Real-Time Step Length Estimation in Indoor and Outdoor Scenarios.

In this paper, human step length is estimated based on the wireless channel properties and the received signal strength indicator (RSSI) method. The path loss between two ankles, called the on-ankle path loss, is converted from the RSSI, which is measured by our developed wearable hardware in indoor and outdoor ambulation scenarios. The human walking step length is estimated by a reliable range of RSSI values. The upper threshold and the lower threshold of this range are determined experimentally. This paper advances our previous step length measurement technique by proposing a novel exponential weighted moving average (EWMA) algorithm to update the upper and lower thresholds, and thus the step length estimation, recursively. The EWMA algorithm allows our measurement technique to process each shorter subset of the dataset, called a time window, and estimate the step length, rather than having to process the whole dataset at a time. The step length is periodically updated on the fly when the time window is "sliding" forwards. Thus, the EWMA algorithm facilitates the step length estimation in real-time. The impact of the EWMA parameter is analysed, and the optimal parameter is discovered for different experimental scenarios. Our experiments show that the EWMA algorithm could achieve comparable accuracy as our previously proposed technique with errors as small as 3.02% and 0.30% for the indoor and outdoor scenarios, respectively, while the processing time required to output an estimation of the step length could be significantly shortened by 53.96% and 60% for the indoor walking and outdoor walking, respectively.

Step Length Estimation Using the RSSI Method in Walking and Jogging Scenarios.

In this paper, human step length was estimated based on wireless channel properties and the received signal strength indicator (RSSI) method. Path loss between two ankles of the person under test was converted from the RSSI, which was measured using our developed wearable transceivers with embedded micro-controllers in four scenarios, namely indoor walking, outdoor walking, indoor jogging, and outdoor jogging. For brevity, we call it on-ankle path loss. The histogram of the on-ankle path loss showed clearly that there were two humps, where the second hump was closely related to the maximum path loss, which, in turn, corresponded to the step length. This histogram can be well approximated by a two-term Gaussian fitting curve model. Based on the histogram of the experimental data and the two-term Gaussian fitting curve, we propose a novel filtering technique to filter out the path loss outliers, which helps set up the upper and lower thresholds of the path loss values used for the step length estimation. In particular, the upper threshold was found to be on the right side of the second Gaussian hump, and its value was a function of the mean value and the standard deviation of the second Gaussian hump. Meanwhile, the lower threshold lied on the left side of the second hump and was determined at the point where the survival rate of the measured data fell to 0.68, i.e., the cumulative distribution function (CDF) approached 0.32. The experimental data showed that the proposed filtering technique resulted in high accuracy in step length estimation with errors of only 10.15 mm for the indoor walking, 4.40 mm for the indoor jogging, 4.81 mm for the outdoor walking, and 10.84 mm for the outdoor jogging scenarios, respectively.

Step Length Measurements Using the Received Signal Strength Indicator.

In this paper, portable transceivers with micro-controllers and radio frequency modules are developed to measure the received signal strength, path loss, and thus the distance between the human ankles for both indoor and outdoor environments. By comparing the experimental results and the theoretical model, a path loss model between transceivers attached to the subject's ankles is derived. With the developed experimental path loss model, the step length can be measured relatively accurately, despite the imperfections of hardware devices, with the distance errors of a centimeter level. This paper, therefore, helps address the need for a distance measurement method that has fewer health concerns, is accurate, and is less affected by occlusions and confined spaces. Our findings possibly lay a foundation for some important applications, such as the measurement of gait speed and localization of the human body parts, in wireless body area networks.

Unbalanced Hybrid AOA/RSSI Localization for Simplified Wireless Sensor Networks.

Source positioning using hybrid angle-of-arrival (AOA) estimation and received signal strength indicator (RSSI) is attractive because no synchronization is required among unknown nodes and anchors. Conventionally, hybrid AOA/RSSI localization combines the same number of these measurements to estimate the agents' locations. However, since AOA estimation requires anchors to be equipped with large antenna arrays and complicated signal processing, this conventional combination makes the wireless sensor network (WSN) complicated. This paper proposes an unbalanced integration of the two measurements, called 1AOA/nRSSI, to simplify the WSN. Instead of using many anchors with large antenna arrays, the proposed method only requires one master anchor to provide one AOA estimation, while other anchors are simple single-antenna transceivers. By simply transforming the 1AOA/1RSSI information into two corresponding virtual anchors, the problem of integrating one AOA and N RSSI measurements is solved using the least square and subspace methods. The solutions are then evaluated to characterize the impact of angular and distance measurement errors. Simulation results show that the proposed network achieves the same level of precision as in a fully hybrid nAOA/nRSSI network with a slightly higher number of simple anchors.

