fog-RAN), the integration of fog computing, and traditional heterogeneous radio access networks can be implemented through the next-generation wireless communication networks. However, most of the solutions are limited to the spectrum efficiency optimization, and cross-tier interference existing in the fog access points (F-APs) could affect the network performance seriously. In this paper, the user association, resource allocation (including bandwidth and power), and caching deployment are investigated in the heterogeneous Fog-RAN to consider energy efficiency and cross-tier interference mitigation. Specifically, the user association, resource allocation, and caching strategy are formulated as a non-convex optimization problem and then transformed into a convex problem, which can be solved by a proposed algorithm based on the concept of the alternating direction method of multipliers (ADMM). Then an ADMM-based algorithm is proposed to enhance the energy efficiency of the Fog-RAN. Compared with the current solutions, simulation results illustrate the proposed algorithm’s convergence and effectiveness. [ABSTRACT FROM AUTHOR]

In this paper, a new mathematical approach for the analysis and optimization of cellular-enabled low-energy mobile devices with simultaneous wireless information and power transfer capabilities is introduced. The proposed methodology relies on modeling the locations of the base stations as points of a spatial Poisson point process, and it leverages stochastic geometry for system-level analysis. The tradeoffs emerging from simultaneous wireless information and power transfer transmission are characterized through the concept of “feasibility regions” and are quantified through the joint cumulative distribution function of harvested power and rate. To gain insight on the achievable performance, in addition, an upper bound is proposed, and its accuracy is discussed. The system model encompasses a realistic channel model that accounts for line-of-sight (LOS) and non-LOS (NLOS) links, different cell association criteria, practical receivers based on time switching and power splitting schemes, and directional beamforming. The analysis shows that optimal values for the time switching and power splitting ratios exist and that directional beamforming and network densification are capable of enhancing system performance. More specifically, high directional antennas lead cellular networks to operate in the noise-limited regime, which is proved to provide optimal performance, and because of the existence of LOS and NLOS links, an optimal deployment density for the base stations is proven to exist for typical system setups. [ABSTRACT FROM PUBLISHER]

To efficiently trade off system sum rate and link fairness, power allocation in wireless spectrum-sharing networks often concentrates upon proportional fairness. The corresponding problem has been proved to be convex for a single tone but NP-hard for more than two tones. However, in the two-tone case, the complexity of the problem for achieving proportional fairness has not been addressed yet. In this paper, we prove that the issue of proportional-fairness optimization for the two-tone situation is NP-hard by reducing the problem of finding the maximum independent set in an undirected graph to it. Moreover, a computationally efficient algorithm is proposed to provide an efficient suboptimal solution. Simulation results are presented to illustrate the effectiveness of our proposal. [ABSTRACT FROM PUBLISHER]

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]

In heterogeneous multi-cell networks (HetNets), inter-and intra-cell interference are critical issues impairing the performance. In this paper, the frequency-hopping (FH) technique based on an attractive FH sequence (FHS) set with two-level Hamming correlations is exploited in such networks. Motivating from the idea of no-and low-hit-zone FHS sets, a construction algorithm of the new FHS set is proposed by utilizing the interleaving technique. Then, the performance metric of such FHS set in terms of Hamming correlation properties are derived, which are verified by an example. Compared with classic FHS sets (patterns), the proposed FHS set offers a zero Hamming cross-correlation for intra-cell users, and a low Hamming cross-correlation for inter-cell users (i.e., multi-level quality-of-services). The intra-and inter-interference in multi-cell HetNets can be significantly reduced by the proposed sequence-based FH technique. [ABSTRACT FROM AUTHOR]

The level crossing rate (LCR) is an important second-order statistical quantity that characterizes the rate of occurrence of fading time intervals. In this paper, we investigate the LCR of multiantenna flat-fading channels in the presence of additive white Gaussian noise and cochannel interferers with unequal received powers and Doppler shifts. We first present a unified approach to derive the exact LCR of the signal-to-interference-noise ratio at a receiver, where maximum ratio combining is deployed over spatially correlated or uncorrelated systems. Through the exact LCR derivation, we identify an accurate approach to obtain a simplified approximate LCR expression in the spatially uncorrelated system case. Benefits of the LCR expressions derived in the paper are demonstrated in two important applications: 1) the packet error rate is evaluated through the finite-state Markov channel model; and 2) the optimum packet length to maximize the throughput of the system with the stop-and-wait automatic repeat request protocol is derived. The analytical results are validated by simulations. [ABSTRACT FROM PUBLISHER]

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]

Mobile edge computing (MEC) has attracted great interests as a promising approach to augment computational capabilities of mobile devices. An important issue in the MEC paradigm is computation offloading. In this paper, we propose an integrated framework for computation offloading and interference management in wireless cellular networks with MEC. In this integrated framework, we formulate the computation offloading decision, physical resource block (PRB) allocation, and MEC computation resource allocation as optimization problems. The MEC server makes the offloading decision according to the local computation overhead estimated by all user equipments (UEs) and the offloading overhead estimated by the MEC server itself. Then, the MEC server performs the PRB allocation using the graph coloring method. The outcomes of the offloading decision and PRB allocation are then used to distribute the computation resource of the MEC server to the UEs. Simulation results are presented to show the effectiveness of the proposed scheme with different system parameters. [ABSTRACT FROM AUTHOR]

