The path-loss exponent (PLE) is one of the most crucial parameters in wireless communications to characterize the propagation of fading channels. It is currently adopted for many different kinds of wireless network problems such as power consumption issues, modelling the communication environment, and received signal strength (RSS)-based localization. PLE estimation is thus of great use to assist in wireless networking. However, a majority of methods to estimate the PLE require either some particular information of the wireless network, which might be unknown or some external auxiliary devices, such as anchor nodes or the Global Positioning System. Moreover, this external information might sometimes be unreliable, spoofed, or difficult to obtain. Therefore, a self-estimator for the PLE, which is able to work independently, becomes an urgent demand to robustly and securely get a grip on the PLE for various wireless network applications. This paper is the first to introduce two methods that can solely and locally estimate the PLE. To start, a new linear regression model for the PLE is presented. Based on this model, a closed-form total least squares (TLS) method to estimate the PLE is first proposed, in which, with no other assistance or external information, each node can estimate the PLE merely by collecting RSSs. Second, to suppress the estimation errors, a closed-form weighted TLS method is further developed, having a better performance. Due to their simplicity and independence of any auxiliary system, our two proposed methods can be easily incorporated into any kind of wireless communication stack. Simulation results show that our estimators are reliable, even in harsh environments, where the PLE is high. Many potential applications are also explicitly illustrated in this paper, such as secure RSS-based localization, kth nearest neighbour routing, etc.
Wireless communication in millimetre wave bands, namely above 20 GHz and up to 300 GHz, is foreseen as a key enabler technology for the next generation of wireless systems. The huge available bandwidth is contemplated to achieve high data-rate wireless communications, and hence, to fulfil the requirements of future wireless networks. In this paper, we discuss and illustrate new paradigms for the sub-THz physical layer, which either aim at maximizing the spectral efficiency, minimizing the device complexity, or finding good tradeoff. The solutions offered by appropriate modulation schemes and m…
Fifth-generation (5G) cellular systems are likely to operate in the centimeter-wave (3-30 GHz) and millimeter-wave (30-300 GHz) frequency bands, where a vast amount of underutilized bandwidth exists world-wide. To assist in the research and development of these emerging wireless systems, a myriad of measurement studies have been conducted to characterize path loss in urban environments at these frequencies. The standard theoretical free space (FS) and Stanford University Interim (SUI) empirical path loss models were recently modified to fit path loss models obtained from measurements performed…
School of Electronic Science（电子科学学院）；National University of Defense Technology（国防科技大学）
This letter illustrates our preliminary works in deep nerual network (DNN) for wireless communication scenario identification in wireless multi-path fading channels. In this letter, six kinds of channel scenarios referring to COST 207 channel model have been performed. 100% identification accuracy has been observed given signal-to-noise (SNR) over 20dB whereas a 88.4% average accuracy has been obtained where SNR ranged from 0dB to 40dB. The proposed method has tested under fast time-varying conditions, which were similar with real world wireless multi-path fading channels, enabling it to work …
WEKP-PLP: A Wireless Environment Knowledge Pool-Enhanced Path Loss Prediction Framework for Shore-to-Ship Communication
Beijing University of Posts and Telecommunications（北京邮电大学）；Inner Mongolia University（内蒙古大学）；China Information Technology Designing & Consulting Institute Co., Ltd.（中国信息技术设计咨询有限公司）
State-of-the-art device-free localization systems infer presence and location of users based on received signal strength measurements of line-of-sight links in wireless networks. In this letter, we propose to enhance device-free localization systems by exploiting multipath propagation between the individual network nodes. Particularly indoors, wireless propagation channels are characterized by multipath propagation, i.e., received signals comprise multipath components due to reflection and scattering. Given prior information about the surrounding environment, e.g., a floor plan, the individual…
We investigate the existence of 'long-memory' or long-range dependence (LRD) of the wireless body-centric channels, e.g., on-body, body-to-body (B2B), with real-life experimental dataset collected from 10 co-located wireless body area networks or BANs (people fitted with wearable sensors). We examine two different factors on that purpose such as: the pattern of the decaying autocorrelation function (ACF) and the Hurst exponent. From the experimental outcome, we show that, the ACF decay of the body-centric channels follows a power-like decay and the channels have a Hurst exponent much greater t…
For UAV-aided wireless systems, online path planning attracts much attention recently. To better adapt to the real-time dynamic environment, we, for the first time, propose a Monte Carlo Tree Search (MCTS)-based path planning scheme. In details, we consider a single UAV acts as a mobile server to provide computation tasks offloading services for a set of mobile users on the ground, where the movement of ground users follows a Random Way Point model. Our model aims at maximizing the average throughput under energy consumption and user fairness constraints, and the proposed timesaving MCTS algor…
