CSI-Based Human Activity Recognition Using Multi-Input Multi-Output Autoencoder and Fine-Tuning

Wi-Fi-based human activity recognition (HAR) has gained considerable attention recently due to its ease of use and the availability of its infrastructures and sensors. Channel state information (CSI) captures how Wi-Fi signals are transmitted through the environment. Using channel state information of the received signals transmitted from Wi-Fi access points, human activity can be recognized with more accuracy compared with the received signal strength indicator (RSSI). However, in many scenarios and applications, there is a serious limit in the volume of training data because of cost, time, or resource constraints. In this study, multiple deep learning models have been trained for HAR to achieve an acceptable accuracy level while using less training data compared to other machine learning techniques. To do so, a pre-trained encoder which is trained using only a limited number of data samples, is utilized for feature extraction. Then, by using fine-tuning, this encoder is utilized in the classifier, which is trained by a fraction of the rest of the data, and the training is continued alongside the rest of the classifier’s layers. Simulation results show that by using only 50% of the training data, there is a 20% improvement compared with the case where the encoder is not used. We also showed that by using an untrainable encoder, an accuracy improvement of 11% using 50% of the training data is achievable with a lower complexity level

Enhancing CSI-Based Human Activity Recognition by Edge Detection Techniques

Human Activity Recognition (HAR) has been a popular area of research in the Internet of Things (IoT) and Human–Computer Interaction (HCI) over the past decade. The objective of this field is to detect human activities through numeric or visual representations, and its applications include smart homes and buildings, action prediction, crowd counting, patient rehabilitation, and elderly monitoring. Traditionally, HAR has been performed through vision-based, sensor-based, or radar-based approaches. However, vision-based and sensor-based methods can be intrusive and raise privacy concerns, while radar-based methods require special hardware, making them more expensive. WiFi-based HAR is a cost-effective alternative, where WiFi access points serve as transmitters and users’ smartphones serve as receivers. The HAR in this method is mainly performed using two wireless-channel metrics: Received Signal Strength Indicator (RSSI) and Channel State Information (CSI). CSI provides more stable and comprehensive information about the channel compared to RSSI. In this research, we used a convolutional neural network (CNN) as a classifier and applied edge-detection techniques as a preprocessing phase to improve the quality of activity detection. We used CSI data converted into RGB images and tested our methodology on three available CSI datasets. The results showed that the proposed method achieved better accuracy and faster training times than the simple RGB-represented data. In order to justify the effectiveness of our approach, we repeated the experiment by applying raw CSI data to long short-term memory (LSTM) and Bidirectional LSTM classifiers

Power allocation for D2D communications using max-min message-passing algorithm

The approach of factor-graphs (FGs) is applied in the context of power control and user pairing in Device-to-Device (D2D) communications as an effective underlay concept in wireless cellular networks. D2D communications can increase the spectral efficiency of wireless cellular networks by establishing a direct link between devices with limited help from the evolved node base stations (eNBs). A well-designed user pairing and power allocation scheme with low complexity can remarkably improve the system’s performance. In this paper, a simple and distributed FG based approach is utilized for power control and user pairing implementation in an underlay cellular network with D2D communications. A max-min criterion is proposed to maximize the minimum rate of all active users in the network, including the cellular and multiple D2D co-channel links in the uplink direction. An associated message-passing (MP) algorithm is presented to distributedly solve the resultant NP-hard maximization problem, with a guaranteed convergence compared to game-theoretic and Q-learning based methods. The complexity and convergence of the proposed method are analyzed and numerical results confirm that the proposed scheme outperforms alternative algorithms in terms of complexity, while keeping the sum-rate of users nearly the same as centralized counterpart methods

A rate-compatible puncturing scheme for finite-length LDPC Codes

In this paper, we propose a rate-compatible puncturing scheme for finite-length low-density parity-check (LDPC) codes over the additive white Gaussian noise (AWGN) channel. The proposed method is applicable to any LDPC mother code, both regular and irregular, and constructs punctured codes which perform well in both the waterfall and the error floor regions for a wide range of code rates. The scheme selects code bits to be punctured one at a time and based on a sequence of criteria. An important selection criterion is the number of short cycles with low approximate cycle extrinsic message degree (ACE) in which a candidate bit node participates. Simulation results demonstrate that the ACE measure, which is most often the determining criterion in the final selection of the puncturing candidates, plays an important role in improving the performance of the codes in both the waterfall and the error-floor regions. These results also demonstrate that the proposed scheme is superior to the existing puncturing methods, particularly when a wide range of code rates is desirable