This paper proposes feasible and satisfactory system design parameters to mitigate the impact of interference on real-time high-definition video streaming in infrastructure-to-vehicle (I2V) telematic platforms utilizing 60-GHz radiation and the corresponding IEEE 802.11ad baseband. The analysis captures the impact of interference on the 60-GHz I2V vehicle (IV), which is caused by multiple interference sources through the 60-GHz wireless transmissions from nearby I2V base stations (IBSs) to their associated IVs. The impact of the interference on the quality of main 1080p at 30-frame/s (30 1080p frames/s) and 1080p at 60-frame/s (60 1080p frames/s) streaming is analyzed and estimated for various simulation settings. [ABSTRACT FROM PUBLISHER]

To support a tremendous amount of traffic demands via wireless access in 2020 and beyond, limited bandwidth of the licensed bands has been a major obstacle to boosting further the capacity of wireless services. To fundamentally break through this predicament, an emerging technology known as heterogeneous carrier communications has been launched into standardization in the form of licensed-assisted access (LAA) to the unlicensed bands. Integrating the heterogeneous cloud radio access networks and carrier aggregation, and although LAA-empowered cellular networks gain wider bandwidth from the unlicensed bands, communications may suffer from intersystem interference. To avoid interference, listen-before-talk has been designated as a mandatory function; however, it leads to significant challenges of the hidden-terminal problem. To address this open issue in LAA, in this paper, we consequently propose a resource-optimal scheme using a minimum amount of replicated radio resources to achieve the most essential latency guarantees for real-time applications. To further support non-real-time applications, a new resource control as well as the mathematical architecture inspired by so-called political communications is proposed to further maximize the throughput of packet delivery. Our scheme not only optimizes resource utilization in time and spatial domains but also suggests optimum energy efficiency and computation efficiency, to successfully deploy cellular networks on the unlicensed bands. [ABSTRACT FROM PUBLISHER]

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]

Modern models for public safety networks (PSN) utilize commercial user equipment (UE) and exclusively rely on cellular architecture. This paper introduces a heterogeneous PSN mechanism where multiple wireless protocols are used to establish resilient communications. Specifically, each UE acts as a learning automaton and using a reinforcement-learning approach selects the most appropriate operation protocol, in terms of environment/topology needs, protocol specifications, and PSN battery-life extension. In addition, we follow a UE coalition formation approach, using a Chinese restaurant process that considers UEs’ communication interest, physical distance, and energy availability. Finally, each UE's optimal transmission power is obtained using the formulation of a utility-based power control problem as a non-cooperative, distributed game among UEs, which converges to a unique Nash equilibrium. The performance of the proposed approach is evaluated using modeling and simulation under several scenarios; also, its superiority is demonstrated. [ABSTRACT FROM AUTHOR]

The small cell network (SCN) is one of the emerging technologies for the next generation wireless systems. It can provide lots of advantages, such as enlargement of cell coverage, boost of peak data rate, improvement of link quality, flexibility of deployment, etc. In SCN, a specific scenario, where the density of small cell base stations (SBS) is much higher than that of user equipments (UE), becomes popular topic recently. Because of the high density of SBSs, it can offer diversity of SBS selection and, hence, improve the system performance. Besides, under this condition, each UE can be served by multiple SBSs, which also motivates the possibility of using coordinated communication schemes such as coordinated multi-point (CoMP) transmissions. Therefore, in this paper, we investigate the SCN with highly dense deployment of SBSs, and suggest a CoMP transmission structure to improve the transmission performance. In addition, for well performing CoMP transmissions, we also propose CoMP set formation method, which selects SBSs to form CoMP set according to the designed metric. We conduct simulations to validate the performance of the SCN with proposed CoMP method. The simulation results show that the proposed CoMP method can indeed improve the dense SCN corresponding to the designed metric. Specifically, the proposed CoMP method can significantly improve sum rate and prompt most of the transmissions to reach the quality of service requirement of the UEs. This method is flexible and easy to be adopted in many kinds of systems, including single-operator or inter-operator ones. [ABSTRACT FROM AUTHOR]

This paper analyzes statistical properties of the Poisson line Cox point process useful in the modeling of vehicular networks. The point process is created by a two-stage construction: a Poisson line process to model road infrastructure and independent Poisson point processes, conditionally on the Poisson lines, to model vehicles on the roads. We derive basic properties of the point process, including the general quadratic position of the points, the nearest distance distribution, the Laplace functional, the densities of facets of the Cox–Voronoi tessellation, and the asymptotic behavior of the typical Voronoi cell under vehicular densification. These properties are closely linked to features that are important in vehicular networks. [ABSTRACT FROM AUTHOR]

