Wee-Seng Soh

Aloha-Based MAC Protocols with Collision Avoidance for Underwater Acoustic Networks

Unlike terrestrial networks that mainly rely on radio waves for communications, underwater networks utilize acoustic waves, which have comparatively lower loss and longer range in underwater environments. However, the use of acoustic waves pose a new research challenge in the networking area. While existing network schemes for terrestrial sensor networks are mainly designed for negligible propagation delay and high data rate, underwater acoustic communications are characterized by high propagation delay and low data rate. These terrestrial schemes, when directly applied to the underwater channel, will under-utilize its already limited capacity. We investigate how the underwater channels throughput may be enhanced via medium access control (MAC) techniques that consider its unique characteristics. Specifically, we study the performance of Aloha-based protocols in underwater networks, and propose two enhanced schemes, namely, Aloha with collision avoidance (Aloha-CA), and Aloha with advance notification (Aloha-AN), which are capable of using the long propagation delays to their advantage. Simulation results have shown that both schemes can boost the throughput by reducing the number of collisions, and, for the case of Aloha-AN, also by significantly reducing the number of unproductive transmissions.

QoS provisioning in cellular networks based on mobility prediction techniques

In cellular networks, QoS degradation or forced termination may occur when there are insufficient resources to accommodate handoff requests. One solution is to predict the trajectory of mobile terminals so as to perform resource reservations in advance. With the vision that future mobile devices are likely to be equipped with reasonably accurate positioning capability, we investigate how this new feature may be used for mobility predictions. We propose a mobility prediction technique that incorporates road topology information, and describe its use for dynamic resource reservation. Simulation results are presented to demonstrate the improvement in reservation efficiency compared with several other schemes.

Indoor Localization Using Multiple Wireless Technologies

Indoor localization techniques using location fingerprints are gaining popularity because of their cost-effectiveness compared to other infrastructure-based location systems. However, their reported accuracy fall short of their counterparts. In this paper, we investigate many aspects of fingerprint-based location systems in order to enhance their accuracy. First, we derive analytically a robust location fingerprint definition, and then verify it experimentally as well. We also devise a way to facilitate under-trained location systems through simple linear regression technique. This technique reduces the training time and effort, and can be particularly useful when the surrounding or setup of the localization area changes. We further show experimentally that because of the positions of some access points or the environmental factors around them, their signal strength correlates nicely with distance. We argue that it would be more beneficial to give special consideration to these access points for location computation, owing to their ability to distinguish locations distinctly in signal space. The probability of encountering such access points will be even higher when we denote a locations signature using the signals of multiple wireless technologies collectively. We present the results of two well- known localization algorithms (K-Nearest Neighbor and Bayesian Probabilistic Model) when the above factors are exploited, using Bluetooth and Wi-Fi signals. We have observed significant improvement in their accuracy when our ideas are implemented.

A robust dead-reckoning pedestrian tracking system with low cost sensors

The emergence of personal mobile device with low cost sensors, such as accelerometer and digital compass, has made dead-reckoning (DR) an attractive choice for indoor pedestrian tracking. In this paper, we propose a robust DR pedestrian tracking system on top of such commercially accessible sensor sets capable of DR. The proposed method exploits the fact that, multiple DR systems, carried by the same pedestrian, have stable relative displacements with respect to the center of motion, and therefore to each other. We first formulate the robust tracking task as a generalized maximum a posteriori sensor fusion problem, and then we narrow it to a simple computation procedure with certain assumptions. A prototype is implemented and evaluated with a benchmark system that collects ground truth efficiently and accurately. In a practical indoor testbed, the proposed scheme has exhibited robust tracking performance, with reduction in average tracking error up to 73.7%, compared to traditional DR tracking methods.

Dynamic bandwidth reservation in cellular networks using road topology based mobility predictions

In cellular networks, an important call-level quality-of-service (QoS) issue is how to limit the probability of forced termination during handoffs. One solution is to predict the trajectory of mobile terminals so as to perform bandwidth reservation in advance. With the vision that future mobile devices are likely equipped with reasonably accurate positioning capability, we propose a novel mobility prediction technique that incorporates both mobile positioning information and road topology knowledge. We then develop an adaptive bandwidth reservation scheme that dynamically adjusts the reservation at each base station according to both incoming and outgoing hand-off predictions generated using our mobility prediction technique. We evaluate the performance of the scheme via simulations, along with six other schemes for comparison purposes. Results agree with intuition that schemes which incorporate more knowledge are able to achieve better reservation efficiency. Our scheme is shown to achieve the best efficiency among all realizable schemes simulated.

