Channel quality estimation and impairment mitigation in 802.11 networks

Wireless communication has been boosted by the adoption of 802.11 as standard de facto for WLAN transmission. Born as a niche technology for providing wireless connectivity in small office/enterprise environments, 802.11 has in fact become a common and cheap access solution to the Internet, thanks to the large availability of wireless gateways (home modems, public hot-spots, community networks, and so on). Nowdays, the trend towards increasingly dense 802.11 wireless deployments is creating a real need for effective approaches for channel allocation/hopping, power control, etc. for interference mitigation while new applications such mesh networks in outdoor contexts and media distribution within the home are creating new quality of service demands that require more sophisticated approaches to radio resource allocation. The new framework of WLAN deployments require a complete understanding of channel quality at PHY and MAC layer. Goal of this thesis is to assess the MAC/PHY channel quality and mitigate the different channel impairments in 802.11 networks, both in dense/controlled indoor scenarios and emerging outdoor contexts. More specifically, chapter 1 deals with the necessary background material and gives insight into the different channel impairments/quality it can be encountered in WLAN networks. Then the thesis pursues a down/top approach: chapter 2, 3 and 4 aim at affording impairments/quality at PHY level, while chapter 5 and 6 analyse channel impairments/quality from a MAC level perspective. An important contribution of this thesis is to undisclose that some PHY layer parameters, such as the transmission power, the antenna selection, and interference mitigation scheme, have a deep impact on network performance. Since the criteria for selecting these parameters is left to the vendor specific implementations, the performance spread of most experimental results about 802.11 WLAN could be affected by vendor proprietary schemes. Particularly, in chapter 2 we find that switching transmit diversity mechanisms implemented in off-the-shelf devices with two antenna connectors can dramatically affect both performance and link quality probing mechanisms in outdoor medium-range WLAN deployments, whenever one antenna deterministically works worse than the other one. A second physical algorithm with side-effects is shown in chapter 3. Particulary the chapter shows that interference mitigation algorithms may play havoc with the link-level testbeds, since they may erroneously lower the sensitivity threshold, and thus not detect the 802.11 transmit sources. Finally, once disabled the interference mitigation algorithm — as well as any switching diversity scheme described in the previous chapter — link-level experimental assessment concludes that, unlike 802.11b, which appears a robust technology in most of the operational conditions, 802.11g may lead to inefficiencies when employed in an outdoor scenario, due to the lower multi-path tolerance of 802.11g. Since multipath is hard to predict, a novel mechanism to improve the link-distance estimation accuracy — based on CPU clock information — is outlined in chapter 4. The proposed methodology can not only be applied in localization context, but also for estimating the multi-path profile. The second part of the thesis moves the perspective to the MAC point of view and its impairments. Particularly, chapter 5 provides the design of a MAC channel quality estimator to distinguish the different types of MAC impairments and gives separate quantitative measures of the severity of each one. Since the estimator takes advantage of the native characteristics of the 802.11 protocol, the approach is suited to implementation on commodity hardware and makes available new measures that can be of direct use for rate adaptation, channel allocation, etc. Then, chapter 6 introduces a previous unknown phenomenon, the Hidden ACK, that may cause frame losses into multiple WLAN networks when a node replies with an ACK frame. Again, a solution is provided without requiring any modification to the 802.11 protocol. Whenever possible, the quantitative analysis has been led through experimental assessments with implementation on commodity hardware. This was the adopted methodology in chapter 2, 3, 4 and 5. Particularly, this has required an accurate investigation of two brands of WLAN cards, particularly the Atheros and Intel cards, and their driver/firmware, respectively MADWiFi and IPW2200, which are currently the most adopted, respectively, by researchers and layman users

Measuring Transmission Opportunities in 802.11 Links

We propose a powerful MAC/PHY cross-layer approach to measuring IEEE 802.11 transmission opportunities in WLAN networks on a per-link basis. Our estimator can operate at a single station and it is able to: 1) classify losses caused by noise, collisions, and hidden nodes; and 2) distinguish between these losses and the unfairness caused by both exposed nodes and channel capture. Our estimator provides quantitative measures of the different causes of lost transmission opportunities, requiring only local measures at the 802.11 transmitter and no modification to the 802.11 protocol or in other stations. Our approach is suited to implementation on commodity hardware, and we demonstrate our prototype implementation via experimental assessments. We finally show how our estimator can help the WLAN station to improve its local performance

Offloading cellular traffic through opportunistic communications: analysis and optimization

Offloading traffic through opportunistic communications has been recently proposed as a way to relieve the current overload of cellular networks. Opportunistic communication can occur when mobile device users are (temporarily) in each other's proximity, such that the devices can establish a local peer-to-peer connection (e.g., via WLAN or Bluetooth). Since opportunistic communication is based on the spontaneous mobility of the participants, it is inherently unreliable. This poses a serious challenge to the design of any cellular offloading solutions, that must meet the applications' requirements. In this paper, we address this challenge from an optimization analysis perspective, in contrast to the existing heuristic solutions. We first model the dissemination of content (injected through the cellular interface) in an opportunistic network with heterogeneous node mobility. Then, based on this model, we derive the optimal content injection strategy, which minimizes the load of the cellular network while meeting the applications' constraints. Finally, we propose an adaptive algorithm based on control theory that implements this optimal strategy without requiring any data on the mobility patterns or the mobile nodes' contact rates. The proposed approach is extensively evaluated with both a heterogeneous mobility model as well as real-world contact traces, showing that it substantially outperforms previous approaches proposed in the literature.This work has been sponsored by the HyCloud project, supported by Microsoft Innovation Cluster for Embedded Software (ICES), and by the EU H2020-ICT-2014-2 Flex5Gware project, no. 671563

Nanosecond-precision Time-of-Arrival Estimation for Aircraft Signals with low-cost SDR Receivers

Precise Time-of-Arrival (TOA) estimations of aircraft and drone signals are important for a wide set of applications including aircraft/drone tracking, air traffic data verification, or self-localization. Our focus in this work is on TOA estimation methods that can run on low-cost software-defined radio (SDR) receivers, as widely deployed in Mode S / ADS-B crowdsourced sensor networks such as the OpenSky Network. We evaluate experimentally classical TOA estimation methods which are based on a cross-correlation with a reconstructed message template and find that these methods are not optimal for such signals. We propose two alternative methods that provide superior results for real-world Mode S / ADS-B signals captured with low-cost SDR receivers. The best method achieves a standard deviation error of 1.5 ns.Comment: IPSN 201