Approximation of log-likelihood ratio for wireless channels based on Taylor series

A new approach for the approximation of the channel log-likelihood ratio (LLR) for wireless channels based on Taylor series is proposed. The approximation is applied to the uncorrelated flat Rayleigh fading channel with unknown channel side information at the receiver. It is shown that the proposed approximation greatly simplifies the calculation of channel LLRs, and yet provides results almost identical to those based on the exact calculation of channel LLRs. The results are obtained in the context of iterative decoding of low-density parity-check (LDPC) codes and include threshold calculations and error rate performance of finite-length codes. Compared to the existing approximations, the proposed method is either significantly less complex, or considerably more accurate

Lowering the error floor of LDPC codes using cyclic liftings

Cyclic liftings are proposed to lower the error floor of low-density parity-check (LDPC) codes. The liftings are designed to eliminate dominant trapping sets of the base code by removing the short cycles which are part of the trapping sets. We derive a necessary and sufficient condition for the cyclic permutations assigned to the edges of a cycle ξ of length ℓ(ξ) in the base graph such that the inverse image of ξ in the lifted graph consists of only cycles of length strictly larger than ℓ(ξ). The proposed method is universal in the sense that it can be applied to any LDPC code over any channel and for any iterative decoding algorithm. It also preserves important properties of the base code such as degree distributions, and in some cases, the code rate. The constructed codes are quasi-cyclic and thus attractive from a practical point of view. The proposed method is applied to both structured and random codes over the binary symmetric channel (BSC). The error floor improves consistently by increasing the lifting degree, and the results show significant improvements in the error floor compared to the base code, a random code of the same degree distribution and block length, and a random lifting of the same degree. Similar improvements are also observed when the codes designed for the BSC are applied to the additive white Gaussian noise (AWGN) channel

Design of irregular quasi-cyclic protograph codes with low error floors

We propose a technique to design finite-length irregular low-density parity-check (LDPC) codes over the binary-input additive white Gaussian noise (AWGN) channel with good performance in both the waterfall and the error floor region. The design process starts from a protograph which embodies a desirable degree distribution. This protograph is then lifted cyclically to a certain block length of interest. The lift is designed carefully to satisfy a certain approximate cycle extrinsic message degree (ACE) spectrum. The target ACE spectrum is one with extremal properties, implying a good error floor performance for the designed code. The proposed construction results in quasi-cyclic codes which are attractive in practice due to simple encoder and decoder implementation. Simulation results are provided to demonstrate the effectiveness of the proposed construction in comparison with similar existing constructions

Brief carbon dioxide exposure blocks heat hardening but not cold acclimation in Drosophila melanogaster

Carbon dioxide is a commonly used anaesthetic in Drosophila research. While any detrimental effects of CO2 exposure on behaviour or traits are largely unknown, a recent study observed significant effects of CO2 exposure on rapid cold hardening and chill-coma recovery in Drosophila melanogaster. In this study we investigated the effect of a brief CO, exposure on heat hardening and cold acclimation in D. melanogaster, measuring heat knockdown and chill-coma recovery times of flies exposed to CO2 for 1 min after hardening or acclimation. CO2 anaesthesia had a significant negative effect on heat hardening, with heat knockdown rates in hardened flies completely reduced to those of controls after CO2 exposure. Chill-coma recovery rates also significantly increased in acclimated flies that were exposed to CO2 although not to the same extent seen in the heat populations. CO2 exposure had no impact on heat knockdown rates of control flies, while there was a significant negative effect of the anaesthetic on chill-coma recovery rates of control flies. In light of these results, we suggest that CO2 should not be used after hardening in heat resistance assays due to the complete reversal of the heat hardening process upon exposure to CO2. (c) 2007 Elsevier Ltd. All rights reserved