Indoor localization with channel impulse response based fingerprint and nonparametric regression

In this paper, we propose a fingerprint-based localization scheme that exploits the location dependency of the channel impulse response (CIR). We approximate the CIR by applying inverse Fourier transform to the receivers channel estimation. The amplitudes of the approximated CIR (ACIR) vector are further transformed into the logarithmic scale to ensure that elements in the ACIR vector contribute fairly to the location estimation, which is accomplished through nonparametric kernel regression. As shown in our simulations, when both the number of access points and density of training locations are the same, our proposed scheme displays significant advantages in localization accuracy, compared to other fingerprint-based methods found in the literature. Moreover, absolute localization accuracy of the proposed scheme is shown to be resilient to the real time environmental changes caused by human bodies with random positions and orientations.

A survey of calibration-free indoor positioning systems

Last decade observed a significant research effort directed towards indoor localization utilizing location fingerprinting techniques. Fingerprinting solutions generally require a pre-deployment site survey procedure during which a radio-map is constructed by laboriously collecting signal strength samples (e.g., Wi-Fi) over the whole localization area. However, such localization efforts have certain shortcomings. For example, it is time consuming, labor intensive, vulnerable to environmental changes, and the process requires certain pedigree on the surveyor that may deem the fingerprinting techniques impractical to be deployed over large areas (e.g., shopping malls, multi-storey offices/residences, etc.). Newer emerging techniques try to bypass this expensive pre-deployment effort of fingerprinting solutions altogether. They may build the radio-map through the implicit participation of the building occupants, office employee, shoppers, visitors, etc. Apart from the traditional performance comparison criteria like accuracy, precision, robustness, scalability, algorithmic complexity based on which the localization techniques were evaluated, these newer approaches warrant some additional ones. For example, whether they require an actual geographical map of the localization area, the percentage of occasional location fix to ensure reasonable accuracy, the usage of explicit/implicit user participation to construct the radio map, the usage of building landmarks (e.g., entrance, conference room, elevator, escalator, etc.) or additional sensors (e.g., accelerometer, gyroscope, compass, etc.), whether they address device heterogeneity, etc. In this article, we survey the newer emerging fingerprinting solutions that try to relieve the pre-deployment woes. We also identify some newer performance comparison criteria based on these solutions’ inherent characteristics, and apply them together with the traditional ones in order to evaluate a number of such proposed systems.

MACA-U: A Media Access Protocol for Underwater Acoustic Networks

Unlike terrestrial wireless communication which uses radio waves, underwater communication relies on acoustic waves. The long latency and limited bandwidth pose great challenges in underwater Media Access Control (MAC) protocol design. As a result, terrestrial MAC protocols perform inefficiently when deployed directly in an underwater environment. In this paper, we examine how an existing asynchronous handshaking based protocol called Multiple Access Collision Avoidance (MACA) can be adapted for use in multi-hop underwater networks. Three areas of improvement are investigated, namely, the state transition rules, the packet forwarding strategy, and the backoff algorithm. Throughput performance is also evaluated through extensive simulation in multi-hop underwater networks. Due to its simplicity and throughput stability, our proposed MAC protocol can be adopted as a reference MAC protocol for underwater networks, with which a more sophisticated underwater MAC may benchmark its performance.

MACA-MN: A MACA-Based MAC Protocol for Underwater Acoustic Networks with Packet Train for Multiple Neighbors

Unlike the terrestrial wireless networks that utilize the radio channel, underwater networks use the acoustic channel, which poses research challenges in the medium access control (MAC) protocol design due to its low bandwidth and high propagation delay characteristics. Since most of the MAC protocols for wireless terrestrial networks have been designed with negligible propagation delay in mind, they generally perform poorly when applied directly in underwater acoustic networks, especially for the case of handshaking-based protocols. In this paper, we propose a MACA-based MAC protocol with packet train to multiple neighbors (MACA-MN). It improves the channel utilization by forming a train of packets destined for multiple neighbors during each round of handshake, which greatly reduces the relative proportion of time wasted due to the propagation delays of control packets. This approach also reduces the hidden terminal problem. Our simulations show that the MACA-MN is able to achieve much higher throughput than the MACA protocol.

A predictive bandwidth reservation scheme using mobile positioning and road topology information

In cellular networks, an important practical issue is how to limit the handoff dropping probability efficiently. One possible approach is to perform dynamic bandwidth reservation based on mobility predictions. With the rapid advances in mobile positioning technology, and the widespread availability of digital road maps previously designed for navigational devices, we propose a predictive bandwidth reservation scheme built upon these timely opportunities. In contrast to the common practice of utilizing only incoming handoff predictions at each cell to compute the reservations, our scheme is more efficient as it innovatively utilizes both incoming and outgoing handoff predictions; it can meet the same target handoff dropping probability by blocking fewer new calls. The individual base stations are responsible for the computations, which are shown to be simple enough to be performed in real-time. We evaluate the scheme via simulation, along with five other schemes for comparison. Simulation results show that those schemes that rely on positioning information are significantly more efficient than those that do not. Our schemes additional use of the road topology information further improves upon this advantage, bringing the efficiency closer to the bound set by a benchmark scheme that assumes perfect knowledge about future handoffs