A new algorithm for the placement of WLAN access points based on nonsmooth optimization technique

With the fast-growing demand for mobile services, where to place the access points (APs) for providing uniformly and appropriately distributed signals in a wireless local area network (WLAN) becomes an important issue in the wireless network planning. Basically, AP placement will affect the coverage and strength of signals in a WLAN. The number and locations of APs in a WLAN are often decided on the basis of the trial-and-error method. Based on this method, the network planner first selects suitable locations to place APs through observation, and then keeps changing the locations to improve the signal strength based on the received signal. Such process is complicated, laborious and time-consuming. To overcome this problem, we investigate the back-propagation neural network (BPNN) algorithm to improve over the traditional trial-and-error method. Without increasing the number of APs, our approach only needs to adjust AP locations to overcome weak signal problems and thus increase the signal coverage for the Internet connection anywhere within the area. In our experiment, we established a WLAN on a C campus. Our experiments also indicate that placing APs according to the BPNN provided better signal coverage and met the students’ demands for connecting to the Internet from anywhere in the classroom.

This paper presents an AP (Access Point) placement framework considering indoor location-awareness and AP-based WLAN (Wireless Local Area Networks) performance enhancement. We first develop four objective functions that yield objective goals significant to the optimal AP placement in terms of location-awareness and network performance factors. Then, we develop three meta-heuristic algorithms based on simulated annealing, tabu search, and genetic algorithm. These algorithms generate a near-optimal solution for a given objective function. The performance of the AP placement framework presented in this paper is measured under the environments simulating indoor spaces, and numerical results obtained by experimental evaluation of proposed objective functions and algorithms confirm that the proposed AP placement framework can achieve a near-optimal solution to a given objective function.

Indoor positioning methods based on wireless local area network (WLAN) signal measurements have gained popularity because of high localisation accuracy. These methods use radio‐maps obtained from wireless signal measurement surveys on location grids. Measurement sets from various WLAN access points are called fingerprints and they can be used to identify locations where the measurements are collected. WLAN positioning methods face unexpected changes in signal patterns because of attenuation changes or transient faults in WLAN cards or access points that often make signal strength readings unavailable. This study studies the effect of faulty measurements on the performance of popular state‐of‐the‐art WLAN indoor positioning methods. Additionally, an integrity monitoring preprocessing algorithm is provided that demonstrates a possibility of faulty measurements mitigation for conventional methods such as K‐ nearest‐neighbour. This is achieved by detecting and excluding faulty measurements prior to classification. Performance figures are provided for both simulated and empirical environments.

The deployment of access points (APs) imposes a great impact on the performance of wireless local area networks (WLANs). Although there have been plenty of works on the optimal AP deployment (OAD), however, the issue remains open that how to deploy APs energy-savingly in 3-D environments while considering some practical demands. Therefore, this article investigates the OAD with the objective of minimizing the total AP transmission power while guaranteeing the effective coverage by jointly optimizing the transmission power and location of each AP. Different from existing works, our article fully considers not only real 3-D environments with various obstacles but also the differentiated coverage demand and the restrictions on AP locations. To solve this NP-hard optimization problem, this article first proposes a novel hybrid swarm intelligence optimization algorithm, named PSO-Lévy-DFOA. The computational results on 16 benchmark functions and comprehensive comparisons with other algorithms demonstrate the superior global convergence performance of PSO-Lévy-DFOA. The proposed PSO-Lévy-DFOA-based OAD method is then applied to WLAN planning in a two-story building. It has been shown that the total AP transmission power can be considerably reduced compared to the current deployment while still fulfilling the effective coverage.

In indoor positioning system, the user’s location is estimated based on user fingerprints database collected. The received signal from a user at a certain location is compared with all database entries and the best match is selected as the correct estimation. For a given number of access points (APs), optimizing the locations of APs can significantly improve the performance of user location estimation. In this work, the probability of correct estimation is analyzed based on APs location. Both analytical expressions and numerical results are presented and discussed. It has been shown that the probability of correct estimation is highly affected by the APs locations. Furthermore, a new technique is proposed to remarkably reduce the search-cost when comparing a received user signal to the data-base. The performance of the system is analyzed considering different APs locations, different user locations, and different noise variances. It is shown that user’s location estimation is significantly improved when compared to existing techniques.

