Performance Of Wireless Communication Networks Research Articles

Deep-Reinforcement-Learning-Based Joint 3-D Navigation and Phase-Shift Control for Mobile Internet of Vehicles Assisted by RIS-Equipped UAVs

Unmanned aerial vehicles (UAVs) are utilized to improve the performance of wireless communication networks (WCNs), notably, in the context of Internet-of-things (IoT). However, the application of UAVs, as active aerial base stations (BSs)/relays, is questionable in the fifth-generation (5G) WCNs with quasi-optic millimeter wave (mmWave) and beyond in 6G (visible light) WCNs. Because path loss is high in 5G/6G networks that attenuate, even, the line-of-sight (LoS) communicating signals propagated by UAVs. Besides, the limited energy/size/weight of UAVs makes it cost-deficient to design aerial multi-input/output BSs for active beamforming to strengthen the signals. Equipping UAVs with the reconfigurable intelligent surface (RIS), a passive component, can help to address the problems with UAV-assisted communication in 5G and optical 6G networks. We propose adopting the RIS-equipped UAV (RISeUAV) to provide aerial LoS service and facilitate communication for mobile Internet-of-vehicles (IoVs) in an obstructed dense urban area covered by 5G/6G. RISeUAV-aided wireless communication facilitates vehicle-to-vehicle/everything communication for IoVs for updating IoT information required for sensor fusion and autonomous driving. However, autonomous navigation of RISeUAV for this purpose is a multilateral problem and is computationally challenging for being optimally implemented in real-time. We intelligently automated RISeUAV navigation using deep reinforcement learning to address the optimality and time complexity issues. Simulation results show the effectiveness of the method.

Deep-Learning-Assisted IoT-Based RIS for Cooperative Communications

Reconfigurable intelligent surfaces (RISs) are software-controlled passive devices that can be used as relay (R) systems to reflect incoming signals from a source (S) to a destination (D) in a cooperative manner with optimum signal strength to improve the performance of wireless communication networks. The configurability and flexibility of an RIS deployed in an Internet-of-Things (IoT)-based network can enable network designers to devise stand-alone or cooperative configurations that have considerable advantages over conventional networks. In this paper, two new deep neural network (DNN)-assisted cooperative RIS models, namely, DNNR-CRIS and DNNR,D-CRIS, are proposed for cooperative communications. In DNNR-CRIS model, the potential of RIS deployment as an IoT-based relay element in a next-generation cooperative network is investigated using deep learning (DL) techniques for RIS phase optimization. In addition, to reduce the maximum likelihood (ML) complexity at D, a new DNN-based symbol detection method is presented with the DNNR,D-CRIS model combined with DNN-assisted phase optimization. For a different number of relays and receiver configurations, the bit error rate (BER) performance results of the proposed DNNR-CRIS and DNNR,D-CRIS models and traditional cooperative RIS (CRIS) scheme (without a DNN) are presented for a multi-relay cooperative communication scenario with path loss effects. It is revealed that the proposed DNN-based models show promising results in terms of BER, even in high-noise environments with low system complexity.

Wireless Control of Modular Multilevel Converter Submodules With Communication Errors

Wireless control of modular multilevel converter (MMC) submodules can benefit from different points of view, such as lower converter cost and shorter installation time. In return for the advantages, the stochastic performance of wireless communication networks necessitates an advanced converter control system immune to the losses and delays of the wirelessly transmitted data. This article proposes an advancement to the distributed control of MMCs to be utilized in wireless submodule control. Using the proposed method, the operation of the MMC continues smoothly and uninterruptedly during wireless communication errors. The previously proposed submodule wireless control concept relies on implementing the modulation and individual submodule-capacitor-voltage control in the submodules using the insertion indices transmitted from a central controller. This article takes the concept as a basis and introduces to synthesize the indices autonomously in the submodules during the communication errors. This new approach allows the MMC continue its operation when one, some, or all submodules suffer from communication errors for a limited time. The proposal is validated experimentally on a laboratory-scale MMC.