Recent advances in loop interference cancelation techniques enable full-duplex relaying (FDR) systems, which transmit and receive simultaneously in the same band with high spectrum efficiency. Meanwhile, wireless virtualization has attracted a lot of attention from both academia and industry because it can provide more flexibility, diversity, and other benefits in the process of wireless network design, construction, operation, and management. In this paper, we introduce the idea of wireless virtualization into FDR cellular networks. Then, the problem of energy-aware virtual resource management is formulated as a three-stage Stackelberg game. The subgame perfect equilibrium for each stage is analyzed. In addition, the interplays of the three-stage game are discussed, and an iterative algorithm is proposed to obtain the Stackelberg equilibrium solution. Simulation results are presented to show the effectiveness of the proposed scheme. [ABSTRACT FROM PUBLISHER]

Deep neural networks (DNNs) have been widely applied for classification tasks in wireless communications such as link scheduling, user association and base station (BS) muting. When training a DNN using datasets with highly-skewed class distribution where most data belong to a few majority classes, learning performance for minority classes will degrade since the imbalanced data forces the training process to be biased towards the majority classes. In many wireless problems, multiple decisions for classification are made jointly, say deciding which BSs in a network should be muted to avoid interference. In this paper, we employ DNN to learn an optimal predictive interference coordination policy, and strive to avoid biased learning in such a multi-label multi-class classification problem. The major contribution is proposing a training method to encourage fairness among classes by minimizing the maximal cost of decisions among classes, which is converted into a problem to optimize the weighting factors on the training cost of each class. We provide a gradient descent algorithm to optimize the weighting factors and the model parameters of the DNN by alternative updates. Simulation results show that the training method can improve the learning performance for the minority class and can achieve higher network utility than existing training methods. [ABSTRACT FROM AUTHOR]

Cooperative communication can significantly enhance the efficient utilization of spectrum in wireless networks. The performance of wireless cooperative networks depends on careful medium access control (MAC) and resource allocation such as relay selection and cooperative link scheduling policy for interference management. Most of the previous centralized works rely on precise instantaneous channel state information (CSI). In this paper, considering the impact of multirelay link interference on relay selection and dynamic spectrum sharing, we propose a fully distributed relay MAC scheme for wireless cooperative networks based on a Stackelberg game framework with only one-hop local CSI, where source nodes that have their own information to send act as leader users and where the others act as follower users. In this scenario, each relay node prices its spectrum resource to the corresponding source node to maximize its revenue. In addition, the proposed scheme helps not only source nodes to find relay nodes by channel gains and obtain an optimal system performance but relay nodes to maximize their revenue by asking a suitable resource price as well. The interactions between the sources and relays iteratively lead to a Stackelberg equilibrium, in which the cooperation system achieves high throughput and low transmission delay. Simulation results are presented to show the effectiveness of the proposed approach. [ABSTRACT FROM PUBLISHER]

In recent years, wearable devices and wireless body area networks have gained momentum as a means to monitor people's behavior and simplify their interaction with the surrounding environment, thus representing a key element of the body-to-body networking (BBN) paradigm. Within this paradigm, several transmission technologies, such as 802.11 and 802.15.4, that share the same unlicensed band (namely, the industrial, scientific, and medical band) coexist, dramatically increasing the level of interference and, in turn, negatively affecting network performance. In this paper, we analyze the cross-technology interference (CTI) caused by the utilization of different transmission technologies that share the same radio spectrum. We formulate an optimization model that considers internal interference, as well as CTI to mitigate the overall level of interference within the system, explicitly taking into account node mobility. We further develop three heuristic approaches to efficiently solve the interference mitigation problem in large-scale network scenarios. Finally, we propose a protocol to compute the solution that minimizes CTI in a distributed fashion. Numerical results show that the proposed heuristics represent efficient and practical alternatives to the optimal solution for solving the CTI mitigation (CTIM) problem in large-scale BBN scenarios. [ABSTRACT FROM PUBLISHER]

We consider the uplink transmission in multiuser wireless systems with multiple single-antenna transmitting users and a multiantenna receiver. We address two problems in this paper. The first problem is user admission, i.e., given a large number of users, how to admit the maximum number of users that can simultaneously satisfy quality of service (QoS) and power constraints. The second problem is how to distribute the data among the users when they are allowed to share data before transmission. The aim is to minimize the total data exchange cost. Such a problem is called user clustering. We formulate those problems into sparsity-maximization problems, which are NP-hard. Inspired by compressive sensing techniques, we propose a common framework to tackle those problems by first applying the \ell1 -norm relaxation and then solving them with convex optimization methods. Simulations show that the proposed algorithms achieve excellent performance. For user admission, the numbers of admitted users by the proposed algorithms are close to the optimum numbers of admitted users obtained by exhaustive search (ES) . For user clustering, the total data exchange cost is reduced by more than 10% after only a few iterations. When the QoS requirement is low, the user data exchange can be avoided using the proposed method, which achieves the optimum result obtained by ES. [ABSTRACT FROM PUBLISHER]

