Access Point Placement Research Articles

ISAC‐oriented access point placement in cell‐free mMIMO systems

AbstractIn mobile communication networks for integrated sensing and communication, site planning of access points fundamentally determines both communication quality and sensing performance. This paper aims to tackle the AP placement problem under the setting of cell‐free massive multiple‐input multiple‐output, which represents a promising direction for network architecture evolution. Seeking a balance between the sum‐throughput of communication and the Cramér–Rao lower bound of target sensing, the access points are first pre‐placed by solving a convex optimization and further adjusted with optimal angular geometry. The final step involves employing nearest neighbour projection to refine access point positions in the cell‐free massive multiple‐input multiple‐output system, ensuring alignment with integrated sensing and communication requirements. The numerical results show that the proposed algorithm achieves 90% of the optimal communication sum‐rate and 95% of the optimal target localization accuracy.

Correction: Zhu et al. Energy Efficient Access Point Placement for Distributed Massive MIMO. Network 2022, 2, 288–310

Following publication, concerns were raised regarding the peer-review process related to the publication of this article [...]

Generative Artificial Intelligence Using Machine Learning on Wireless Ad Hoc Networks

In this article, we discuss the use of Generative Artificial Intelligence (GenAI) to improve the efficiency and performance of access to wireless points located in various spaces and specific places, which allows interaction with wireless mesh networks and enables the use of mobile devices to access all types of information in internal environments. Furthermore, we propose the use of generative neural networks, which are one of the pillars of GenAI, since they use a methodology from the perspective of Machine Learning that allows analysis of a large amount of data and detection of certain types of patterns that help in the better placement of access points for improved reception and connectivity. Images (heat maps), access point locations, positioning points, and bandwidth are analyzed, allowing new information to be created. On the other hand, to understand and model the general architecture of the wireless Ad-Hoc network, we use two processes that are part of neural networks, such as Multilayer Perceptron (MLP), and the Radial Basis Function (RBF), which is a function of predictors or independent variables or input variables that allows the prediction error in the output variables of the wireless network architecture to be reduced. Using these two processes does help reduce blind spots in those internal places where the wireless signal does not reach, resulting in a signal drop. Improving internal scenarios with wireless Ad-Hoc networks is what is required for better functioning and performance of the network infrastructure.

Vector Quantization Methods for Access Point Placement in Cell-Free Massive MIMO Systems

Vector Quantization Methods for Access Point Placement in Cell-Free Massive MIMO Systems

Enhancing Indoor Positioning Systems Accuracy with Optimal Placement of Wi-Fi Access Points

The indoor positioning system (IPS) has generated a considerable amount of interest in recent times, and the prosperity of the system's development is heavily reliant on its ability to accurately locate objects. The performance measure is significantly impacted by the location of access points (APs). However, the bulk of previous studies have tended to overlook the matter of optimal AP placement and efficient design for IPS due to the dependence on pre-existing installed APs, which were chiefly formulated for coverage objectives. In this investigation, an optimal placement function - which is reliant on mean and variance - has been developed using received signal strength (RSS) measurements data. The performance evaluation in this research is based on experimentation and compared with currently employed placement methods. The results indicate that the most optimal function value for the suggested method is 1.5714, which is substantially smaller than the values for rectangular, triangular, and triangular II, which are 12.468, 5.5364, and 8.5147, respectively. When the recommended placement strategy is employed instead of the existing ones, the weighted K-nearest algorithm (WKNN) for location error, using average RSS as the fingerprint radio map database, yielded a heightened degree of precision.

Optimizing WiFi Signal Quality Through Access Point Placement Using Genetic Algorithm Method

Optimizing WiFi Signal Quality Through Access Point Placement Using Genetic Algorithm Method

Design and Construction of 2.4 Ghz Omnidirectional Antenna as Wireless LAN Transmitter (Case Study at Bukit Indah Campus, Malikussaleh University)

Communication with a wireless system is one of the mainstay communications so that communication integration is achieved. For this reason, Malikussaleh University provides a wifi network on each campus, one of which is the Bukit Indah campus. So that the achievement of wifi access points on mobile devices needs to be improved so that it is achieved properly. Therefore it is necessary to optimize the placement of access points on the Malikussaleh University wifi network. Modeling an omnidirectional antenna that has a range of 360 ° is one solution. The method applied is to design and build an omnidirectional antenna on the Bukit Indah Campus of Malikussaleh University. Based on simulations on Mobile Radio, the largest network pathloss is 116.2 dB and the smallest is 102.0 dB. The results of omidirectional antenna testing conducted 5 times obtained the largest download speed worth 3.18 Mbps with 314ms ping at a distance of 30 meters and the smallest download speed worth 0.55Mbps with 195ms ping at a distance of 150 meters. The farther the distance of the antenna the lower the ping and packet loss, from the test results obtained an average ping of 267.8ms and the largest packet loss percentage of 0.4%. The ideal distance for this antenna is 30 to 110 meters and can even get a longer distance provided there are no obstacles. With this distance it is ideal for an assembled antenna with makeshift materials that we often encounter in everyday life.

