TL;DR: This letter presents a power efficient scheme to design the secure transmit power allocation and the surface reflecting phase shift and proposes an alternative optimization algorithm and the semidefinite programming (SDP) relaxation to deal with this issue.
Abstract: In this letter, we propose intelligent reflecting surface (IRS) aided multi-antenna physical layer security. We present a power efficient scheme to design the secure transmit power allocation and the surface reflecting phase shift. It aims to minimize the transmit power subject to the secrecy rate constraint at the legitimate user. Due to the non-convex nature of the formulated problem, we propose an alternative optimization algorithm and the semidefinite programming (SDP) relaxation to deal with this issue. Also, the closed-form expression of the optimal secure beamformer is derived. Finally, simulation results are presented to validate the proposed algorithm, which highlights the performance gains of the IRS to improve the secure transmission.
TL;DR: Simu5G allows users to simulate the data plane of 5G New Radio deployments, in an end-to-end perspective and including all protocol layers, making it a valuable tool for researchers and practitioners interested in the performance evaluation of5G networks and services.
Abstract: In this article we introduce Simu5G, a new OMNeT++-based model library to simulate 5G networks. Simu5G allows users to simulate the data plane of 5G New Radio deployments, in an end-to-end perspective and including all protocol layers, making it a valuable tool for researchers and practitioners interested in the performance evaluation of 5G networks and services. We discuss the modelling of the protocol layers, network entities and functions, and validate our abstraction of the physical layer using 3GPP-based scenarios. Moreover, we show how Simu5G can be used to evaluate Multi-access Edge Computing (MEC) and Cellular Vehicle-to-everything (C-V2X) services offered through a 5G network.
TL;DR: GNPy is validated by feeding it with data from the network controller and comparing the results to experimental measurements on mixed-fiber, Raman-amplified, multivendor scenarios over the full C-band, showing excellent accuracy in predicting both the optical signal-to-noise ratio and the generalized signal- to-no noise ratio (GSNR).
Abstract: In this paper, we describe the validation of GNPy. GNPy is an open source application that approaches the optical layer according to a disaggregated paradigm, and its core engine is a quality-of-transmission estimator for coherent wavelength division multiplexed optical networks. This software is versatile. It can be used to prepare a request for proposal/request for quotation, as an engine of a what-if analysis on the physical layer, to optimize the network configuration to maximize the channel capacity, and to investigate the capacity and performance of a deployed network. We validate GNPy by feeding it with data from the network controller and comparing the results to experimental measurements on mixed-fiber, Raman-amplified, multivendor scenarios over the full C-band. We then test transmission distances from 400 up to 4000 km, polarization-multiplexed (PM) quadrature phase shift keying, the PM-8 quadrature amplitude modulation (QAM) and PM-16QAM formats, erbium-doped fiber amplifier (EDFA) and mixed Raman–EDFA amplification, and different power levels. We show excellent accuracy in predicting both the optical signal-to-noise ratio and the generalized signal-to-noise ratio (GSNR), within 1 dB accuracy for more than 90% of the 500 experimental samples. We also demonstrate the ability to estimate the transmitted power maximizing the GSNR within 0.5 dB of accuracy.
TL;DR: An overview of the issues that need to be overcome to introduce the terahertz spectrum in mobile networks, from a MAC, network, and transport layer perspective, with consideration on the performance of end-to-end data flows on teraHertz connections.
Abstract: Recent evolutions in semiconductors have brought the terahertz band into the spotlight as an enabler for terabit-per-second communications in 6G networks. Most of the research so far, however, has focused on understanding the physics of terahertz devices, circuitry, and propagation, and on studying physical layer solutions. However, integrating this technology in complex mobile networks requires proper design of the full communication stack, to address link- and system-level challenges related to network setup, management, coordination, energy efficiency, and end-to-end connectivity. This article provides an overview of the issues that need to be overcome to introduce the terahertz spectrum in mobile networks, from a MAC, network, and transport layer perspective, with consideration on the performance of end-to-end data flows on terahertz connections.