Deep Learning for Channel Tracking in IRS-Assisted UAV Communication Systems

To boost the performance of wireless communication networks, unmanned aerial vehicles (UAVs) aided communications have drawn dramatically attention due to their flexibility in establishing the line of sight (LoS) communications. However, with the blockage in the complex urban environment, and due to the movement of UAVs and mobile users, the directional paths can be occasionally blocked by trees and high-rise buildings. Intelligent reflection surfaces (IRSs) that can reflect signals to generate virtual LoS paths are capable of providing stable communications and serving wider coverage. This is the first paper that exploits a three-dimensional geometry dynamic channel model in IRS- assisted UAV-enabled communication system. Moreover, we develop a novel deep learning based channel tracking algorithm consisting of two modules: channel pre-estimation and channel tracking. A deep neural network with off-line training is designed for denoising in the pre-estimation module. Moreover, for channel tracking, a stacked bi-directional long short term memory (Stacked Bi-LSTM) is developed based on a framework that can trace back historical time sequence together with bidirectional structure over multiple stacked layers. Simulations have shown that the proposed channel tracking algorithm requires fewer epochs to convergence compared to benchmark algorithms. It also demonstrates that the proposed algorithm is superior to different benchmarks with small pilot overheads and comparable computation complexity.

A Universal Testbed for IoT Wireless Technologies: Abstracting Latency, Error Rate and Stability from the IoT Protocol and Hardware Platform.

IoT applications rely strongly on the performance of wireless communication networks. There is a wide variety of wireless IoT technologies and choosing one over another depends on the specific use case requirements—be they technical, implementation-related or functional factors. Among the technical factors, latency, error rate and stability are the main parameters that affect communication reliability. In this work, we present the design, development and validation of a Universal Testbed to experimentally measure these parameters, abstracting them from the wireless IoT technology protocols and hardware platforms. The Testbed setup, which is based on a Raspberry Pi 4, only requires the IoT device under test to have digital inputs. We evaluate the Testbed’s accuracy with a temporal characterisation—accumulated response delay—showing an error less than 290 µs, leading to a relative error around 3% for the latencies of most IoT wireless technologies, the latencies of which are usually on the order of tens of milliseconds. Finally, we validate the Testbed’s performance by comparing the latency, error and stability measurements with those expected for the most common IoT wireless technologies: 6LoWPAN, LoRaWAN, Sigfox, Zigbee, Wi-Fi, BLE and NB-IoT.

Performance analysis of RIS aided NOMA networks with hardware impairments

Reconfigurable intelligent surface (RIS) has stimulated their potential applications for improving the performance of wireless communication networks. In this paper, the performance of RIS aided non-orthogonal multiple access (NOMA) networks with hardware impairments over Rician fading channels is investigated. More specifically, the exact and asymptotic expressions of outage probability for a pair of users, that is, the nearby user n and distant user m are derived, where the imperfect successive interference cancellation (ipSIC) and perfect SIC (pSIC) are taken into consideration. According to the approximate analyses, the diversity orders of user n with ipSIC/pSIC and user m are obtained in the high signal-to-noise radio regime. It indicates that the diversity orders are in connection with reflecting elements and Rician factors except the channel ordering. The impact of these parameters on outage behaviors of RIS-NOMA networks is also analysed. In addition, the system throughput of RIS-NOMA networks with ipSIC/pSIC is surveyed in detail. Monte Carlo simulations are present to verify the correctness of theoretical analyses that: (1) The outage probability of user n with pSIC is superior to that of orthogonal user, while the outage probability of user m is inferior to that of orthogonal user and (2) as the number of reflecting elements and Rician factors increases, the outage behaviors of RIS-NOMA networks are enhanced carefully.

