Line Of Sight Coverage Research Articles

LOS Coverage Area in Vehicular Networks with Cox-Distributed Roadside Units and Relays

We develop an analytical framework to examine the line-of-sight (LOS) coverage area in vehicular networks with roadside units (RSU) and vehicle relays. In practical deployment scenarios, RSUs and vehicle relays are spatially correlated and we characterize this by employing Cox point processes to model the locations of RSUs and vehicle relays simultaneously. Leveraging the random blockage model, we model the LOS coverage area as Boolean models on these Cox point processes. The LOS coverage area is then evaluated by its area fraction. We show that relays can increase the area fraction of LOS coverage by nearly 50% even when RSUs and relays are spatially correlated. By presenting a stochastic geometry model for a vehicular network with RSUs and relays and then by providing a tool to capture its LOS coverage, our work assesses the viability of vehicle relays for modern vehicular networks exploiting LOS coverage.

Service coverage optimization for facility location: considering line-of-sight coverage in continuous demand space

The reliable service coverage of many facilities or sensors used in smart city infrastructure is highly susceptible to obstructions in urban environments. Optimizing the line-of-sight (LOS) service coverage is essential to locating these facilities for smarter city services. Despite progression in the maximal coverage location problem (MCLP) model for locating facilities, maximizing the LOS service coverage in continuous demand space for facility location problems remains challenging. This study defined the LOS-constrained MCLPs (LOS-MCLPs) and proposed a service coverage optimization model to solve these LOS-MCLPs. We employed a computational geometry algorithm named the visibility polygon (VP) algorithm to simulate the LOS coverage in two-dimensional (2D) continuous demand space. We then coupled this algorithm with a robust heuristic algorithm to search for the optimal solutions to maximize effective LOS service coverage. An experiment applied the developed model to a Wi-Fi hotspot planning problem. The experimental results demonstrated that the proposed model can obtain optimal solutions for LOS-MCLPs according to the distribution of obstacles. Comparative results show that ignoring the LOS effect in the optimization of LOS-MCLPs might lead to large areas of service dead zones.

Joint Optimization of IRS and UAV-Trajectory: For Supporting Statistical Delay and Error-Rate Bounded QoS Over mURLLC-Driven 6G Mobile Wireless Networks Using FBC

Massive ultra-reliable and low-latency communications (mURLLC) has been developed as a new and dominating 6G-standard services to support statistical quality of service (QoS) provisioning while raising several major design issues, including massive connectivity, ultra-low latency, and super-reliability. Correspondingly, a number of emerging 6G candidate enablers, including statistical delay and error-rate bounded QoS provisioning, finite blocklength coding (FBC), intelligent reflecting surfaces (IRS), unmanned aerial vehicle (UAV), etc., have been developed to support mURLLC. Specifically, due to the potential improvements in coverage capability as well as the spectral efficiency, both IRS and UAV have been widely proposed to reconfigure wireless propagation environments to compensate for blocked line-of-sight (LOS) communication links and create controllable and smart radio environments. In addition, to solve the massive connectivity issues imposed by mURLLC, integrating UAV with IRS provides a promising means to significantly enhance LOS coverage due to the relatively high altitude and 3D mobility of the UAVs. However, although small-packet communications enabled by FBC are usually employed for massive access to reduce access latency and decoding complexity, how to upper-bound both delay and error rate while efficiently supporting mURLLC in IRS-UAV-integrated systems still remains a challenging problem.

Maximizing Line-of-Sight Coverage for mmWave Wireless LANs With Multiple Access Points

In this paper, we investigate the optimal line-of-sight (LoS) coverage problem for multiple access point (multi-AP) mmWave wireless LANs in indoor scenarios. Due to the weak diffraction ability of mmWave signals at 60 GHz, maintaining LoS communications between APs and client devices is critical to achieve ultra-high data rates with mmWave communications. We focus on the use of multiple APs deployed to maximize LoS coverage in a target area, and we develop multi-AP placements that maximize LoS coverage by means of both analytical and algorithmic methods. We consider two main scenarios, which differ in their assumptions about knowledge of obstacles and clients. In a random-obstacle, random-client scenario, we derive the LoS-optimal positions of APs by solving a thinnest covering problem. For a fixed-obstacle, random-client scenario, we propose an efficient algorithm that produces a multi-AP placement, which is shown through simulation to provide near-optimal LoS coverage. Finally, through extensive ns-3 simulations based on the IEEE 802.11ad protocol and mmWave-specific channel models, we show that our multi-AP placements are significantly better than existing placement approaches, both in terms of LoS coverage and aggregate throughput.