TL;DR: In this paper, the authors provide a comprehensive survey on the key medium access control (MAC) layer techniques and physical layer (PHY) techniques being discussed in the Extremely High Throughput (EHT) task group, including the channelization and tone plan, multiple resource units (multiRU) support, 4096 quadrature amplitude modulation (4096-QAM), preamble designs, multiple link operations (e.g., multi-link aggregation and channel access), multiple input multiple output (MIMO) enhancement, multiple access point (multi-AP)
Abstract: With the emergence of 4k/8k video, the throughput requirement of video delivery will keep grow to tens of Gbps. Other new high-throughput and low-latency video applications including augmented reality (AR), virtual reality (VR), and online gaming, are also proliferating. Due to the related stringent requirements, supporting these applications over wireless local area network (WLAN) is far beyond the capabilities of the new WLAN standard – IEEE 802.11ax. To meet these emerging demands, the IEEE 802.11 will release a new amendment standard IEEE 802.11be – Extremely High Throughput (EHT), also known as Wireless-Fidelity (Wi-Fi) 7. This article provides the comprehensive survey on the key medium access control (MAC) layer techniques and physical layer (PHY) techniques being discussed in the EHT task group, including the channelization and tone plan, multiple resource units (multi-RU) support, 4096 quadrature amplitude modulation (4096-QAM), preamble designs, multiple link operations (e.g., multi-link aggregation and channel access), multiple input multiple output (MIMO) enhancement, multiple access point (multi-AP) coordination (e.g., multi-AP joint transmission), enhanced link adaptation and retransmission protocols (e.g., hybrid automatic repeat request (HARQ)). This survey covers both the critical technologies being discussed in EHT standard and the related latest progresses from worldwide research. Besides, the potential developments beyond EHT are discussed to provide some possible future research directions for WLAN.
TL;DR: An overview of the vision of how machine learning will impact the wireless communication systems and the ML methods that have the highest potential to be used in wireless networks are provided.
Abstract: The focus of this white paper is on machine learning (ML) in wireless communications. 6G wireless communication networks will be the backbone of the digital transformation of societies by providing ubiquitous, reliable, and near-instant wireless connectivity for humans and machines. Recent advances in ML research has led enable a wide range of novel technologies such as self-driving vehicles and voice assistants. Such innovation is possible as a result of the availability of advanced ML models, large datasets, and high computational power. On the other hand, the ever-increasing demand for connectivity will require a lot of innovation in 6G wireless networks, and ML tools will play a major role in solving problems in the wireless domain. In this paper, we provide an overview of the vision of how ML will impact the wireless communication systems. We first give an overview of the ML methods that have the highest potential to be used in wireless networks. Then, we discuss the problems that can be solved by using ML in various layers of the network such as the physical layer, medium access layer, and application layer. Zero-touch optimization of wireless networks using ML is another interesting aspect that is discussed in this paper. Finally, at the end of each section, important research questions that the section aims to answer are presented.
TL;DR: Simulation experiments show that AODV protocol is superior to DSR protocol in terms of throughput, average network delay, routing load, packet loss rate, and average routing hops, and is more suitable for network communication needs.
TL;DR: In this paper, the authors describe a standard-compatible LoRa PHY software-defined radio (SDR) prototype based on GNU Radio, which can be used to develop and evaluate receiver algorithms for LoRa.
Abstract: LoRa is the proprietary physical layer (PHY) of LoRaWAN, which is a popular Internet-of-Things (IoT) protocol enabling low-power devices to communicate over long ranges. A number of reverse engineering attempts have been published in the last few years that helped to reveal many of the LoRa PHY details. In this work, we describe our standard-compatible LoRa PHY software-defined radio (SDR) prototype based on GNU Radio. We show how this SDR prototype can be used to develop and evaluate receiver algorithms for LoRa. As an example, we describe the sampling time offset and the carrier frequency offset estimation and compensation blocks. We experimentally evaluate the error rate of LoRa, both for the uncoded and the coded cases, to illustrate that our publicly available open-source implementation is a solid basis for further research.
TL;DR: This article addresses the Release 13 of the NB-IoT 3rd generation partnership project (3GPP) standardized LPWA technology and provides a tutorial on its physical layer (PHY) design and discusses the characteristics and the scheduling of downlink and uplink physical channels at theNB- IoT base station side and the user equipment (UE) side.