Intelligent Omni-Surfaces for Full-Dimensional Wireless Communications: Principles, Technology, and Implementation

The recent development of metasurfaces has motivated their potential use for improving the performance of wireless communication networks by manipulating the propagation environment through nearly passive sub-wavelength scattering elements arranged on a surface. However, most studies of this technology focus on reflective metasurfaces, that is, the surface reflects the incident signals toward receivers located on the same side of the transmitter, which restricts the coverage to one side of the surface. In this article, we introduce the concept of an intelligent omni-surface (IOS), which is able to serve mobile users on both sides of the surface to achieve full-dimensional communications by jointly engineering its reflective and refractive properties. The working principle of the IOS is introduced, and a novel hybrid beamforming scheme is proposed for IOS-based wireless communications. Moreover, we present a prototype of IOS-based wireless communications and report experimental results. Furthermore, potential applications of IOSs to wireless communications together with relevant research challenges are discussed.

Enabling Smart Reflection in Integrated Air-Ground Wireless Network: IRS Meets UAV

Intelligent reflecting surface (IRS) and unmanned aerial vehicle (UAV) have emerged as two promising technologies to boost the performance of wireless communication networks by proactively altering wireless communication channels via smart signal reflection and maneuver control, respectively. However, they face different limitations in practice, which restrain their future applications. In this article, we propose new methods to jointly apply IRS and UAV in integrated air-ground wireless networks by exploiting their complementary advantages. Specifically, the terrestrial IRS is used to enhance the UAV-ground communication performance, while the UAV-mounted IRS is employed to assist in terrestrial communication. We present their promising application scenarios, new communication design issues, as well as potential solutions. In particular, we show that it is practically beneficial to deploy both terrestrial and aerial IRSs in future wireless networks to reap the benefits of smart reflections in 3D space.

Energy Efficiency Optimization Using Iterative and Metaheuristic Algorithms

The communication technology industry's energy consumption and the resulting energy-related pollution are becoming serious societal and economic challenges. One of the most essential parameters for selecting potential technologies for upcoming wireless communication networks is bandwidth efficiency (BE). However, the main objective is to develop new creative network architecture and technologies that are required to meet the rapid growth in cellular data demand while maintaining same amount of power.Also, Energy Efficiency (EE) has emerged as a key parameter for assessing the performance of wireless communication networks. In this context, the recently suggested massive multiple-input multiple-output (MIMO) technology, which comes under multiuser MIMO with an excess of base station (BS) antennas to support a substantial number of user equipment's (UE) is one of the main technology enablers for 5G.In this paper, new power consumption model is addressed and also novel EE maximization algorithm is proposed which optimizes the resource allocation in massive MIMO network.

Caching deployment based on energy efficiency in device-to-device cooperative networks

The rapid growth of mobile data traffic demand will cause congestion to the future communication network. The cache-enabled device-to-device communication has been proven to effectively enhance the performance of wireless communication networks. This article investigates the caching deployment problem from the energy efficiency in the cache-enabled device-to-device networks. According to the random geometry theory modeling, the closed form expression of energy efficiency is derived, which measures the average number of successful transmitted file bits per unit time and per unit power consumption. And then we establish an optimization problem to maximize energy efficiency. As the formulated optimization problem is a multiple-ratio fractional programming problem that cannot be solved conveniently, we propose a quadratic transformation method to nest in the energy efficiency maximization problem. To tackle this problem, an iterative optimization algorithm is proposed to optimize the caching policy and network energy efficiency. The simulation results demonstrate that the proposed policy can achieve higher energy efficiency and hit probability in the cache-enabled device-to-device network.

Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network

IRS is a new and revolutionizing technology that is able to significantly improve the performance of wireless communication networks, by smartly reconfiguring the wireless propagation environment with the use of massive low-cost passive reflecting elements integrated on a planar surface. Specifically, different elements of an IRS can independently reflect the incident signal by controlling its amplitude and/or phase and thereby collaboratively achieve fine-grained 3D passive beamforming for directional signal enhancement or nulling. In this article, we first provide an overview of the IRS technology, including its main applications in wireless communication, competitive advantages over existing technologies, hardware architecture as well as the corresponding new signal model. We then address the key challenges in designing and implementing the new IRS-aided hybrid (with both active and passive components) wireless network, as compared to the traditional network comprising active components only. Finally, numerical results are provided to show the great performance enhancement with the use of IRS in typical wireless networks.