Spectrum scarcity and intercell interference (ICI) are two fundamental limiting factors in wireless cellular systems. Soft frequency reuse (SFR) has been proposed as an effective way to manage the spectrum and reduce ICI in cellular systems. In a static SFR scheme, the allocations of transmit power or subcarriers in each cell are fixed prior to system deployment. This limits the potential performance of the SFR scheme. In this paper, we propose an intercell resource-allocation algorithm, which is referred to as the adaptive SFR algorithm (ASFR), that dynamically optimizes subcarrier and power allocations for multicell wireless networks to improve system capacity. The ASFR first finds the subcarrier and power allocations in each cell by using exhaustive search and greedy descend methods and then iteratively repeats among cells until a predefined convergence criterion is satisfied. The theoretical analysis proves the convergence of the ASFR algorithm. Simulation results show that the ASFR achieves a higher system throughput and better cell edge user performance than existing frequency reuse schemes. [ABSTRACT FROM PUBLISHER]

Heterogeneous cellular network is considered as an important network architecture to improve spectral efficiency and energy efficiency. Extensive research has revealed that spectral efficiency and energy efficiency could be two conflicting performance metrics under most scenarios. Toward the next generation 5G wireless systems, both spectral efficiency and energy efficiency become increasingly important. How to design a wireless system that jointly considers/optimizes these two performance metrics is critical yet challenging. This paper jointly analyzes the area spectral efficiency and area energy efficiency in a wireless heterogeneous network with inter-tier fractional frequency reuse. Proportional fairness resource allocation is used to balance the spectral efficiency and user fairness within each cell. A theoretical framework is formulated to analyze the area spectral efficiency and area energy efficiency in such a system. Fractional frequency reuse and proportional fairness resource allocation define the optimal power reduction factor and fractional bandwidth partition to maximize the joint area spectral efficiency and area energy efficiency. The system performance is evaluated by using the proposed scheme with different system parameter settings including base station densities, cell fractional bandwidth partition, power threshold, and base station power consumptions. The study shows that fractional frequency reuse with proper settings can significantly increase the area spectral efficiency and area energy efficiency in wireless heterogeneous networks. [ABSTRACT FROM AUTHOR]

Channel state information (CSI) is critical for the performance of cooperative multicell transmission. In this paper, the performances of cooperative multicell precoding under global CSI and local individual CSI are analyzed and compared in the large dimensional regime. Using theoretical results from large random matrix theory, we derive large dimensional approximations of signal-to-interference-plus-noise ratio for both precoding cases. Such approximations depend only on the slow fading channel statistics instead of the fast fading channel realizations. It is easy to quantify the performance loss caused by local individual CSI in the large dimensional regime. Two different massive MIMO scenarios are considered. When the number of antennas and that of users go large at the same rate, there is a constant gap between the two CSI cases. When the number of antennas goes large, while the number of users is fixed, the performances of both CSI cases are the same. This means that the impact of limited local individual CSI vanishes. Numerical results validate the theoretical analysis and show that there is constant performance loss due to the price of limited CSI. Also, the performance of precoding with local individual CSI almost decreases linearly with the increased number of BSs for the first scenario. [ABSTRACT FROM PUBLISHER]

This paper investigates simultaneous wireless information and power transfer (SWIPT) in the ad hoc network, where access points (APs) with multiple antennas can transfer energy as well as information using a common spectrum resource. The receiving nodes decode the incoming information data (information decoding, ID) and/or harvest the RF energy (energy harvesting, EH), where two different receiving node architectures—time switching (TS) and power splitting (PS)—are considered. By using a stochastic geometry approach, we aim to analyze the transmission capacity and the harvested energy per unit area as performance measures of the SWIPT in the ad hoc network. From the analytical results, we can derive the optimal node densities of ID nodes and EH nodes for TS architectures and, furthermore, optimize the power splitting ratio jointly with the node density for the PS architectures such that the harvested energy per unit area is maximized when the target transmission capacity is given. The proposed node density optimization gives us a useful insight into the design of SWIPT-based ad hoc network, where we can show how densely the APs/nodes can be deployed in a given area and furthermore, find that the ad hoc network with PS receiving nodes outperforms that with TS receiving nodes for a large target transmission capacity, and vice versa. [ABSTRACT FROM AUTHOR]

Blocking probability is widely used as a performance measure for dimensioning a variety of networks, including wireless communication systems. However, the performance of the system may be affected by factors other than traffic and resources, i.e., the primary ingredients in blocking. Such factors include interference, energy consumption, service delay restriction, and others. In this case, blocking by itself does not fully convey the extent of the system quality of service (QoS). Those other phenomena may lead the system to experience an outage, in which case resources, even if available, cannot be used because of the performance degradation that this may incur. In this paper, we propose a performance measure, i.e., BlockOut probability, that combines blocking and outage in one parameter. Exact, closed-form, and recursive forms of this parameter are presented, and a simple example of application is shown. The BlockOut probability encompasses the well-known Erlang-B formula as a special case. Although the application example focuses on wireless systems, BlockOut may find use in a variety of other networks. [ABSTRACT FROM PUBLISHER]