Abstract: The Internet of Things (IoT) is transforming the whole of society. It represents the next evolution of the Internet and will significantly improve the ability to gather and analyze data, as well as the ability to control devices remotely. In this respect, the usage of connected devices is continuously growing with the expansion of the applications being offered to individuals and industries. To address IoT market needs, many low-power wide-area (LPWA) technologies have been developed, some operating on licensed frequencies (e.g., narrowband-IoT [NB-IoT] and Long-Term Evolution-M [LTE-M]), and others on unlicensed frequencies (e.g., LoRa, Sigfox, etc.). In this article, we address the Release 13 of the NB-IoT 3rd generation partnership project (3GPP) standardized LPWA technology and provide a tutorial on its physical layer (PHY) design. Specifically, we focus on the characteristics and the scheduling of downlink and uplink physical channels at the NB-IoT base station side and the user equipment (UE) side. The goal is to help readers easily understand the NB-IoT system without having to read all the 3GPP specifications or the state-of-the-art papers that generally describe the system. To this end, each presented concept is followed by examples and concrete use-cases to further aid in the reader’s comprehension. Finally, we briefly describe and highlight the new features added to the NB-IoT system in Releases 14 and 15.
TL;DR: A detailed account of current research on the application of ML in communication networks and important future research challenges are identified and presented to help stir further research in key areas in this direction.
Abstract: The growing network density and unprecedented increase in network traffic, caused by the massively expanding number of connected devices and online services, require intelligent network operations. Machine Learning (ML) has been applied in this regard in different types of networks and networking technologies to meet the requirements of future communicating devices and services. In this article, we provide a detailed account of current research on the application of ML in communication networks and shed light on future research challenges. Research on the application of ML in communication networks is described in: i) the three layers, i.e., physical, access, and network layers; and ii) novel computing and networking concepts such as Multi-access Edge Computing (MEC), Software Defined Networking (SDN), Network Functions Virtualization (NFV), and a brief overview of ML-based network security. Important future research challenges are identified and presented to help stir further research in key areas in this direction.
TL;DR: Wireless protocols are proposed that implement Decentralized Stochastic Gradient Descent by accounting for the presence of path loss, fading, blockages, and mutual interference in the deployment of Federated Learning.
Abstract: Federated Learning (FL), an emerging paradigm for fast intelligent acquisition at the network edge, enables joint training of a machine learning model over distributed data sets and computing resources with limited disclosure of local data. Communication is a critical enabler of large-scale FL due to significant amount of model information exchanged among edge devices. In this paper, we consider a network of wireless devices sharing a common fading wireless channel for the deployment of FL. Each device holds a generally distinct training set, and communication typically takes place in a Device-to-Device (D2D) manner. In the ideal case in which all devices within communication range can communicate simultaneously and noiselessly, a standard protocol that is guaranteed to converge to an optimal solution of the global empirical risk minimization problem under convexity and connectivity assumptions is Decentralized Stochastic Gradient Descent (DSGD). DSGD integrates local SGD steps with periodic consensus averages that require communication between neighboring devices. In this paper, wireless protocols are proposed that implement DSGD by accounting for the presence of path loss, fading, blockages, and mutual interference. The proposed protocols are based on graph coloring for scheduling and on both digital and analog transmission strategies at the physical layer, with the latter leveraging over-the-air computing via sparsity-based recovery.
TL;DR: In this paper, the authors present a PHY abstraction model for 5G New Radio (NR) and its integration into an open-source ns-3 based NR system-level simulator.
Abstract: A physical layer (PHY) abstraction model estimates the PHY performance in system-level simulators to speed up the simulations. This paper presents a PHY abstraction model for 5G New Radio (NR) and its integration into an open-source ns-3 based NR system-level simulator. The model capitalizes on the exponential effective signal-to-interference-plus-noise ratio (SINR) mapping (EESM) and considers the latest NR specification. To generate it, we used an NR-compliant link-level simulator to calibrate the EESM method as well as to obtain SINR-block error rate (BLER) lookup tables for various NR configurations. We also illustrate the usability of the developed model through end-to-end simulations in ns-3, under different NR settings of modulation and coding schemes, hybrid automatic repeat request combining methods, and link adaptation approaches.
TL;DR: This survey provides a comprehensive review in the domain of physical layer authentication (PLA) in wireless communication systems, including the concepts, several key techniques of typical PLA architectures as well as future challenges and research trends in more sophisticated communication systems.
Abstract: Physical layer security (PLS) in wireless communication systems has attracted extensive research attentions in recent years. Unlike cryptography-based methods applied in upper-layer in network, PLS methods are applied in physical layers and can provide information-theoretic security by utilizing the randomness of signals and wireless channels. In this survey, we provide a comprehensive review in the domain of physical layer authentication (PLA) in wireless communication systems, including the concepts, several key techniques of typical PLA architectures as well as future challenges and research trends in more sophisticated communication systems. The survey begins with an overview of the background and basic concepts of PLA, such as the general model of wireless security communication system, typical frameworks of key-based/less PLA systems, and the common attack models. We then discuss the major concerns and key techniques that are applied in PLA systems, where three types of authentication schemes are considered, i.e., the authentication based on channel information, radio-frequency and identity watermarks. Basic models and representative research results about key approaches and techniques applied to the authentication systems above are subsequently covered. Finally, the associated challenges and potential research trends of PLA in future communication systems are presented at the end of the survey paper.