3D-OMP and 3D-FOMP algorithms for DOA estimation

Adaptive antennas and antenna array processing have vital effects on enhancing the performance of wireless communication networks. One of the most significant applications of adaptive antenna systems is the Direction of Arrival (DOA) detection. Several schemes have been proposed in the literature for DOA estimation in two-dimensional space. Among them, Orthogonal Matching Pursuit (OMP) algorithm provides several advantages in comparison to other schemes. The OMP algorithm reduces complexity and improves resolution of detection. Furthermore, in this algorithm, the number of signal emitters is not required to be known. In this paper, we extend the OMP algorithm and propose Three Dimensional OMP (3D-OMP) scheme for DOA estimation in three dimensional space. We provide a redundant dictionary for 3D-OMP scheme by employing azimuth and elevation angles. Simulation results show the high performance of the 3D-OMP algorithm when the signal to noise ratio is higher than −10dB. Moreover, the 3D-OMP algorithm has a high efficiency in detecting multiple signal sources, simultaneously. Then, we evaluate the accuracy of the estimated directions by the 3D-OMP algorithm via comparing the variance of estimation error with the Cramer-Rao bound. Nevertheless, DOA estimation by the 3D-OMP algorithm has a substantial challenge where it cannot distinguish between two adjacent signal sources. To resolve this challenge, we propose Three Dimensional Focused Orthogonal Matching Pursuit (3D-FOMP) algorithm. The 3D-FOMP algorithm is an improved version of the 3D-OMP algorithm. It can detect two adjacent signal sources when the beam former has a single peak corresponding to a direction between right directions. In addition, we show the 3D-OMP and 3D-FOMP algorithms have lower complexities in comparison to the 3D-MUSIC and 3D-ESPRIT schemes when Root Mean Square Error (RMSE)>0.3o. This accuracy is persuasive for most applications. Moreover, simulation results show the capability of the 3D-FOMP algorithm to detect adjacent signal sources and it outperforms the 3D-OMP, 3D-MUSIC and 3D-ESPRIT algorithms for all values of signal to noise ratio.

Low complexity resource allocation in the relay channels with energy harvesting transmitters

Energy Harvesting (EH) is a novel technique to prolong the lifetime of the wireless Ad-hoc and sensor networks with replenishable nodes. In this sense, it has emerged as a promising technique for Green Communications. On the other hand, cooperative communication with the help of relay nodes improves the performance of wireless communication networks. In this paper, we investigate the cooperation in EH nodes. We consider the optimal power and rate allocation in the full-duplex Gaussian relay channel in which source and relay can harvest energy from their environments. In our model, the energy arrivals at the source and the relay are general stochastic processes with known EH times and amounts before the start of transmission. This problem has a constrained min-max optimization form that is not easy to solve. We propose a method based on a mathematical theorem to decompose it into two problems: the first problem has a tractable convex optimization form and can be solved efficiently. We show that the second problem is an unconstrained discrete convex optimization problem, which has the complexity of O(K2), instead of O(2K), where K is the dimension of variables. Also, we provide some numerical examples that confirm our results.

On Geostatistical Methods for Radio Environment Maps Generation under Location Uncertainty

Radio environment map (REM) can provide important information for designing and optimizing the performance of wireless communication networks. However, the location uncertainty related to the measurements used to build the REM can considerably deteriorate the accuracy of such map. This paper addresses this problem by proposing a modified approach of a classical geostatistical prediction tool, named Kriging method, which incorporates the location uncertainty and is able to improve the REM accuracy without adding significant complexity. Finally, we also show through simulation results that the average path loss and covariance parameter estimation play an important role and should be considered when the location errors occur in the wireless communication systems.

