Loss Diagnosis and Indoor Position Location System based on IEEE 802.11 WLANs

Wireless local area networks (WLANs) have been widely deployed to provide short range broadband communications. Due to the fast evolvement of IEEE 802.11 based WLAN standards and various relevant applications, many research efforts have been focused on the optimization of WLAN data rate, power and channel utilization efficiency. On the other hand, many emerging applications based on WLANs have been introduced. Indoor position location (IPL) system is one of such applications which turns IEEE 802.11 from a wireless communications infrastructure into a position location network. This thesis mainly focuses on data transmission rate enhancement techniques and the development of IEEE 802.11 WLAN based IPL system with improved locationing accuracy. In IEEE 802.11 systems, rate adaptation algorithms (RAAs) are employed to improve transmission efficiency by choosing an appropriate modulation and coding scheme accord­ ing to point-to-point channel conditions. However, due to the resource-sharing nature of WLANs, co-channel interferences and frame collisions cannot be avoided, which further complicates the wireless environment and makes the RAA design a more challenging task. As WLAN performance depends on many dynamic factors such as multipath fading and co-channel interferences, differentiating the cause of performance degradation such as frame losses, which is known as loss diagnosis techniques, is essential for performance enhance­ ments of existing rate adaptation schemes. In this thesis, we propose a fast and reliable collision detection scheme for frame loss diagnosis in IEEE 802.11 WLANs. Collisions are detected by tracking changes of the signal-to-interference-and-noise-ratio (SINR) in IEEE 802.11 WLANs with a nonparametric order-based cumulative sum (CUSUM) algorithm for rapid loss diagnosis. Numerical simulations are conducted to evaluate the effectiveness of the proposed collision detection scheme. The other aspect of this thesis is the investigation of an IEEE 802.11 WLAN based IPL system. WLAN based IPL systems have received increasing attentions due to their variety of potential applications. Instead of relying on dedicated locationing networks and devices, IEEE 802.11 WLAN based IPL systems utilize widely deployed IEEE 802.11 WLAN infrastructures and standardized wireless stations to determine the position of a target station in indoor environments. iii Abstract In this thesis, a WLAN protocol-based distance measurement technique is investigated, which takes advantages of existing IEEE 802.11 data/ACK frame exchange sequences. In the proposed distance measurement technique, neither dedicated hardware nor hardware modifications is required. Thus it can be easily integrated into off-the-shelf commercial, inexpensive WLAN stations for IPL system implementation. Field test results confirm the efficacy of the proposed protocol-based distance measurement technique. Furthermore, a preliminary IPL system based on the proposed method is also developed to evaluate the feasibility of the proposed technique in realistic indoor wireless environments

Distributed localisation algorithm for wireless ad hoc networks of moving nodes

Existing ad hoc network localisation solutions rely either on external location references or network-wide exchange of information and centralised processing and computation of location estimates. Without these, nodes are not able to estimate the relative locations of other nodes within their communication range. This thesis defines a new distributed localisation algorithm for ad hoc networks of moving nodes. The Relative Neighbour Localisation (RNL) algorithm works without any external localisation signal or systems and does not assume centralised information processing. The idea behind the location estimates produced by the RNL algorithm is the relationship between the relative locations of two nodes, their mobility parameters and the signal strengths measured between them. The proposed algorithm makes use of the data available to each node to produce a location estimate. The signal strength each node is capable of measuring is used as one algorithm input. The other input is the velocity vector of the neighbouring node, composed of its speed and direction of movement, which each node is assumed to periodically broadcast. The relationship between the signal strength and the mobility parameters on one, and the relative location on the other side can be analytically formulated in an ideal case. The limitations of a realistic scenario complicate this relationship, making it very difficult to formulate analytically. An empirical approach is thus used. The angle and the distance estimates are individually computed, together forming a two-dimensional location estimate. The performance of the algorithm was analysed in detail using simulation, showing a median estimate error of under 10m, and its application was tested through design and evaluation of a distributed sensing coverage algorithm, showing RNL location estimates can provide 90% of the coverage achievable with true locations being known