In this paper, multiple reconfigurable intelligent surfaces (RIS) aided secure precise wireless transmission (SPWT) schemes are proposed in the three-dimensional (3D) wireless communication scenario. Unavailable direct path channels from transmitter to receivers are considered when the direct paths are obstructed by obstacles. Then, multiple RISs are utilized to achieve SPWT through the reflection path among transmitter, RISs and receivers in order to enhance the communication performance and energy efficiency simultaneously. First, a maximum-signal-to-interference-and-noise ratio (MSINR) sche…
In the recent years, the proliferation of wireless data traffic has led the scientific community to explore the use of higher unallocated frequency bands, such as the millimeter wave and terahertz (0.1-10 THz) bands. However, they are prone to blockages from obstacles laid in the transceiver path. To address this, in this work, the use of a reconfigurable-intelligent-surface (RIS) to restore the link between a transmitter (TX) and a receiver (RX), operating in the D-band (110-170 GHz) is investigated. The system performance is evaluated in terms of pathgain and capacity considering the RIS des…
Next generation in-to-out-of body biomedical applications have adopted optical wireless communications (OWCs). However, by delving into the published literature, a gap is recognised in modeling the in-to-out-of channel, since most published contributions neglect the particularities of different type of tissues. Towards this direction, in this paper we present a novel pathloss and scattering models for in-to-out-of OWC links. Specifically, we derive extract analytical expressions that accurately describe the absorption of the five main tissues' constituents, namely fat, water, melanin, oxygenat…
The classic wireless communication channel modeling is performed using Deterministic and Stochastic channel methodologies. Machine learning (ML) emerges to revolutionize system design for 5G and beyond. ML techniques such as supervise leaning methods will be used to predict the wireless channel path loss of a variate of environments base on a certain dataset. The propagation signal of communication systems fundamentals is focusing on channel modeling particularly for new frequency bands such as MmWave. Machine learning can facilitate rapid channel modeling for 5G and beyond wireless communicat…
Up until now, path planning for unmanned aerial vehicles (UAVs) has mainly been focused on the optimisation towards energy efficiency. However, to operate UAVs safely, wireless coverage is of utmost importance. Currently, deployed cellular networks often exhibit an inadequate performance for aerial users due to high amounts of intercell interference. Furthermore, taking the never-ending trend of densification into account, the level of interference experienced by UAVs will only increase in the future. For the purpose of UAV trajectory planning, wireless coverage should be taken into account to…
Millimeter wave (mmWave) bands have been utilized for the fifth generation (5G) communication systems and will no doubt continue to be deployed for beyond 5G (B5G). However, the underlying channels are not fully investigated at multifrequency bands and in multi-scenarios by using the same channel sounder, especially for the outdoor, multiple-input multiple-output (MIMO), and vehicle-to-vehicle (V2V) conditions. In this paper, we conduct multi-frequency multi-scenario mmWave MIMO channel measurements with 4*4 antennas at 28, 32, and 39 GHz bands for three cases, i.e., the human body and vehicle…
Underwater wireless optical communication is one of the critical technologies for buoy-based high-speed cross-sea surface communication, where the communication nodes are vertically deployed. Due to the vertically inhomogeneous nature of the underwater environment, seawater is usually vertically divided into multiple layers with different parameters that reflect the real environment. In this work, we consider a generalized UWOC channel model that contains$N$ layers. To capture the effects of air bubbles and temperature gradients on channel statistics, we model each layer by a mixture Exponenti…
Reconfigurable intelligent surfaces (RISs) comprised of tunable unit cells have recently drawn significant attention due to their superior capability in manipulating electromagnetic waves. In particular, RIS-assisted wireless communications have the great potential to achieve significant performance improvement and coverage enhancement in a cost-effective and energy-efficient manner, by properly programming the reflection coefficients of the unit cells of RISs. In this paper, free-space path loss models for RIS-assisted wireless communications are developed for different scenarios by studying …
Non-orthogonal multiple access (NOMA) scheme enables serving users with the same resource block i.e. frequency or time by multiplexing the signal of the users. Intelligent reflecting surfaces (IRS) or reconfigurable intelligent surfaces (RIS) is a potential approach for increasing transmission efficiency by modifying signal propagation by tweaking typically passive reflective components. IRS reconfigures the wireless network in this manner to improve system performance. The research considered an IRS-assisted downlink NOMA system. This work modified the reference model by adopting an IRS-speci…