NSGA-II based optimal Wi-Fi access point placement for indoor positioning: A BIM-based RSS prediction

One of the most basic systems required in smart cities are indoor positioning systems that allow positioning of people and objects inside buildings to provide them with suitable location-based services. Due to the existence of Wi-Fi technology infrastructure in most buildings and the fact that most mobile devices are equipped with this technology, indoor positioning systems based on Wi-Fi technology and fingerprinting method are quite popular. Therefore, the optimal placement of Wi-Fi Access Points (APs) is important to maximize the accuracy of indoor positioning. This paper presents a method to generate virtual fingerprints inside buildings by predicting Wi-Fi RSS values using integration of BIM and signal propagation models. The proposed method allows the optimization of the spatial distribution and number of Wi-Fi APs. The experiments reveal improvement in signal propagation modelling to measure RSS, efficient RSS fingerprinting-based IPS in the offline phase, decrease in the number of measurement efforts, and optimization of the spatial distribution of Wi-Fi APs, that finally was resulted in high overall accuracy of the indoor positioning.

Joint Access Point Placement and Power-Channel-Resource-Unit Assignment for IEEE 802.11ax-Based Dense WiFi Network With QoS Requirements

IEEE 802.11ax is the standard for the new generation WiFi networks. In this paper, we formulate the problem of joint access point (AP) placement and power-channel-resource unit assignment for 802.11ax-based dense WiFi. The objective is to minimize the number of APs. Two quality-of-service (QoS) requirements are to be fulfilled: (1) a two-tier throughput requirement which ensures that the throughput of each station is good enough, and (2) a fault tolerance requirement which ensures that the stations could still use WiFi even when some APs fail. We prove that this problem is NP-hard. To tackle this problem, we first develop an analytic model to derive the throughput of each station under the OFDMA mechanism and a widely used interference model. We then design a heuristic algorithm to find high-quality solutions with polynomial time complexity. Simulation results under both fixed-user and mobile-user cases show that: (1) when the area is small (50 x 50 m2), our algorithm gives the optimal solutions; when the area is larger (80 x 60 m2), our algorithm can reduce the number of APs by 34.9-87.7% as compared to the Random and Greedy algorithms. (2) Our algorithm can always get feasible solutions that fulfill the QoS requirements.

R-AP's position-domain model for an RO-receiver and AP placement strategy for an uninterrupted link between the robotic arm and AP in the VLC network.

In the visible light communication (VLC) network, the optical link between the robotic arm and the access point (AP) is easily interrupted due to the random orientation of the receiver on the robotic arm. First, based on the VLC channel model, a position-domain model of reliable AP (R-AP) for a random-orientation receiver (RO-receiver) is proposed. The channel gain of the VLC link between the receiver and the R-AP is non-zero. The tilt-angle range of the RO-receiver is [0,π]. Given the field of view (FOV) angle and the orientation of the receiver, the R-AP's position domain of the receiver can be obtained by this model. Then, based on the R-AP's position-domain model for the RO-receiver, a novel AP placement strategy is proposed. Under this AP placement strategy, the number of R-APs for the RO-receiver is not less than 1, thereby effectively avoiding link interruption caused by the random orientation of receivers. Finally, it is proved by the Monte Carlo method that, under the AP placement strategy proposed in this paper, the VLC link of the receiver on the robotic arm can remain uninterrupted during the movement of the robotic arm.

Fluence-based QMRA model for bacterial photorepair and regrowth in drinking water after decentralized UV disinfection