TL;DR: It is proved that the hardware-quality scaling effect vanishes as the number of APs increases in the considered secure cell-free massive MIMO system with active attack, and the optimal power allocation scheme is obtained to maximize the achievable secrecy rate.
Abstract: This paper investigates the effect of hardware impairments on the physical layer security for a cell-free massive multiple-input multiple-output (MIMO) network in the presence of pilot spoofing attack. By employing a classical additive hardware distortion model, the joint hardware impairment effects brought by both access points (APs) and user equipments have been taken into account, whereas the eavesdropper is assumed to be equipped with perfect hardware. Thereby, we derive a closed-form lower bound for the ergodic secrecy rate in the presence of imperfect channel state information. To obtain further insights, we investigate asymptotic secrecy performance under different hardware scaling factors. It proves that the hardware-quality scaling effect vanishes as the number of APs increases in the considered secure cell-free massive MIMO system with active attack. Furthermore, by using continuous approximation and path-following algorithms, the optimal power allocation scheme is obtained to maximize the achievable secrecy rate. Numerical results validate the derived results and the efficiency of the proposed power allocation scheme.
TL;DR: This paper proposes a threshold-based scheduling scheme, where the geographically clustered eavesdroppers with both the colluded and collaborated eavesdropping scenarios are assumed, and deduces that with the proposed scheme, a comparable system performance with regard to the maximal selection scheme can be achieved.
Abstract: Satellite communication (SatCom) has attracted much attention due to its inherent characteristics. Security issues have gained severe concerns in SatCom since it is susceptible to be illegally eavesdropped by malicious ground stations within large-scale wireless coverage. In this paper, we investigate the physical layer security of a multiuser SatCom system in the presence of multiple eavesdroppers. Particularly, we propose a threshold-based scheduling scheme, where the geographically clustered eavesdroppers with both the colluded and collaborated eavesdropping scenarios are assumed. Specifically, closed-form expression for the secrecy outage probability (SOP) is derived for the passive eavesdropping scenario when the channel state information (CSI) of the eavesdroppers is unavailable. Moreover, we obtain a closed-form expression for the average secrecy capacity (ASC) of the considered system under the proposed user scheduling scheme. In order to get further insights of the proposed scheduling scheme at high signal-to-noise ratios (SNRs), the asymptotic analysis for the SOP and ASC is also demonstrated. Moreover, the reduced percentage with respect to number of user examination is also given, which validates the simplicity and efficiency of our proposed scheme compared to the traditional approaches. Numerical results deduce that with the proposed scheme, a comparable system performance with regard to the maximal selection (MS) scheme can be achieved.
TL;DR: The potential impacts of AI on the air interface design and standardization are investigated and the AI-enabled network architecture is first discussed, which may substantially reduce the standardization efforts and costs of wireless communication networks.
Abstract: As 3GPP has completed Release 16 specifications and worldwide 5G commercialization is speeding up, global interest in 6G is starting to grow. An interesting and important question is: will the rapid progress in artificial intelligence (AI) eventually alleviate the tremendous efforts required for future standardization of 6G and beyond? In this article, the potential impacts of AI on the air interface design and standardization are investigated. The AI-enabled network architecture is first discussed. The higher layer, physical layer, and cross-layer design empowered by AI capability are further presented. Based on these designs, the future 6G and beyond are expected to enter into an AI era. For potential new use cases and more challenging requirements, the network is capable of automatic updating the air interface protocols, which may substantially reduce the standardization efforts and costs of wireless communication networks.
TL;DR: In this paper, the problem of power control at the base station for physical-layer broadcasting under quality of service (QoS) constraints at mobile users, by jointly designing the transmit beamforming at the BS and the phase shifts of the RIS units, was investigated.