This paper studies multi-agent deep reinforcement learning (MADRL) based resource allocation methods for multi-cell wireless powered communication networks (WPCNs) where multiple hybrid access points (H-APs) wirelessly charge energy-limited users to collect data from them. We design a distributed reinforcement learning strategy where H-APs individually determine time and power allocation variables. Unlike traditional centralized optimization algorithms which require global information collected at a central unit, the proposed MADRL technique models an H-AP as an agent producing its action based only on its own locally observable states. Numerical results verify that the proposed approach can achieve comparable performance of the centralized algorithms. [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]

In this paper, resilient transmission in a multicell multiple-input multiple-output (MIMO) interference wiretap channel model is studied. Each base station (BS) transmits confidential messages to its intended legitimate user with multiple antennas in the presence of eavesdroppers that can overhear the transmission. We study the problem of finding the optimal transmit covariance matrices at the BSs to maximize the secrecy sum rate, which is typically nonconvex and intractable to obtain a globally optimal solution. A distributed iterative optimization algorithm based on a novel decomposition framework across all users is proposed. The decomposition framework preserves the convexity of the objective function and linearizes the nonconvex part. At each iteration, the BSs simultaneously solve a sequence of problems that are decoupled convex approximations of the original secrecy sum-rate function. Moreover, the complexity of the algorithm is analyzed. Numerical results are presented to validate the effectiveness of the proposed distributed algorithm. [ABSTRACT FROM PUBLISHER]

Dynamic spectrum access (DSA) techniques based on the exclusive-use model provide a huge opportunity for wireless service providers (WSPs) to improve the spectrum utilization in their licensed bands and generate additional profits by allowing temporary wireless access to unsubscribed secondary users (SUs). This paper presents a techno-economic analysis for regulated SU access based on a novel base station (BS)-centric framework, where SUs coexist with the subscribers, i.e., primary users (PUs), on a mutually exclusive basis. Considering the highly competitive WSP environment, the proposed framework is aimed at maximizing the localized spectrum utilization within the static spectrum licensed to the WSP and assumes no cooperation and no spectrum sharing among WSPs, thus making this a business case for implementation. The dynamic incentive-based SU pricing model proposed in this paper has the inherent capability of call admission control and, hence, is useful in attracting SUs to obtain temporary wireless access during periods of low PU demand, thus improving spectrum usage in the temporal domain. Although SU access is regulated by the WSP at their BS, the SUs have the freedom to connect or handoff to their preferred BS in the area based on the SU price quoted by the WSP. The implementation of the proposed framework to Long Term Evolution (LTE) infrastructure requires minimal enhancements and can be potentially attractive to WSPs, since the SU devices in this framework do not require spectrum sensing cognitive capabilities. Considering all the aforementioned aspects, this paper can be considered an intermediate step in the evolution toward complete DSA. [ABSTRACT FROM PUBLISHER]

In this paper, a full-duplex unmanned aerial vehicle-(UAV) base station is used to provide wireless communication to an area lacking a conventional terrestrial infrastructure, and its efficient deployment is investigated. More concretely, the UAV positioning and resource allocation problems are solved with the aim of minimizing the transmit power of the UAV, while serving users with their rate requirements and accounting for the backhaul limitation of the UAV. To this end, a complete solution for the optimal 3D position of the UAV, the bandwidth assignment and the transmit power distribution in the access and backhaul links is proposed that accounts for both the backhaul interference and the self-interference. When the UAV power budget is insufficient to fulfill rate requirements, non-orthogonal multiple access (NOMA) pairing is conducted to enhance system performance. Simulation results show that, when using the proposed approach, both the achieved sum rate and the percentage of satisfied users are significantly increased, when compared to a strategy that uses separate frequency bands in the access and backhaul links, as well as to a previously proposed method. [ABSTRACT FROM AUTHOR]

In this paper, we study the secure transmission in multiple access wiretap channels when the instantaneous channel state information (CSI) of the wiretap channels is unknown by the legitimate users. We propose a two-phase jamming-assisted secure transmission scheme based on the randomness and independence of wireless channels. In this scheme, we appropriately design artificial noise in two transmission phases and make sure that the eavesdropper's channel is degraded by the artificial noise but the legitimate user's channel is free of the artificial noise. We analyze the capacity of the legitimate channel after using successive interference cancellation (SIC), and demonstrate that the eavesdropping capacity has an upper bound. Furthermore, we prove that a positive secrecy rate can be achieved and the achievable secrecy rate can be maximized by allocating appropriate power to the private information and the artificial noise. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new concept of a knowledge management framework to enable a self-optimizing and self-learning for wireless system operation in real time. The framework encapsulates both environment and intelligent agent to reach optimal operation through sensing, perception, reasoning, and learning in a truly autonomous fashion. The agent derives adequate knowledge from previous actions improving the quality of future decisions. Domain experience was provided to guide the agent while exploring and exploiting the set of possible actions in the environment. Thus, it guarantees low-cost learning and achieves a near-optimal network configuration addressing the non-deterministic polynomial-time hardness problem of joint channel and location optimization in a wireless system. Extensive simulations are run to validate its fast convergence, high throughput, and resilience to dynamic interference conditions. We deploy the framework on off-the-shelf wireless devices to propose autonomous self-optimization with knowledge management. [ABSTRACT FROM AUTHOR]