Ultraviolet disinfection is a promising solution for decentralized drinking water systems such as communal water taps. A potential health risk is enzymatic photorepair of pathogens after UV disinfection, which can result in regrowth of pathogens. Even though photorepair is a known issue, no formal risk assessments have been conducted for photorepair after UV disinfection in drinking water. The main objective was to construct a quantitative microbial risk assessment (QMRA) of photorepair after UV disinfection of drinking water in a decentralized system. UV disinfection and photorepair kinetics for E. coli were modelled using reproducible fluence-based determinations. Impacts of water collection patterns, and wavelength-dependent water container material transmittance, sunlight intensity, and photorepair enzyme absorbance were quantified. After UV disinfection by 16 or 40 mJ/cm2 of < 5-log microorganisms per L, risk of infection did not exceed 1-in-10,000 under conditions permitting E. coli photorepair. Risk from photorepair was less than 1-in-10,000 for photorepair light exposure < 0.75 h throughout the day for UV fluence 16 mJ/cm2 or greater. UV disinfection followed by solar disinfection surpassing photoreactivation during storage reduced risk below 1-in-10,000 for photorepair light exposure > 2.5 h between modelled times of 9 AM – 3 PM. The model can be expanded to other pathogens as UV fluence and photorepair fluence response kinetics become available, and this QMRA can be used to inform the placement of community water access points to reduce risk of photorepair and ensure adequate shelf life of UV disinfected water under safe storage conditions.

Smartphone-based Indoor Navigation for Guidance in Finding Location Buildings Using Measured WiFi-RSSI

This study investigates a Wi-Fi-based indoor navigation system to determine building locations. The system was developed using the fingerprint method from the Received Signal Strength Indication (RSSI) of each Access Point (AP). The main components of a smartphone-based system use data from Wi-Fi and the Global Positioning System (GPS). The system developed for navigation is designed and implemented as an element of a dynamic, seamless mobility planning and building location route guidance application. Building map data is collected from Google Map data and enhanced by coloring the geographic location of buildings displayed on mobile devices. Navigational aids collected from sensors provide trip orientation and position updates. The approach of measuring the distance between known positions is compared to those displayed in the application with the haversine formula to measure the accuracy of the position displayed. A series of experiments were conducted in the Politeknik Negeri Semarang area, Indonesia. The experiment results showed that the Wi-Fi-based indoor positioning system was accurate within 7.050 meters of the error for that location, thus proving the system's usefulness for determining the location of buildings in the campus area. The measurement has not adopted the maximum APs placement for signal coverage and strength, only using the existing APs positions. The temperature nor humidity was neither measured in each area where the AP was installed, which is discussed later. This system can help visitors without asking, even though they have only visited once.

Link-Blockage Model and AP-Placement Scheme for No-Blockage Link between AGV and AP in Logistics–Warehousing VLC Network

In this paper, the blockage problem of the optical link between AGV (autonomous ground vehicles) and AP (access point) in the logistics–warehousing VLC (visible light communication) network is analyzed. First, based on the random geometric model, a link-blockage model is proposed. Given the position of AGV, AP and obstacle, the blockage state of the VLC link between AGV and AP can be obtained through this model. Then, an AP-placement scheme based on the link-blockage model is proposed. Under this AP placement, AGVs in any position have a reliable link that is not affected by obstacles. During the movement of AGV, the VLC link of AGV will not be interrupted by a random blockage. Finally, the effectiveness of the link-blockage model is demonstrated by the shadow method. In this paper, the link outage probability and the data rate under different AP heights, AP spacings and the number of obstacles are simulated. Simulation results show that the VLC link can keep uninterrupted under the AP placement proposed in this paper.

OPTIMIZATION OF ACCESS POINT ARRANGEMENT AND PLACEMENT IN THE INDOOR ROOM OF SMP NEGERI 6 SALATIGA USING GENETIC ALGORITHM

Access points are generally only recommended to load up to 40 clients only. Thus, proper placement and arrangement of access points in a room or building can optimize the signal strength received by users. The purpose of this study is to optimize the arrangement and placement of access points built using the genetic algorithm method. In the system built, the user is required to input the number of populations, iterations and the number of nodes 1 and 2. In the program implementation, the population functions to load the genes resulting from the possible placement of the access point based on the iteration results. The access point placement optimization system using the genetic algorithm method has been successfully implemented, the system can perform calculations in processing the ideal access point placement. Access point placement using genetic algorithms can provide recommendations for network architecture design in terms of the coverage area that needs to be used so that designers can save time on node point design and estimate the ideal price in determining the number of access points for network installation and can assist in determining the required coverage area. ideal for schools.

PENGGUNAAN METODE SIMULATED ANNEALING DAN TRILATERATION UNTUK OPTIMASI PENEMPATAN POSISI TITIK AKSES STUDI KASUS: KANTOR KESYAHBANDARAN DAN OTORITAS PELABUHAN (KSOP) KELAS 1 TANJUNG EMAS

Computer network technology is developing rapidly, and wired networks are being replaced by WiFi technology.&#x0D; The limitation of the WiFi coverage area is the main problem with this technology. Therefore, it is necessary to design for optimal placement of access points.&#x0D; This study analyzes the need for access point placement at KSOP Tanjung Mas Port, Semarang, where the need for internet connection via WiFi is very high.&#x0D; Simulation Annealing and Trilateration method is used in this study to determine the position of the access point. With the point blankspot method can be reduced.