3D Placement and Orientation of mmWave-Based UAVs for Guaranteed LoS Coverage

Unmanned aerial vehicles (UAVs), as aerial base stations, are a promising solution for providing wireless communications, thanks to their high flexibility and autonomy. Moreover, emerging services, such as extended reality, require high-capacity communications. To achieve this, millimeter wave (mmWave), and recently, terahertz bands have been considered for UAV communications. However, communication at these high frequencies requires a line-of-sight (LoS) to the terminals, which may be located in 3D space and may have extremely limited direct-line-of-view (LoV) due to blocking objects, like buildings and trees. In this letter, we investigate the problem of determining 3D placement and orientation of UAVs such that users have guaranteed LoS coverage by at least one UAV and the signal-to-noise ratio (SNR) between the UAV-user pairs are maximized. We formulate the problem as an integer linear programming(ILP) problem and prove its NP-hardness. Next, we propose a low-complexity geometry-based greedy algorithm to solve the problem efficiently. Our simulation results show that the proposed algorithm (almost) always guarantees LoS coverage to all users in all considered simulation settings.

Fingerprinting-assisted UWB-based localization technique for complex indoor environments

Among the numerous radio-based solutions for indoor localization, ultra-wideband (UWB) technology is of particular interest due to its signal characteristics. The wide bandwidth of the UWB signal provides a fine time resolution of the transmitted pulses that enables a centimetre-level ranging accuracy under line-of-sight (LOS) conditions even in multipath intensive indoor environments. Nevertheless, it is still a challenge to implement accurate UWB-based localization in complex multi-room indoor environments at low cost because of a large number of static UWB anchors that may need to be deployed in order to provide an adequate LOS coverage in every segment of the environment. Therefore, there is a strong interest in developing UWB-based localization techniques that will provide acceptable accuracy under partially LOS coverage conditions. In this paper, we present a novel hybrid method that combines two conventional localization techniques, trilateration and fingerprinting, to address the problem of cost-effective UWB-based localization in complex indoor environments. With the proposed method, the target location is determined by a trilateration algorithm, while a fingerprinting-based algorithm is used to provide additional distances for trilateration in cases when there is an insufficient number of available LOS measurements. The additional distances are generated by a non-parametric regression algorithm that relies on a fingerprint database to map all available online range measurements (LOS as well non-LOS) to distances between the target and the set of pre-defined reference points. To minimize human effort in fingerprint collection, the indoor environment is site-surveyed in a room-by-room fashion with auxiliary UWB anchors temporarily placed at up to three reference points in the surveyed room. The method is validated through an extensive indoor measurement campaign with commercially available UWB transceivers. The experimental results show that the proposed method achieves sub-decimetre level localization accuracy under typical real-world conditions.

Coverage and capacity improvement of millimetre wave 5G network using distributed base station architecture

In this work, the distributed base station (DBS) with remote radio head (RRH) is considered as the envisioned architecture of the fifth generation (5G) network. DBS network architecture supports easier scalability for network expansions using remote antennas in the form of RRHs. RRHs have been used in this work in order to compensate for the high path loss and penetration loss that characterise millimetre wave (mmWave) communications. The band of interest is the pioneer band at 26 GHz, which has been recently released for 5G services focused on areas of high traffic demand in the UK. DBS architecture can minimise the number of base stations required for the same quality of service (QoS). An algorithm has been developed for DBS scheduling. In addition to that, the gain of using DBS has been demonstrated in terms of: increasing the user data throughput, decreasing the unnecessary handovers as a result of dense network deployment, increasing the coverage probability in terms of line-of-sight (LoS) coverage, and minimising the impact of shadow fading. The results have shown significant improvement in terms of peak, average, and cell-edge data throughput, and the LoS coverage probability has been improved due to the spatial distribution of RRHs.

Performance analysis of a smart meter node for congestion avoidance and LoS coverage

Smart meters are intelligent next-generation energy meters which are used for measuring energy consumption and transmitting information over a network. In a real-time environment, a smart meter network faces congestion and coverage issues. To connect to the network, a network interface card (NIC) is installed for each smart meter. NICs are hardware components that link a host to a network and acts as both the physical and data link layer. Generally, a single node is connected to a NIC. We found that the use of multiple NICs in a node shows significant improvement over the use of a single NIC to overcome network congestion in a real-time environment. The line of sight (LoS) between the transmitter and the receiver is a coverage issue in a smart meter network, which leads to an increase in the packet loss ratio (PLR). In this work, we address network congestion and the coverage issue through multi-channel capability and maximum LoS with single-and multi-hop nodes respectively. The proposed multi-channel network shows two times improvement in the throughput over the regular system; with additional hardware and approximately 1.5 times lower PLR for Node. The experimental results suggest that for a single-hop node, approximately 30 m is the average distance over which LoS communication is possible, and for multi-hop nodes, the distance is 24 m.