Abstract: As a recently proposed idea for future wireless systems, intelligent reflecting surface (IRS) can assist communications between entities which do not have high-quality direct channels in between. Specifically, an IRS comprises many low-cost passive elements, each of which reflects the incident signal by incurring a phase change so that the reflected signals add coherently at the receiver. In this paper, for an IRS-aided wireless network, we study the problem of power control at the base station (BS) for physical-layer broadcasting under quality of service (QoS) constraints at mobile users, by jointly designing the transmit beamforming at the BS and the phase shifts of the IRS units. Furthermore, we derive a lower bound of the minimum transmit power at the BS to present the performance bound for optimization methods. Simulation results show that, the transmit power at the BS approaches the lower bound with the increase of the number of IRS units, and is much lower than that of the communication system without IRS.
TL;DR: It is demonstrated that the proposed scheme makes it possible for us to flexibly control authentication performance by adjusting thresholds (for channel gain, phase noise, and decision, respectively) to achieve a required authentication performance in specific MIMO applications.
Abstract: In this paper, we propose a physical layer authentication scheme in heterogeneous coexist multiple-input-multiple-output (MIMO) systems. This scheme utilizes two physical layer features in terms of location-specific channel gains and transmitter-specific phase noise caused by imperfect oscillators to identify transmitters. Three properties of the proposed scheme: covertness, robustness, and security, are analyzed in detail. By using a maximum-likelihood estimator (MLE) and extended Kalman filter (EKF), we estimate channel gains and phase noise, and formulate variances of estimation errors. We also quantize the temporal variations of channel gains and phase noise through the developed quantizers. Based on quantization results and theories of hypothesis testing and stochastic process, we then derive the closed-form expressions for false alarm and detection probabilities with the consideration of quantization errors. Simulations are carried out to validate the theoretical results of the two probabilities. Based on theoretical models, we further demonstrate that the proposed scheme makes it possible for us to flexibly control authentication performance by adjusting thresholds (for channel gain, phase noise, and decision, respectively) to achieve a required authentication performance in specific MIMO applications.
TL;DR: By combining the deep neural network with data augmentation methods, the performance of the proposed multiuser PHY-layer authentication scheme is improved and the training speed is accelerated, even with fewer training samples.
Abstract: Unlike most of the upper layer authentication mechanisms, the physical (PHY) layer authentication takes advantages of channel impulse response from wireless propagation to identify transmitted packages with low-resource consumption, and machine learning methods are effective ways to improve its implementation. However, the training of the machine-learning-based PHY-layer authentication requires a large number of training samples, which makes the training process time consuming and computationally resource intensive. In this article, we propose a data augmented multiuser PHY-layer authentication scheme to enhance the security of mobile-edge computing system, an emergent architecture in the Internet of Things (IoT). Three data augmentation algorithms are proposed to speed up the establishment of the authentication model and improve the authentication success rate. By combining the deep neural network with data augmentation methods, the performance of the proposed multiuser PHY-layer authentication scheme is improved and the training speed is accelerated, even with fewer training samples. Extensive simulations are conducted under the real industry IoT environment and the figures illustrate the effectiveness of our approach.
TL;DR: This work demonstrates the feasibility of RF fingerprinting base stations over the large-scale over-the-air experimental POWDER platform and shows how the approach overcomes the challenges posed by changing channel conditions and protocol choices with 99.86% detection accuracy.
Abstract: 5G and open radio access networks (Open RANs) will result in vendor-neutral hardware deployment that will require additional diligence towards managing security risks. This new paradigm will allow the same network infrastructure to support virtual network slices for transmit different waveforms, such as 5G New Radio, LTE, WiFi, at different times. In this multivendor, multi-protocol/waveform setting, we propose an additional physical layer authentication method that detects a specific emitter through a technique called as RF fingerprinting. Our deep learning approach uses convolutional neural networks augmented with triplet loss, where examples of similar/dissimilar signal samples are shown to the classifier over the training duration. We demonstrate the feasibility of RF fingerprinting base stations over the large-scale over-the-air experimental POWDER platform in Salt Lake City, Utah, USA. Using real world datasets, we show how our approach overcomes the challenges posed by changing channel conditions and protocol choices with 99.86% detection accuracy for different training and testing days.
TL;DR: In this article, a cognitive unmanned aerial vehicle (UAV) communication network is studied by exploiting the high flexibility of a UAV and the possibility of establishing line-of-sight links, and the average secrecy rate of the secondary network is maximized by robustly optimizing the UAV's trajectory and transmit power.