This manuscript presents a novel approach based on hybrid optimization techniques for planning Wireless Local Area Networks in two stages: i) network structure design for access point (AP) placement and channel assignment and ii) channel assignment enhancement. We consider two objective functions: network load balance and signal-to-interference-plus-noise ratio; and three hard constraints: maximum AP capacities, client demand attendance, and minimum coverage levels. The proposed algorithm delivers an approximation of the efficient solution set, considering the two functions described above. The results from two scenarios were compared to the following four approaches: two multiobjective evolutionary algorithms, a well-known commercial tool, and a greedy technique. Finally, the solutions were subjected to sensitivity analysis to validate their robustness regarding user mobility and AP failures.

This paper presents the use of a multi-objective genetic algorithm (MOGA) for solving an access point placement problem in a wireless LAN. The aim is to maximize signal coverage over the interested area. The problem has been formulated as a multi-objective optimization problem where the decision variables are derived from the locations of the access points in the target area. The objectives consist of the number of access points and the average SNR over the whole area. The major advantage of using MOGA is that multiple optimal placement configurations for different numbers of access points can be obtained from a single run. A set of solutions provides more alternatives to the network designer. The simulation results indicate that the MOGA is capable of generating a placement result which is superior to that produced using standard placement techniques. In addition, the result assessment has been confirmed using statistical and analyzed data profile.

In recent years, there has been a growing demand in 3G data services, leading to deteriorating 3G service quality. Noting that Wireless Local Area Networks (WLANs) as well as 3G cellular networks are widely available today, WLANs could be effectively utilized to relieve the overload in the 3G networks. On the other hand, use of IEEE 802.11 WLAN Access Points (APs) has proliferated tremendously, resulting in a communication device inside a mobile vehicle to access the Internet. However, using Internet through APs in moving vehicles is challenging since WLAN APs have a short range and are typically not deployed to cover all roads. Several studies have investigated the performance of using intermittently available WLAN connectivity from moving vehicles for data transfers and predictive offloading in WLAN/3G networks. However, these works have not addressed mobility pattern from the viewpoint that drivers' mobility is generally known to have a daily routine. Therefore, in this paper, we consider the user's historical mobility to decide to offload data to WLAN instead of switching to 3G network. The user's application usage pattern is also considered into predicting available WLANs. To evaluate the performance of our offloading algorithm, we analyze the prediction error and conduct simulations. The simulation results show that the proposed algorithm achieves shorter transmission time than the existing schemes that do not consider user's mobility pattern by delivering more data to the WLANs.

Recent demands on affordable, portable wireless communication and computation devices have resulted in exponential growth of wireless networks ranging from Wireless Local Area Networks (WLAN) and Wireless Wide Area Networks (WWAN) to Ad-Hoc and Sensor networks. The major goal of wireless communication is to allow users to communicate together and to have access to global network anytime anywhere. This has led to wide acceptance of infrastructure based cellular networks (WWANs) where mobile stations communicate with a centralized controller, often referred as Access Point (AP) that is connected to the wired networks. On the other hand, WLANs have appeared as dominant popular technologies in many venues including a local area such as an academic campus or an airport terminal. These wireless networks mostly rely on IEEE 802.11 Wi-Fi (Wireless Fidelity) technology and its various derived versions (i.e. 802.11a,b,g). IEEE 802.11 standard supports two operational modes: The infrastructure-based Wireless Local Area Networks (WLANs) and an infrastructure-less Ad-Hoc Networks. A WLAN (Conti, 2003) typically imposes the existence of an AP and normally is connected to the wired networks to provide internet access for mobile devices. Obviously, only one hop link is needed to communicate between mobile devices and AP. In contrast, there is no AP or infrastructure in Ad-Hoc networks. Any two stations can communicate directly when they are in the range of reception of each other. To this end, the stations may use multi-hop routing to deliver their packets to destinations. The ad-hoc protocols (Conti, 2003; Mohapatra & Krishnamurthy, 2005) are self-configured for address and routing in the face of mobility and the network topology may change in each configuration. The multi-hop wireless ad-hoc networks, or multi-hop wireless networks enable wireless networking in the environments where the wired or cellular connections are impossible, inadequate, or cost effective (e.g. battle field, disaster recovery, etc.). The popularity of internet over the last decades has resulted in rapid advancement of demanding applications. The Transmission Control Protocol/Internet Protocol (TCP/IP) (Stevens, 1994) is a well-known de facto protocol in developing today’s internet. Basically, TCP provides a connection-oriented and reliable end-to-end data delivery between two hosts in traditional wired networks. Since TCP is well tuned and due to its wide acceptance in internet, it is desirable to extend and adopt its functionality to wireless networks. On the

This paper investigates the optimal access point (AP) placement (OAPP) in simultaneous broadcast system using orthogonal frequency division multiplexing (OFDM) for high data rate indoor wireless LAN. We aim to determine the best combination of multiple AP placements that minimizes average bit error rate (BER) of terminals when in put information including an indoor configuration, a number APs, and total transmission power is given a priori. Since OAPP is categorized as a hard combinatorial problem with many variables and constraints, we applied a nonlinear optimization scheme called uniform design simulated annealing (UDSA) to search for an approximate optimal solution and analyzed its performance in detail. The simulation results demonstrate that the UDSA algorithm has been successfully applied to OAPP and its effectiveness was also confirmed in comparison with very fast simulated annealing (VFSA) and local search (LS) algorithms.