In emerging heterogeneous networks (HetNets), a wide range of the underlying performance evaluation problems is related to wireless interference characterization and can be reduced to investigating the distribution of a side length in a random triangle. In this paper, we address the task of calculating the side-length distribution in such a triangle determined by the known distributions of its two other sides and the distribution of the angle between them. No restrictions on the distributions of input random variables (RVs) are imposed except for their statistical independence. Our solution delivers a crucial building block for interference analysis in multitier and multiradio HetNets, including mobile device-to-device communication as one of the most extreme interference-limited cases. [ABSTRACT FROM AUTHOR]

This paper investigates advanced energy-efficient wireless systems in orthogonal frequency-division multiple access (OFDMA) downlink networks using coordinated multipoint (CoMP) transmissions between the base stations (BSs) in a heterogeneous network (HetNet), which is adopted by Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE)-Advanced to meet International Mobile Telecommunications-Advanced targets. HetNet CoMP has received significant attention as a way of achieving spectral efficiency (SE) and energy efficiency (EE). Usually, in the literature, the total network power consumption is restricted to the sum of the power consumption of all BSs. The significance of the power consumption of the backhaul links in wireless networks is normally omitted for its trivial effect with respect to that of the radio BSs. For SE and EE analysis of HetNet CoMP, the energy and bandwidth consumption of the backhaul is considered, without which, the investigation remains incomplete. However, SE and EE are design criteria in conflict with each other, and a careful study of their tradeoff is mandatory for designing future wireless communication systems. The EE is measured as “throughput (bits) per joule,” whereas the power consumption model includes RF transmit (radiated), circuit, and backhaul power. Furthermore, a nonideal backhaul model such as a microwave link is also investigated within intra-HetNet-CoMP (inside one cell), where an implementing fiber is not feasible. An intercell interference (ICI) coordination method is also studied to mitigate ICI. At the end, a novel resource allocation algorithm is proposed—modeled as an optimization problem—which takes into account the total power consumption, including radiated, circuit, and backhaul power, and the minimum required data rate to maximize EE. Given an SE requirement, the EE optimization problem is formulated as a constrained optimization problem. The considered optimization problem is transformed into a convex optimization problem by redefining the constraint using cubic inequality, which results in an efficient iterative resource allocation algorithm. In each iteration, the transformed problem is solved by using dual decomposition with a projected gradient method. Simulations results demonstrate how backhaul has a significant impact on total power consumption and the effectiveness of the studied schemes. In addition, the results demonstrate that the proposed iterative resource allocation algorithm converges within a small number of iterations and illustrate the fundamental tradeoffs between SE and EE. Our analytical results shed light on future “green” network planning in advanced OFDMA wireless systems like those envisioned for a fifth-generation (5G) system. [ABSTRACT FROM PUBLISHER]

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

The shared resource access wireless communication system is regarded as an efficient paradigm that allows the mobile network operators to have extended coverage and satisfy their subscribers’ high capacity demands while keeping the capital and operational expenditure in check. On the other hand, dual connectivity (DC), a small cell enhancement feature, allows the subscribers to have two simultaneous connections increasing throughput and enhancing mobility robustness. The coordinated multipoint (CoMP) transmission/reception and user-centric virtual cell (VC) improve the signal quality and performance. For all of these mechanisms, the user needs to be under the coverage of multiple base stations (BSs) concurrently. Because of the random nature of the wireless links and distribution of BSs in a network, the practicability/operability of DC and CoMP/VC for a typical user under such random operating conditions (both topological and wireless link randomness) needs to be adequately evaluated. In this paper, we take an extensive look at this problem exploiting tools from Poisson point process theory and stochastic geometry and derive easy-to-evaluate tractable integral expressions for essential performance metrics such as DC and CoMP/VC coverage probability of a typical user in downlink cellular. Unlike most of the existing works, we consider a signal propagation loss model, where the selection of the strongest (not necessarily the closest) BS that serves the typical user is perturbed by arbitrary shadowing, not by fading, i.e., we consider a fading-averaged signal propagation loss process. We derive the coverage probability as a function of various system parameters such as BS density, fading parameters, the cardinality of the coordination set for CoMP/VC, etc. We verify the analytical analysis with simulation results [ABSTRACT FROM AUTHOR]