Abstract: Cognitive radio is a promising technology to improve spectral efficiency. However, the secure performance of a secondary network achieved by using physical layer security techniques is limited by its transmit power and channel fading. In order to tackle this issue, a cognitive unmanned aerial vehicle (UAV) communication network is studied by exploiting the high flexibility of a UAV and the possibility of establishing line-of-sight links. The average secrecy rate of the secondary network is maximized by robustly optimizing the UAV’s trajectory and transmit power. Our problem formulation takes into account two practical inaccurate location estimation cases, namely, the worst case and the outage-constrained case. In order to solve those challenging non-convex problems, an iterative algorithm based on $\mathcal {S}$ -Procedure is proposed for the worst case while an iterative algorithm based on Bernstein-type inequalities is proposed for the outage-constrained case. The proposed algorithms can obtain effective suboptimal solutions of the corresponding problems. Our simulation results demonstrate that the algorithm under the outage-constrained case can achieve a higher average secrecy rate with a low computational complexity compared to that of the algorithm under the worst case. Moreover, the proposed schemes can improve the secure communication performance significantly compared to other benchmark schemes.
TL;DR: This article proposes a Gaussian-tag-embedded physical-layer authentication (GTEA) scheme by using a weighted fractional Fourier transform (WFRFT) and shows that with the deliberately designed Gaussian tag, the GTEA scheme is robust against spoofing and replaying attacks.
Abstract: Internet of Things (IoT) is regarded as the fundamental platform for many emerging services, such as smart city, smart home, and intelligent transportation systems. With ever-increasing penetration of IoT, it becomes of great importance to ensure the IoT security, as the security threats are extended from the cyber world to the physical world. In this article, we investigate physical-layer authentication to help verify the identity of IoT entities for preventing unauthorized access to information or service. Specifically, we propose a Gaussian-tag-embedded physical-layer authentication (GTEA) scheme by using a weighted fractional Fourier transform (WFRFT). Through the superimposition of a low-power Gaussian WFRFT tag onto the message signal, the legitimate receiver can verify the authenticity of the received signal at the physical layer, without being detected by adversaries. Moreover, security analysis shows that with the deliberately designed Gaussian tag, the GTEA scheme is robust against spoofing and replaying attacks. In addition, tradeoff analysis and simulation results are provided to demonstrate the capability of the GTEA scheme in achieving reliability of the message delivery, stealth of the embedded tag signal, and balancing the tradeoff among the robustness of user authentication. Moreover, a prototype is further developed using FPGA and experiments are conducted to demonstrate the effectiveness and performance improvement of the proposed GTEA scheme.
TL;DR: A review of current initiatives and system architecture for the convergence of satellite and 5G networks, and various approaches to improve reliability or security at the physical layer for the integrated 5G-satellite networks are investigated.
Abstract: Fifth generation (5G) mobile systems are expected to be integrated with different radio access methods such as satellite components to provide seamless connectivity and ubiquitous coverage for users worldwide. In this article, we first provide a brief review of current initiatives and system architecture for the convergence of satellite and 5G networks. Then, we investigate various approaches to improve reliability or security at the physical layer for the integrated 5G-satellite networks. An effective achievable rate is presented as the key performance indicator to measure the security and reliability trade-off, followed by the implementation of a proposed beamforming scheme. Finally, we present future trends and challenges in integrated 5G-satellite networks.
TL;DR: This work argues for fine-grained mobile endpoint-based wireless measurements to inform a precise congestion control algorithm through a well-defined API to the mobile's cellular physical layer, based on Physical-Layer Bandwidth measurements taken at the Endpoint (PBE-CC).
Abstract: Wireless networks are becoming ever more sophisticated and overcrowded, imposing the most delay, jitter, and throughput damage to end-to-end network flows in today's internet. We therefore argue for fine-grained mobile endpoint-based wireless measurements to inform a precise congestion control algorithm through a well-defined API to the mobile's wireless physical layer. Our proposed congestion control algorithm is based on Physical-Layer Bandwidth measurements taken at the Endpoint (PBE-CC), and captures the latest 5G New Radio innovations that increase wireless capacity, yet create abrupt rises and falls in available wireless capacity that the PBE-CC sender can react to precisely and very rapidly. We implement a proof-of-concept prototype of the PBE measurement module on software-defined radios and the PBE sender and receiver in C. An extensive performance evaluation compares PBE-CC head to head against the leading cellular-aware and wireless-oblivious congestion control protocols proposed in the research community and in deployment, in mobile and static mobile scenarios, and over busy and quiet networks. Results show 6.3% higher average throughput than BBR, while simultaneously reducing 95th percentile delay by 1.8x.
