Human pose estimation based on Channel State Information (CSI) has emerged as a promising approach for non-intrusive and precise human activity monitoring, yet faces challenges including accurate multi-person pose recognition and effective CSI feature learning. This paper presents MultiFormer, a wireless sensing system that accurately estimates human pose through CSI. The proposed system adopts a transformer-based time-frequency dual-token feature extractor with multi-head self-attention. This feature extractor is able to model inter-subcarrier correlations and temporal dependencies of the CSI. The extracted CSI features and the pose probability heatmaps are then fused by the Multi-Stage Feature Fusion Network (MSFN) to enforce the anatomical constraints. Extensive experiments conducted on the public MM-Fi dataset and our self-collected dataset show that the MultiFormer achieves higher accuracy over state-of-the-art approaches, especially for high-mobility keypoints (wrists, elbows) that are particularly difficult for previous methods to accurately estimate.

In contrast to most of the existing equalization methods, blind equalization (BE) can eliminate the effect of multipath fading without any known sequences. As a result, BE is a promising technique for wireless intelligence and non-cooperative communication. However, the conventional BE methods require long sequences or large-scale training to recover the received signals. In this paper, a deep learning-based neighborhood-assisted symbol-based decision (DL-NA-SBD) method is proposed to tackle this problem. Specifically, we replace the commonly used linear approaches with neural network to optimize the traditional SBD function and the mean square error (MSE) loss function in two stages to generate the equalizer coefficients. To avoid collecting large numbers of signals, we train the network using the online training strategy. Simulation results demonstrate that the proposed method achieves better inter-symbol interference (ISI) elimination and bit error rate (BER) performance compared with the conventional methods while requiring only a short-length signal sequence.

Polarization modulation (PM) is a recently developed multiple-input multiple-output (MIMO) toward low-cost implementation by exploiting the polarization degree of freedom in an efficient way. In the context of a PM transmitter, an improved expectation propagation (EP) detector is proposed in this contribution, while the bit-error rate (BER) performance and computational complexity are both evaluated and quantified respectively. We demonstrate that the proposed detector outperforms its original EP-based counterpart and traditional linear minimum mean square error (LMMSE) detector as a promising receiver design for PM systems.

As a revolutionary technology for future wireless communications, reconfigurable intelligent surface (RIS), characterized by an efficient way of manipulating wireless signals, has been widely investigated in recent years toward enhancing signal quality, energy efficiency, throughput, and so on. However, in RIS-assisted Internet of Things (IoT), a new issue as multipath separation emerges, especially, when deploying multiple RISs to assist communication, since the devices may have limited signal processing capabilities. For alleviating this problem, we conceive a novel RIS-enabled code-division multiple access (CDMA) structure, where each RIS holds a specified time-varying coefficient to tag the channel. Moreover, multipath extraction is further considered, including a practical channel estimation approach along with theoretical derivations in terms of Cramér–Rao lower bound, mean-square error, as well as ergodic channel capacity. Simulation results corroborate the feasibility of the conceived RIS-CDMA structure and the effectiveness of the proposed multipath extraction approach.

Recently, communications with the aid of reconfigurable intelligent surface (RIS), which operates with the aim of enhancing the system communication performance, have aroused extensive researches. Furthermore, the use of RIS for positioning has been considered. Therefore, we focus on a practical structure of indoor positioning assisted by distributed RISs through utilizing their ability to manipulate multipath signals, through the developed quasi-static and dynamic modes. Specifically, in the quasi-static mode, for reducing the implementation cost, the reflection coefficients for each RIS are preset and remain constant. In the dynamic mode, the reflection coefficients can be timely updated with a two-step positioning approach toward more accurate positioning performance. Furthermore, the Cramér-Rao lower bound of the developed positioning scheme is quantified through theoretical analysis. Both theoretical analysis and simulation results demonstrate that RIS has the potential to realize accurate positioning even with a single access point, due to its ability to mark the channel and replace traditional active positioning anchors. Meanwhile, we also show that the developed two-step positioning scheme can achieve considerable performance gain in accurate positioning.