ANALISIS SINYAL WIRELESS DENGAN MAPPING SSID DAN HOTSPOT AREA ACCESS POINT DENGAN METODE PPDIOO DI SMK NEGERI 2 PRAYA TENGAH

The Final Semester Exam at SMK Negeri 2 Praya Tengah still uses a manual exam system, namely using paper and stationery, this requires more time and cost than using a computer/android-based exam system. Currently, SMK Negeri 2 Praya Tengah is in the migration stage from manual semester exams to web/computer-based semester exams, but the quality and signal strength of the internet network at SMK Negeri 2 Praya Tengah is influenced by various kinds of obstacles (interference) and improper location of access point placement. So that the internet network at SMK Negeri 2 Praya Tengah often experiences buffering, disconnected from the internet network and signals with weak strength. From the problems obtained related to the strength and quality of the internet network signal at SMK Negeri 2 Praya Tengah, a wireless signal analysis was carried out using the PPDIOO method to determine the area of the building with a weak or poor signal. The PPDIOO method is a network life cycle consisting of 6 stages: prepare, plan, design, implement, operate and optimize. This study aims to analyze the existing network at SMK Negeri 2 Praya Tengah in order to find out how the signal coverage is from each access point installed in each building at SMK Negeri 2 Praya Tengah.

Modified Vector Quantization for Small-Cell Access Point Placement With Inter-Cell Interference

In this paper, we explore the small-cell uplink access point (AP) placement problem in the context of throughput optimality and provide solutions while taking into consideration inter-cell interference (ICI). First, we briefly review the vector quantization (VQ) approach and related single user throughput-optimal formulations for AP placement. Then, we investigate the small-cell case with multiple users and expose the limitations of mean squared error based VQ for solving this problem. While the Lloyd algorithm from the VQ approach is found not to strictly solve the small-cell case, based on the tractability and quality of the resulting AP placement, we deem it suitable as a simple and appropriate framework to solve more complicated problems. Accordingly, to minimize ICI and consequently enhance achievable throughput, we design two Lloyd-type algorithms, namely the Interference Lloyd algorithm and the Inter-AP Lloyd algorithm, both of which incorporate ICI in their distortion functions. Simulation results show that both of the proposed algorithms provide superior 95%-likely rate over the traditional Lloyd algorithm and the Inter-AP Lloyd algorithm yields a significant increase of up to 36.34% in achievable rate over the Lloyd algorithm.

Strategic placement of access points for message communication in a smart building environment

Strategic placement of access points for message communication in a smart building environment

WOAIP: Wireless Optimization Algorithm for Indoor Placement Based on Binary Particle Swarm Optimization (BPSO)

Optimizing the Access Point (AP) deployment has a great role in wireless applications due to the need for providing an efficient communication with low deployment costs. Quality of Service (QoS), is a major significant parameter and objective to be considered along with AP placement as well the overall deployment cost. This study proposes and investigates a multi-level optimization algorithm called Wireless Optimization Algorithm for Indoor Placement (WOAIP) based on Binary Particle Swarm Optimization (BPSO). WOAIP aims to obtain the optimum AP multi-floor placement with effective coverage that makes it more capable of supporting QoS and cost-effectiveness. Five pairs (coverage, AP deployment) of weights, signal thresholds and received signal strength (RSS) measurements simulated using Wireless InSite (WI) software were considered in the test case study by comparing the results collected from WI with the present wireless simulated physical AP deployment of the targeted building - Computer Science Department at University of Baghdad. The performance evaluation of WOAIP shows an increase in terms of AP placement and optimization distinguished in order to increase the wireless coverage ratio to 92.93% compared to 58.5% of present AP coverage (or 24.5% coverage enhancement on average).

Optimization of Access Point Positioning on Wi-Fi Networks Using the K-Means Clustering Method

Uneven distribution is a common problem in setting up access points where some areas have many signals colliding with each other and others have no signals at all (blank spots). As a result, proper access point positioning on the WI-FI network is required to optimize the number of access points used and the signal strength received while maintaining the same coverage area's functionality. In this study, signal strength measurement is used to obtain the estimated distance using the Received Signal Strength Indicator (RSSI) method. The server analyzes using the K-Means Clustering algorithm to cluster the observation area. The output of this classification is the mapping of dense regions (traffic) and loose regions to determine the coverage areas of each access point. This approach aims to optimize the placement of access points in terms of their number and specifications.