Intelligent surfaces exert deterministic control over the wireless propagation phenomenon, enabling novel capabilities in performance, security and wireless power transfer. Such surfaces come in the form of rectangular tiles that cascade to cover large surfaces such as walls, ceilings or building facades. Each tile is addressable and can receive software commands from a controller, manipulating an impinging electromagnetic wave upon it by customizing its reflection direction, focus, polarization and phase. A new problem arises concerning the orchestration of a set of tiles towards serving end-…
Faculty of Information Technology, Monash University, Australia（澳大利亚莫纳什大学信息技术学院）
This paper describes a reflexive multilayered mission planner with a mounted energy efficient local path planner for Unmanned Underwater Vehicle's (UUV) navigation throughout the complex subsea volume in a time-variant semi-dynamic operation network. The UUV routing protocol in Underwater Wireless Sensor Network (UNSW) is generalized with a homogeneous Dynamic Knapsack-Traveler Salesman Problem emerging with an adaptive path planning mechanism to address UUV's long-duration missions on dynamically changing subsea volume. The framework includes a base layer of global path planning, an inner lay…
In wireless systems aided by reconfigurable intelligent surfaces (RISs), channel state information plays a pivotal role in achieving the performance gain of RISs. Mobility renders accurate channel estimation (CE) more challenging due to the Doppler effect. In this letter, we propose two practical wideband CE schemes incorporating Doppler shift adjustment (DSA) for multi-path and single-path propagation environments, respectively, for RIS-assisted communication with passive reflecting elements. For the multi-path scenario, ordinary CE is first executed assuming quasi-static channels, followed b…
Simple and accurate expressions for path gain are derived from electromagnetic fundamentals in a wide variety of common environments, including Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) indoor urban canyons, urban/rural macro, outdoor-indoor and suburban streets with vegetation. Penetration into a scattering region, sometimes aided by guiding, is the "universal" phenomenon shared by the diverse morphologies. Root Mean Square (RMS) errors against extensive measurements are under 5 dB, better than 3GPP models by 1-12 dB RMS, depending on environment. In urban canyons the models have 4.7 d…
Prior studies on intelligent reflecting surface (IRS) have mostly considered wireless communication systems aided by a single passive IRS, which, however, has limited control over wireless propagation environment and suffers severe product-distance path-loss. To address these issues, we propose in this paper a new multi-active multi-passive (MAMP)-IRS aided wireless communication system, where a number of active and passive IRSs are deployed to assist the downlink communication in complex environment, by establishing a multi-hop reflection path across active and passive IRSs. An optimization p…
NYU Tandon School of Engineering（纽约大学坦登工程学院）；University of British Columbia（不列颠哥伦比亚大学）；Harvard University（哈佛大学）
The millimeter wave (mmWave) bands have attracted considerable attention for high precision localization applications due to the ability to capture high angular and temporal resolution measurements. This paper explores mmWave-based positioning for a target localization problem where a fixed target broadcasts mmWave signals and a mobile robotic agent attempts to capture the signals to locate and navigate to the target. A three-stage procedure is proposed: First, the mobile agent uses tensor decomposition methods to detect the multipath channel components and estimate their parameters. Second, a…
Outdoor-to-indoor (OtI) signal propagation further challenges the already tight link budgets at millimeter-wave (mmWave). To gain insight into OtI mmWave scenarios at 28 GHz, we conducted an extensive measurement campaign consisting of over 2,200 link measurements. In total, 43 OtI scenarios were measured in West Harlem, New York City, covering seven highly diverse buildings. The measured OtI path gain can vary by up to 40 dB for a given link distance, and the empirical path gain model for all data shows an average of 30 dB excess loss over free space at distances beyond 50 m, with an RMS fitt…
Reconfigurable Intelligent Surfaces (RIS) or Intelligent Reflecting Surfaces (IRS) are metasurfaces that can be deployed in various places in wireless environments to make these environments controllable and reconfigurable. In this paper, we investigate the problem of using 3D beamforming in RIS-empowered wireless networks and propose a new scheme that provides more degrees of freedom in designing and deploying the RIS-based networks. In the proposed scheme, a base station (BS) equipped with a full dimensional array of antennas optimizes its radiation pattern in the three-dimensional space to …
EURECOM（欧洲通信学院）；Technical University of Munich（慕尼黑工业大学）
Autonomous deployment of unmanned aerial vehicles (UAVs) supporting next-generation communication networks requires efficient trajectory planning methods. We propose a new end-to-end reinforcement learning (RL) approach to UAV-enabled data collection from Internet of Things (IoT) devices in an urban environment. An autonomous drone is tasked with gathering data from distributed sensor nodes subject to limited flying time and obstacle avoidance. While previous approaches, learning and non-learning based, must perform expensive recomputations or relearn a behavior when important scenario paramet…