SHER: a colored petri net based random mobility model for wireless communications.

In wireless network research, simulation is the most imperative technique to investigate the network’s behavior and validation. Wireless networks typically consist of mobile hosts; therefore, the degree of validation is influenced by the underlying mobility model, and synthetic models are implemented in simulators because real life traces are not widely available. In wireless communications, mobility is an integral part while the key role of a mobility model is to mimic the real life traveling patterns to study. The performance of routing protocols and mobility management strategies e.g. paging, registration and handoff is highly dependent to the selected mobility model. In this paper, we devise and evaluate the Show Home and Exclusive Regions (SHER), a novel two-dimensional (2-D) Colored Petri net (CPN) based formal random mobility model, which exhibits sociological behavior of a user. The model captures hotspots where a user frequently visits and spends time. Our solution eliminates six key issues of the random mobility models, i.e., sudden stops, memoryless movements, border effect, temporal dependency of velocity, pause time dependency, and speed decay in a single model. The proposed model is able to predict the future location of a mobile user and ultimately improves the performance of wireless communication networks. The model follows a uniform nodal distribution and is a mini simulator, which exhibits interesting mobility patterns. The model is also helpful to those who are not familiar with the formal modeling, and users can extract meaningful information with a single mouse-click. It is noteworthy that capturing dynamic mobility patterns through CPN is the most challenging and virulent activity of the presented research. Statistical and reachability analysis techniques are presented to elucidate and validate the performance of our proposed mobility model. The state space methods allow us to algorithmically derive the system behavior and rectify the errors of our proposed model.

Performance Evaluation of Broad Band CDMA Signal Using Beam Forming Antenna Technology for Next Generation Communications

<p>In order to accommodate various multimedia services, next generation wireless networks are characterized by very high transmission rates. Thus, in such systems and networks, the received signal is not only limited by noise like Additive White Gaussian noise (AWGN) but especially with increasing data transmission rate by the Intersymbol Symbol Interference (ISI) due to time dispersion of channel. A number of techniques such as rake receiver in CDMA systems and equalizers in GSM systems have been proposed to combat the effect of fading so as to improve the performance of wireless communication network. In this paper we evolve the performance of uncoded uplink transmission in broadband CDMA using beam forming technique under multipath conditions. The beam-former has been implemented using Transport Delay Line (TDL) filters. An expression for the optimal weights of a TDL based beam former has been derived. A carrier frequency of 2 Ghz has been used in this work as they are useful for next generation wireless systems. Simulation results show that TDL beamformer can reduce the multipath fading and Multiple Access Interferance (MAI). It has been shown that if SNR (related with Variance of the channel) is maintained at 10 db and if a 3 ray based beamformer having 3 antennas with 3 taps is used, the Error Rate of 0.1was found without using channel coding.</p>

Incentives in cooperative networks: a contract-theoretic perspective

Abstract Multiuser cooperative communication significantly improves the performance of wireless communication networks. One key challenge of multiuser cooperative communication is how to design a cooperative mechanism to incentivize potential relay nodes to help a source node in its data transmission. In this paper, to address this problem, a contract-based principal-agent framework is proposed in the context of a cognitive-radio-based wireless relaying networks in which the sources’ wireless characteristics constitute hidden information which is not known by the relay. The problem is modeled as a monopolist’s problem, in which a mobile relay node acts as the principal who designs incentive-compatible (IC) and individually rational (IR) contract items, consisting of a set of rate-price pairs. Subsequently, contract items can be broadcast by the relay to nearby mobile users that want to send data. Once these sources optimally select an item and notify the relay that they are willing to accept it, the relay then chooses one source based on the highest revenue for which to provide service. The cooperative gain, relay’s revenue, and expected data rate are characterized for the optimal contract under complete information and incomplete information. Theoretical analysis and numerical results show that this pricing mechanism can lead to a win-win situation in which source nodes get good communication service and relay nodes maximize their own profit that can, in turn, be used to purchase the relay service of other nodes when needed in the future. Moreover, the proposed mechanism is shown to also exhibit other important features such as low complexity and low signaling overhead.