This paper considers a heavy loaded full-duplex (FD) small cell consisting of one FD base station and multiple half-duplex users where the number of subchannels is less than the number of uplink and downlink users. With the objective of maximizing the total sum-rate, a joint power allocation, and user pairing problem is formulated. To solve this problem, a novel decomposition method is proposed, which decouples the power allocation and user pairing problem into two subproblems. It is proven that the optimal solution of subproblems is the optimal solution of the original problem. Then, optimal algorithms are developed for the two subproblems. Numerical results show that the proposed algorithm achieves better performance compared with the baselines of the greedy algorithm and random pairing algorithm. [ABSTRACT FROM AUTHOR]

This paper develops an adaptive cooperative transmission scheme with relays harvesting wireless energy. Two relays are adopted to alternately forward source data to the destination using the two-path successive relaying (TPSR) protocol. When one relay forwards previous data along with source transmitting current data, using the power-splitting technique, the other relay will harvest energy and decode the current data from the received composite signal. If the TPSR cannot be performed due to the failure of data decoding at either relay, the decode-and-forward (DF) protocol will be performed by selecting a better relay. If one relay joins in the DF relaying, it will harvest energy and decode source data using the PS technique, while the other relay will always harvest energy from the received signal. If neither TPSR nor DF relaying can be performed, the source will transfer wireless power to both relays. The transmit powers of relays and the PS ratio are judiciously determined through analyzing the occurrence probability, average power fading, and success probability of each case. Numerical results show that our adaptive relaying scheme can achieve a much higher throughput than the single-relay DF scheme and the TPSR-only scheme. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the resource allocation problem in two-tier heterogenous networks (HetNets) with massive MIMO, where two frequency bands, cellular frequency band and millimeter wave frequency band, are used for wireless backhaul links. To coordinate the interference among small cells (SCs), SCs are grouped into multiple SC clusters (SCCs), where SC users are jointly served by SC base stations (BSs) (SBSs) belonging to the same SCC. To eliminate the multi-user and inter-tier interference, we propose a block diagonalization based precoding scheme at macro-BS and each SCC, where the transmit precoding matrix for users is projected onto the null space of interference channels. Following this, we formulate a power allocation optimization problem to maximize the downlink sum rate of the system subject to per-SCC power and users’ quality of service requirements. Since the formulated problem is nonconvex, we transform it into a convex one by appropriate approximation, and a constrained concave convex procedure based iterative algorithm is proposed to obtain the solution. Furthermore, we prove that the obtained solution converges to the local optimum. Meanwhile, according to the structure of the original formulated problem, we divide it into multiple subproblems and propose an optimal iterative water-filling algorithm. Next, we extend the original problem with per-SBS power constraint, which results in that the precoding of each SCC has to be redesigned. On this basis, we propose an iterative water-filling algorithm to obtain the optimal power allocation and precoding. Numerical results are presented to verify the performance of our proposed algorithms. [ABSTRACT FROM PUBLISHER]

Sharing spectrum resources in unlicensed bands grants vehicular applications inexpensive and ubiquitous access to wireless services. However, wireless technology coexistence concerns are gaining increased attention. In response, coexistence test methods are now being reported in the literature, and novel solutions are considered in the American National Standards Institute C63.27 Standard for Evaluation of Wireless Coexistence. Furthermore, the IEEE 802 standards committee formed a new study group, named wireless automotive coexistence, operating under the umbrella of 802.19 working group to highlight the increasing concerns of wireless coexistence in the automotive domain. The radiated open environment coexistence test (ROECT) method offers high flexibility to test wireless devices for coexistence. Radio signal propagation during testing is over the air, reducing access to the signal path. Consequently, monitoring instantaneous device performance is a challenge yet to be addressed. This paper introduces a novel method for estimating the channel utilization of multiple, concurrent wireless transmitters sharing the 2.4-GHz ISM band in the context of ROECT. Passively received power measurements were collected during testing, and then a Gaussian mixture model was used to build a classifier for labeling observed power samples relative to their source. Case studies utilizing IEEE 802.11n as an interfering system with an under test system based on either IEEE 802.11n or ZigBee are detailed. Findings demonstrate the mutual effect of spectrum sharing on both interfering and under test systems in terms of per-second channel utilization and frame collision. Experimental results show an overall accuracy exceeding 98%. [ABSTRACT FROM PUBLISHER]

Beyond third-generation (3G) wireless systems will support real-time (inelastic) and nonreal-time (elastic) traffic over a common packet-switched radio channel using quality-of-service (QoS) mechanisms to differentiate the traffic. A key challenge in accurately modeling user and system performances is to be able to simultaneously account for the impacts of mixed traffic types, QoS mechanisms, and varying radio channels. This paper presents a novel way of extending and combining a number of techniques into a single approximate analytic methodology for providing fast and accurate performance analysis of multiple inelastic- and elastic-traffic classes, which is subject to preemptive priority for the inelastic traffic. The methodology is compared with the simulation for a range of guaranteed bit-rate requirements for the inelastic traffic and overall system traffic loads, with the results showing excellent agreement between the model and simulation. [ABSTRACT FROM PUBLISHER]