Reconfigurable intelligent surface (RIS)-assisted wireless communications have been widely investigated toward enhanced signal quality, energy efficiency as well as throughput. The issue of multipath separation and identification via multiple RISs, which, however, remains to be further investigated, is of paramount importance. For alleviating this problem, we conceive a novel RIS-assisted spreading and code division multiple access (CDMA) structure, where each RIS holds a time-varying reflection coefficient sequence for spreading, in order to tag the channel and distinguish each other with the idea of CDMA. Moreover, practical channel estimation and multipath identification are considered, and the ergodic channel capacity is also derived when the receiver employs maximum ratio combining. Simulation results corroborate the feasibility of the proposed RIS-CDMA structure and the effectiveness of the developed channel estimation and multipath combination approaches.

A new radio frequency fingerprint that incorporates the channel impulse response and Angle of Arrival was introduced to enhance the accuracy of the indoor positioning. To use the new fingerprint. We use the generalized distance metric, i.e., Jensen-Shannon Divergence and cluster center to compare the difference between data collected at the test point and given reference point. Based on the new RF fingerprint, we proposed a device free passive localization system that does not require the user to have any measurement devices. The user location is estimated by searching the reference points with the the smallest distance between the test data and the database. The experimental result shows that the proposed system has better location accuracy method comparing with the conventional fingerprint algorithms.

To support interference-free quasi-synchronous code-division multiple-access (QS-CDMA) communication with low spectral density profile in a cognitive radio (CR) network, it is desirable to design a set of CDMA spreading sequences with zero-correlation zone (ZCZ) property. However, traditional ZCZ sequences (which assume the availability of the entire spectral band) cannot be used because their orthogonality will be destroyed by the spectrum hole constraint in a CR channel. To date, analytical construction of ZCZ CR sequences remains open. Taking advantage of the Kronecker sequence property, a novel family of sequences (called "quasi-ZCZ" CR sequences) which displays zero cross-correlation and near-zero auto-correlation zone property under arbitrary spectrum hole constraint is presented in this paper. Furthermore, a novel algorithm is proposed to jointly optimize the peak-to-average power ratio (PAPR) and the periodic auto-correlations of the proposed quasi-ZCZ CR sequences. Simulations show that they give rise to single-user bit-error-rate performance in CR-CDMA systems which outperform traditional non-contiguous multicarrier CDMA and transform domain communication systems; they also lead to CR-CDMA systems which are more resilient than non-contiguous OFDM systems to spectrum sensing mismatch, due to the wideband spreading.

As a cognitive radio (CR) modulation technique, transform domain communication system (TDCS) has been proposed by utilizing white space spectrum for the network access and achieving low probability of interception (LPI). In the previously reported TDCS- based cognitive radio networks (CRN), however, the non-zero periodic correlation function between any pair of users results in multiuser interference (MUI). In this paper, a novel framework under the CR constraints is presented by employing a two- dimension spreading scheme (i.e., time and frequency domains). We first obtain a class of spreading sequences with almost perfect periodic correlation function for arbitrary spectrum utilization pattern. Then, an universal criteria is presented for synchronous MUI-free CRNs when employing TDCS. Simulation results demonstrate that the proposed TDCS-based CRN architecture is a preferable candidate for distribution wireless networks, such as CR Ad-hoc wireless sensor networks.

A simple and efficient method for generating correlated multivariate Weibull random variables with arbitrary fading parameters and arbitrary average powers is proposed. The multivariate Weibull random variables generated via this method can be used to simulate the performance of wireless communication systems with any diversity order or channel impulse response length, under arbitrary correlated Weibull fading conditions.

In this paper we describe results of a channel measurement campaign for modeling the V2V channel. After review of applications, potential frequency bands, and related work, we describe the measurements and results for delay spreads and multipath component fading amplitudes and correlations, made in multiple V2V environments. We also note how the V2V channel can differ appreciably from other common terrestrial (e.g., cellular) channels. We describe considerations used in developing the statistical channel models for these environments, and provide some example measurement and modeling results that should be useful for system designers in future V2V applications

In this paper, we describe a generalized scheme to analyze the bit error probability of Hamming codes when the code symbols have different symbol energies. The method of analysis is general, and could be used to analyze other block code schemes. We illustrate the effectiveness of our method with application to a spectrally-shaped multicarrier direct-sequence spread spectrum system.