Indoor positioning methods using location-sensitive features of available wireless signals can achieve high accuracy. In particular, many state-of-the-art methods exploit quite unique sets of location-dependent received signal strength (RSS) measurements from multiple wireless local area network (WLAN) access points (APs), also called as wireless fingerprints. However, reception of signals from WLAN APs is not often stable, and RSS measurements tend to be unavailable due to WLAN card or AP transient effects, limited sensitivity of WLAN cards, and fluctuating attenuation and reflection of signals due to a multipath environment, structural changes and moving objects. In certain hostile scenarios, bogus APs may be installed to disorient WLAN localisation algorithms. In this study, two approaches are proposed to mitigate the impact of faulty signal strength measurements. Performance figures are provided for both simulated and empirical environments in order to support conclusions.

Fingerprint-based localization systems mainly utilize the received signal strength (RSS) to estimate the location of a receiver, and the localization accuracy depends largely on the number and placement of access points (APs). In this paper, we propose a novel method for placing the APs, which aims to minimize the total number of similar fingerprints (SFs) over the entire array of training locations. Minimizing SFs will increase the diversity of RSS array and hence improve localization accuracy. To solve the problem using a simple brute force search would be highly computationally expensive and inefficient. Instead, we propose a heuristic optimization algorithm based on Simulated Annealing (SA). Numerical results are obtained for both the brute force search and the SA based approach. Finally, the proposed algorithm's outputs, i.e., the APs' locations, are used with a K-Nearest Neighbors based localization algorithm, and the resulting localization errors are analyzed.

The Wireless Local Area Networks (WLAN) large-scale deployment is a difficult parameterisation work and it requires automatic planning process with formal models. This paper proposes a solution to this matter and provides a model integrating all useful parameters to estimate the location and parameter settings of such network while optimising network costs and throughput. The access point location, the access point pattern, the antenna orientation, the emitted power and the antenna frequency channel are set in this model which brings together cell and frequency planning features (mix of Automatic Cell Planning (ACP) and Automatic Frequency Planning (AFP) problems). With the formal model description this paper illustrates step by step the process of WLAN planning from the AP location to the effective throughput computation. A fair example is given at each section to didactically emphasise the planning problem and the model we defined. At the end, the optimisation problem is to minimise the economical cost of deployment and the economical cost of throughput loss inside a unique and understandable objective function.

Wireless local area networks (WLANs) for public access need to provide privacy between users and also ensure correct charging where access is based on payment. However, by design, conventional LANs and WLANs provide directs unmediated communications between networked devices at the link layer. The paper presents a method to allow networked client devices to communicate with a network comprising routers and other servers while preventing unmediated communication between the clients on the wireless network. An advantage of the method is that it can be implemented entirely within the WLAN access point as a configurable forwarding policy database. No changes are needed to the WLAN client software or the routers and servers and the communication remains completely within the scope of existing industry standards.

Wireless local area network (WLAN) has changed the paradigm of communication and become ubiquitous. As the number of devices connected to wireless is increasing, it is therefore, essential to find vulnerabilities in the security of wireless networks. In this research WLAN security vulnerabilities are exposed in real time. WLAN security techniques (MAC filtering, Hidden SSID and WPA2) available to residential users were practically exploited. Tenda WiFi wireless access point was set up with MAC filtering, hidden SSID and WPA2 security mechanisms in different combinations in such a way as to add an additional layer of security to previous configuration. Kali Linux version 2017.1 was used as a platform to exploit WLAN networks in real time. In this research, the sensitive information broadcasted by WLAN was utilized to carry out attacks on wireless networks. A practical demonstration of exposing vulnerabilities in MAC filtering, Hidden SSID with MAC filtering and WPA2-PSK with hidden SSID and MAC filtering security mechanisms of AP was carried out in real time. It was observed that the existing security mechanisms were vulnerable. Researchers have exploited many security mechanisms of WLAN focusing upon a single parameter of WLAN security at a time. However, in this work, the three available security mechanisms were cascaded to produce a three layer security mechanism i.e. WPA2 with hidden SSID and MAC filtering. This cascaded model was exploited in real time.