Most slot assignment algorithms that are proposed for spatial time-division multiple-access (STDMA) mesh networks use a simplified transmission model that does not consider the time-varying fading characteristic of a wireless channel. In addition, these algorithms are usually link based, and scheduling in each slot is fixed and done for links. When the scheduled link is in deep fade or has no traffic, the slot that is given to that link will be wasted. In this paper, we present a node-based slot assignment scheme in which scheduling in each slot is done for nodes and not links. Because a node has multiple links, it can exploit multiuser diversity, i.e., different links have different traffic and fading conditions, to achieve much better performance. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a distributed and asynchronous topology control framework for wireless multihop networks, aiming at improving the quality-of-service capabilities of such systems. The proposed mechanisms exploit cross-layer information such as physical-layer signal-to-interference-plus-noise ratio (SINR) values and medium-access-control (MAC)/network-layer connectivity to effectively allocate resources. Based on properly defined utility functions, we cast the transmission power allocation problem as a noncooperative game and then show that it belongs to the class of potential games. We obtain structural properties of the defined game and its variations and demonstrate their effectiveness. Through analysis and simulation, we explore the behavior of the proposed framework and compare it with the most relevant approach in the literature. It is shown that the proposed unifying game-theoretic framework achieves three key goals for multihop ad hoc networks, i.e., reduced transmission power, high-quality links, and connectivity maintenance. [ABSTRACT FROM PUBLISHER]

This paper provides novel analysis methods and detailed simulations for determining the impact of out-of-band emissions (OOBE) of adjacent band wireless services on mobile receive-only wireless services. Using the interference from the adjacent cellular bands on an operational digital wireless receive-only system as an example, we demonstrate the impact of the interference from adjacent cellular band transmitters and determine the performance impact such as outage on satellite receivers in realistic roadway conditions. This paper presents new methods for determining appropriate OOBE spectral masks for use by new cellular subscriber transmitters. This paper considers realistic propagation and traffic conditions in five cities throughout the United States and offers approaches that the engineering community may use to determine interference conditions between new cellular and fixed broadband mobile services in adjacent spectrum bands to existing receive-only mobile receiver systems, such as satellite radio. [ABSTRACT FROM PUBLISHER]

In this paper, a novel social network-aware user association in wireless small cell networks with underlaid device-to-device (D2D) communication is investigated. The proposed approach exploits strategic social relationships between user equipments (UEs) and their physical proximity to optimize the overall network performance. This problem is formulated as a matching game between UEs and their serving nodes (SNs) in which, an SN can be a small cell base station (SCBS) or an important UE with D2D capabilities. The problem is cast as a many-to-one matching game in which UEs and SNs rank one another using preference relations that capture both the wireless aspects (i.e., received signal strength, traffic load, etc.) and users’ social ties (e.g., UE proximity and social distance). Due to the combinatorial nature of the network-wide UE–SN matching, the problem is decomposed into a dynamic clustering problem in which SCBSs are grouped into disjoint clusters based on mutual interference. Subsequently, an UE–SN matching game is carried out per cluster. The game under consideration is shown to belong to a class of matching games with externalities arising from interference and peer effects due to users social distance, enabling UEs and SNs to interact with one another until reaching a stable matching. Simulation results show that the proposed social-aware user association approach yields significant performance gains, reaching up to \text26\%, \text24\%, and \text31\% for 5th, 50th, and 95th percentiles for UE throughputs, respectively, as compared to the classical social-unaware baseline. [ABSTRACT FROM AUTHOR]

In this paper, we propose a general framework to evaluate the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in cognitive radio networks (CRNs). The proposed framework is discussed in three typical CRN paradigms: underlay CRNs (UCRNs), overlay CRNs (OCRNs), and interweave CRNs (ICRNs). The EE–SE relation for three CRNs is expressed in the closed-form formulation, in which the optimal (suboptimal) EE solution as the function of SE is deduced with the corresponding limits. The theoretical analysis and numerical results indicate that the EE–SE relation in CRNs is not contrary, i.e., an optimal EE–SE tradeoff can be achieved. The proposed framework provides a useful guidance in the design of practical green CRNs. [ABSTRACT FROM AUTHOR]

The communication channel power gain to the nearest neighbor of a node in a wireless communication network is not necessarily the largest among all neighbors due to fading. The probability that the $k$th nearest neighbor of a node has the best communication channel with the highest power gain in a 2-D network with homogeneous Poisson distribution of nodes is derived for a general fading environment. The result is specialized to the case where the communication links are modeled as generalized-gamma fading channels. The analytical results are verified and illustrated by computer simulations and numerical results. Some applications of the new theory are also presented. A novel criterion that represents the fading severity, i.e., the generalized amount of fading (GAF) , is defined, and its value as an important measure for fading channels is justified. [ABSTRACT FROM PUBLISHER]