Electromagnetic Lens-Focusing Antenna Enabled Massive MIMO: Performance Improvement and Cost Reduction

Massive multiple-input-multiple-output (MIMO) techniques have been recently advanced to tremendously improve the performance of wireless communication networks. However, the use of very large antenna arrays at the base stations brings new issues, such as the significantly increased hardware and signal processing costs. In order to reap the performance gains of massive MIMO and yet reduce its cost, this paper proposes a novel system design by integrating an electromagnetic (EM) lens with the large antenna array, termed the EM-lens enabled MIMO. The EM lens has the capability of focusing the power of an incident wave to a small area of the antenna array, whereas the location of the focal area varies with the angle of arrival (AoA) of the wave. Hence, in scenarios where the arriving signals from geographically separated users have different AoAs, the EM-lens enabled receiver provides two new benefits, namely, energy focusing and spatial interference rejection. By taking into account the effects of imperfect channel estimation via pilot-assisted training, in this paper, we analytically show that the average received signal-to-noise ratio in both the single-user and multiuser uplink transmissions can be improved by the EM-lens enabled system. Furthermore, we demonstrate that the proposed design makes it possible to considerably reduce the hardware and signal processing costs with only slight degradations in performance. To this end, two complexity/cost reduction schemes are proposed, which are small-MIMO processing with parallel receiver filtering applied over subgroups of antennas to reduce the computational complexity, and channel covariance based antenna selection to reduce the required number of radio frequency chains. Numerical results are provided to corroborate our analysis and show the great potential advantages of our proposed EM-lens enabled MIMO system for next generation cellular networks.

The effect of hexagonal grid topology on wireless communication networks based on network coding

SUMMARYNetwork coding has emerged as a promising technology that can provide significant improvements in the performance of wireless communication networks. Inspired by the recent advances in complex networks, we herein study the effect of topology structure on the performance benefit of network coding based on a highly structured wireless communication network with hexagonal grid topology. We propose a new concept called ‘network intensity’, namely γ to characterize the property of hexagonal grid topology. We first derive a value of 12 ∕ 7 for the upper bound on performance benefit in a single regular hexagon network. This value holds only if the network intensity is in the case of . Based on the results in a single regular hexagon network, we then derive a value of 16 ∕ 7 for the upper bound on performance benefit in a general hexagonal grid network only if the network intensity is in the case of . Furthermore, a comparative analysis demonstrates that the network intensity affects the performance benefit of network coding in terms of the interference and the coding number. These findings will contribute to the design of network topology and the analysis of the bound on the performance benefit of network coding in wireless communication networks. Copyright © 2014 John Wiley & Sons, Ltd.

Security and Reliability Performance Analysis for Cloud Radio Access Networks With Channel Estimation Errors

Physical layer (PHY) security is recently regarded as a promising technique to improve the security performance of wireless communication networks. Current developments in PHY security are often based on the assumption of perfect channel state information (CSI). In this paper, both security and reliability performance for the downlink cloud radio access network with optimal remote radio heads (RRHs) node selection are investigated in a practical scenario by considering channel estimation (CE) errors. In particular, a three-phase transmission scheme is proposed and the linear minimum mean-square error (MMSE) estimation method is utilized to obtain the CSI. Based on the CSI estimates and the statistics of CE errors, the outage probability and intercept probability are derived in closed-form expression to evaluate the security and reliability performance, respectively. In addition, two possible cases (with or without intercepting signals from baseband unit) are considered for the eavesdropper. It is found that the suggested optimal RRHs selection scheme outperforms the nonselection scheme, and that the increasing number of RRHs can lower the outage probability as well as the intercept probability. It is also shown that there exists an optimal training number to minimize the sum of the outage probability and intercept probability. Finally, simulation results are provided to corroborate our proposed studies.