TL;DR: Design for the first time its physical layer, accounting for modulation, coding, message split, adaptive modulation and coding, and SIC receiver is designed, confirming the significant throughput benefits of RSMA over various baselines as SDMA and NOMA.
Abstract: Rate-Splitting Multiple Access (RSMA) is an emerging flexible, robust and powerful multiple access scheme for downlink multi-antenna wireless networks. RSMA relies on multi-antenna Rate-Splitting (RS) strategies at the transmitter and Successive Interference Cancellation (SIC) at the receivers, and has the unique ability to partially decode interference and partially treat interference as noise so as to softly bridge the two extremes of fully decoding interference (as in Non-Orthogonal Multiple Access, NOMA) and treating interference as noise (as in Space Division Multiple Access, SDMA or Multi-User Multiple-Input Multiple-Output, MU-MIMO). RSMA has been shown to provide significant room for spectral efficiency, energy efficiency, Quality-of-Service enhancements, robustness to Channel State Information (CSI) imperfections, as well as feedback overhead and complexity reduction, in a wide range of network loads (underloaded and overloaded regimes) and user deployments (with a diversity of channel directions, channel strengths and qualities). RSMA is also deeply rooted and motivated by recent advances in understanding the fundamental limits of multi-antenna networks with imperfect CSI at the Transmitter (CSIT). In this work, we leverage recent results on the optimization of RSMA and design for the first time its physical layer, accounting for modulation, coding (using polar codes), message split, adaptive modulation and coding, and SIC receiver. Link-level evaluations confirm the significant throughput benefits of RSMA over various baselines as SDMA and NOMA.
TL;DR: Compared with traditional MIMO systems, the RIS-aided system offers better performance in terms of physical layer security, and adopting RIS equipped with a small number of reflecting elements cannot improve the system performance when the path loss of NLoS is small.
Abstract: Reconfigurable intelligent surface (RIS)-aided wireless communications have drawn significant attention recently. We study the physical layer security of the downlink RIS-aided transmission framework for randomly located users in the presence of a multi-antenna eavesdropper. To show the advantages of RIS-aided networks, we consider two practical scenarios: Communication with and without RIS. In both cases, we apply the stochastic geometry theory to derive exact probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-interference-plus-noise ratio. Furthermore, the obtained PDF and CDF are exploited to evaluate important security performance of wireless communication including the secrecy outage probability, the probability of nonzero secrecy capacity, and the average secrecy rate. Monte-Carlo simulations are subsequently conducted to validate the accuracy of our analytical results. Compared with traditional MIMO systems, the RIS-aided system offers better performance in terms of physical layer security. In particular, the security performance is improved significantly by increasing the number of reflecting elements equipped in a RIS. However, adopting RIS equipped with a small number of reflecting elements cannot improve the system performance when the path loss of NLoS is small.
TL;DR: This paper proposes a novel PHY layer approach called SCLoRa, which utilizes cumulative spectral coefficient, which integrates both frequency and power information, to separate symbols in the overlapped signal, and implements and evaluates SCLiRa on USRP B210 base stations and commodity LoRa devices.
Abstract: LoRa as a representative of Low-Power Wide Area Networks (LPWAN) technologies has emerged as an attractive communication platform for the Internet of Things. Since its dense deployment, signal collisions at base stations caused by concurrent transmissions degrade network performance. Existing approaches utilize the signal feature, e.g., frequency, to separate packets from collisions. They do not work well in burst traffic networks because the feature is not stable or fine-grained enough and the information for directed signal separation is not sufficient. In this paper, we leverage multidimensional information and propose a novel PHY layer approach called SCLoRa to decode collided LoRa transmissions. SCLoRa utilizes cumulative spectral coefficient, which integrates both frequency and power information, to separate symbols in the overlapped signal. The practical factors of channel fading, similar symbol boundary, and spectrum leakage are taken into account. The SCLoRa design requires neither hardware nor firmware changes in commodity devices – a feature allowing fast deployment on LoRa base stations. We implement and evaluate SCLoRa on USRP B210 base stations and commodity LoRa devices (i.e., SX1278). The experiment results in different scenarios with different radio parameters show that the throughput of SCLoRa is 3× than the state-of-the-art.
TL;DR: This paper proposes a simple yet effective method to improve the Quality-of-Service (QoS) of LoRaWAN networks by fine-tuning specific radio parameters, and approaches the practical aspects of how to implement and integrate the optimization mechanism proposed in LoRa, guaranteeing backward compatibility with the standard protocol.