Analog Least Mean Square Loop for Self-Interference Cancellation: A Practical Perspective.

Self-interference (SI) is the key issue that prevents in-band full-duplex (IBFD) communications from being practical. Analog multi-tap adaptive filter is an efficient structure to cancel SI since it can capture the nonlinear components and noise in the transmitted signal. Analog least mean square (ALMS) loop is a simple adaptive filter that can be implemented by purely analog means to sufficiently mitigate SI. Comprehensive analyses on the behaviors of the ALMS loop have been published in the literature. This paper proposes a practical structure and presents an implementation of the ALMS loop. By employing off-the-shelf components, a prototype of the ALMS loop including two taps is implemented for an IBFD system operating at the carrier frequency of 2.4 GHz. The prototype is firstly evaluated in a single carrier signaling IBFD system with 20 MHz and 50 MHz bandwidths, respectively. Measured results show that the ALMS loop can provide 39 dB and 33 dB of SI cancellation in the radio frequency domain for the two bandwidths, respectively. Furthermore, the impact of the roll-off factor of the pulse shaping filter on the SI cancellation level provided by the prototype is presented. Finally, the experiment with multicarrier signaling shows that the performance of the ALMS loop is the same as that in the single carrier system. These experimental results validate the theoretical analyses presented in our previous publications on the ALMS loop behaviors.

Performance Evaluation of Non-GPS Based Localization Techniques under Shadowing Effects.

Non-GPS localization has gained much interest from researchers and industries recently because GPS might fail to meet the accuracy requirements in shadowing environments. The two most common range-based non-GPS localization methods, namely Received Signal Strength Indicator (RSSI) and Angle-of-Arrival (AOA), have been intensively mentioned in the literature over the last decade. However, an in-depth analysis of the weighted combination methods of AOA and RSSI in shadowing environments is still missing in the state-of-the-art. This paper proposes several weighted combinations of the two RSSI and AOA components in the form of pAOA + qRSSI, devises the mathematical model for analyzing shadowing effects, and evaluates these weighted combination localization methods from both accuracy and precision perspectives. Our simulations show that increasing the number of anchors does not necessarily improve the precision and accuracy, that the AOA component is less susceptible to shadowing than the RSSI one, and that increasing the weight of the AOA component and reducing that of the RSSI component help improve the accuracy and precision at high Signal-to-Noise Ratios (SNRs). This observation suggests that some power control algorithm could be used to increase automatically the transmitted power when the channel experiences large shadowing to maintain a high SNR, thus guaranteeing both accuracy and precision of the weighted combination localization techniques.

Joint Transmission Power Control and Relay Cooperation for WBAN Systems.

Improving transmission reliability is a crucial challenge for Wireless Body Area Networks (WBANs) because of the instability of channel conditions and the stringent Packet Loss Ratio (PLR) requirement for many WBANs applications. On the other hand, limited by the size of WBAN nodes, the energy consumption of WBAN nodes should be minimized. In this paper, we jointly consider transmission power control, dynamic slot scheduling and two-hop cooperative mechanism and propose an Autocorrelation-based Adaptive Transmission (AAT) scheme that achieves a better trade-off between transmission reliability and energy consumption for WBAN systems. The new scheme is designed to be compatible with IEEE 802.15.6. We evaluated the performance of the newly proposed scheme by importing the real channel datasets into our simulation model. Simulation results demonstrate that the AAT method can effectively improve the transmission reliability while reducing the energy consumption. We also provide the performance evaluation from three perspectives, namely packet error ratio, energy consumption and energy efficiency, and provide recommendations on the application of the two-hop cooperative mechanism associated with the proposed AAT in the contexts of WBANs.