Abstract: Low Power Wide Area Networks (LPWAN) enable a growing number of Internet-of-Things (IoT) applications with large geographical coverage, low bit-rate, and long lifetime requirements. LoRa (Long Range) is a well-known LPWAN technology that uses a proprietary Chirp Spread Spectrum (CSS) physical layer, while the upper layers are defined by an open standard—LoRaWAN. In this paper, we propose a simple yet effective method to improve the Quality-of-Service (QoS) of LoRaWAN networks by fine-tuning specific radio parameters. Through a Mixed Integer Linear Programming (MILP) problem formulation, we find optimal settings for the Spreading Factor (SF) and Carrier Frequency (CF) radio parameters, considering the network traffic specifications as a whole, to improve the Data Extraction Rate (DER) and to reduce the packet collision rate and the energy consumption in LoRa networks. The effectiveness of the optimization procedure is demonstrated by simulations, using LoRaSim for different network scales. In relation to the traditional LoRa radio parameter assignment policies, our solution leads to an average increase of 6% in DER, and a number of collisions 13 times smaller. In comparison to networks with dynamic radio parameter assignment policies, there is an increase of 5%, 2.8%, and 2% of DER, and a number of collisions 11, 7.8 and 2.5 times smaller than equal-distribution, Tiurlikova’s (SOTA), and random distribution, respectively. Regarding the network energy consumption metric, the proposed optimization obtained an average consumption similar to Tiurlikova’s, and 2.8 times lower than the equal-distribution and random dynamic allocation policies. Furthermore, we approach the practical aspects of how to implement and integrate the optimization mechanism proposed in LoRa, guaranteeing backward compatibility with the standard protocol.
TL;DR: WiTAG is designed to send data by selectively interfering with subframes (MPDUs) in an aggregated frame (A-MPDU) which enables standard compliant communication using modern, open or encrypted 802.11n and802.11ac networks without requiring hardware or software modifications to any devices.
Abstract: WiFi backscatter communication has the potential to enable battery-free sensors which can transmit data using a WiFi network. In order for WiFi backscatter systems to be practical they should be compatible with existing WiFi networks without any hardware or software modifications. Moreover, they should work with networks that use encryption. In this paper, we present WiTAG which achieves these requirements, making the implementation and deployment of WiFi backscatter communication more practical. In contrast with existing systems which utilize the physical layer for backscatter communication, we take a different approach by leveraging features of the MAC layer to communicate. WiTAG is designed to send data by selectively interfering with subframes (MPDUs) in an aggregated frame (A-MPDU). This enables standard compliant communication using modern, open or encrypted 802.11n and 802.11ac networks without requiring hardware or software modifications to any devices. We implement WiTAG using off-the-shelf components and evaluate its performance in line-of-sight and non-line-of-sight scenarios. We show that WiTAG achieves a throughput of up to 4 Kbps without impacting other devices in the network.
TL;DR: This article discusses the concept of a "THz-wireless fiber extender" in more detail and reports on the recent demonstration of a real-time, short-range THz- wireless Fiber extender with 100 Gb/s net capacity, and analyzes the effect of weather conditions on the transmission performance and determines the maximum physical layer net data rate.
Abstract: Using the concept of a "THz-wireless fiber extender," we can combine the flexibility of wireless networks with the high capacity of fiber optic communication. The availability of a large, contiguous bandwidth in the frequency band around 300 GHz creates the opportunity to seamlessly interconnect coherent THz-wireless and fiber optic transceiver frontends using a transparent, analog baseband interface. In this article, we discuss this concept in more detail and report on the recent demonstration of a real-time, short-range THz-wireless fiber extender with 100 Gb/s net capacity. This combined fiber optic/THz-wireless transmission system is operated by a high-speed fiber optic real-time modem, which is capable of compensating the channel impairments of both the optical and THz-wireless links. In addition, we discuss the potential of THz-wireless links to achieve long-range transmission distances by reporting on the operation of a 500-m-long line-of-sight THz-wireless outdoor link in Berlin, Germany. We analyze the effect of weather conditions on the transmission performance and determine the maximum physical layer net data rate of the system by means of various modulation formats and symbol rates. Finally, we summarize all of our recent high-capacity experiments using THz-wireless transmission, including a field trial with a 1-km-long link, and compare our results to theoretical limits and achieved data rates in the laboratory.