Recent years have witnessed considerable efforts in repurposing ubiquitous wireless communication signals for non-contact sensing.$\bf{NearLink}$is a new-generation short-range wireless communication protocol, which is designed to address the high-quality network connectivity requirements of low power, low latency and high reliability. Given these notable advantages, NearLink has great potential for widespread application in various Internet of Things (IoT) areas. However, NearLink-based wireless sensing has not yet been explored. To bridge this gap, this work explores for the first time the sensing potential and opportunities of NearLink. Specifically, we systematically investigate the sensing capability of NearLink through answering two key questions: (1) How can NearLink's communication-oriented signals be adapted for sensing tasks? (2) How can sensing performance be enhanced under multipath interference and low-power constraints? We prototype the NearLink sensing system-NearSense, and take the respiration detection as a case study to demonstrate its effectiveness. Extensive experiments demonstrate that NearSense can achieve an average detection rate of 98% and a false alarm rate below 1.5% in case of various real-life challenging interference. We believe this work opens up new directions for the new-generation wireless sensing towards high-quality network connections.

Indoor accurate ranging using WiFi signals is a challenge since it is affected by the signal bandwidth, indoor environment, and phase distortions introduced by the underlying hardware. In this paper, we improve channel impulse response (CIR) resolution by splicing channel state information (CSI) measurements from multiple non-contiguous bands. However, most previous efforts have directly used non-contiguous CSI measurements for parameter estimation, which leads to multi-band gain loss and ranging performance degradation. To solve this problem, we propose a novel time of flight (TOF) estimation scheme that includes two stages. In the first stage, we build an equivalent optimization model of the inverse non-uniform discrete Fourier transform (INDFT) to transform the CSI samples to the CIR. In the second stage, we construct a time domain super-resolution TOF estimation model and combine the estimation results of the first stage to obtain the distance information using a subspace projection method. Finally, we conduct the simulation using commercial-grade wireless ray propagation modeling software. Based on the simulation result, the ranging error of our approach is less than 10 cm 85 % with the spliced bandwidth of 240 MHz.

In this paper, we propose a transmission control scheme for the approximate message passing (AMP)-based joint user identification and channel estimation in massive connectivity networks. In the proposed transmission control scheme, a transmission control function is designed to determine a user's transmission probability, when it has a transmission demand. By employing a step transmission control function for the proposed scheme, we derive the channel distribution experienced by the receiver to describe the effect of transmission control on the design of AMP algorithm. Based on that, we modify the AMP algorithm by designing a minimum mean squared error (MMSE) denoiser, to jointly identify the user activity and estimate their channels. We further derive the false alarm and missed detection probabilities to characterize the user identification performance of the proposed scheme. Closed-form expressions of the average packet delay and the network throughput are obtained. Furthermore, we optimize the transmission control function to maximize the network throughput. We demonstrate that the proposed scheme can significantly improve the user identification and channel estimation performance, reduce the average delay, and boost the throughput, compared to the conventional scheme without transmission control.

We propose a new class of information-coupled Turbo codes to improve the transport block (TB) error rate performance for LTE systems. Meanwhile, we keep the LTE hybrid automatic repeat request protocol and the Turbo decoder for each code block (CB) unchanged. In the proposed codes, every two consecutive CBs in a TB are coupled together by sharing a few common information bits. We propose a feed-forward and feed-back decoding scheme to decode the whole TB by exploiting the coupled information between CBs. Numerical results show that the proposed codes achieve a signal-to-noise-ratio (SNR) gain of 0.28 dB to 0.72 dB over LTE Turbo codes for the simulated code parameters at a TB error rate level of 10-2.

We propose a new class of partially information-coupled (PIC) turbo codes to improve the transport block (TB) error rate performance for long-term evolution (LTE) systems, while keeping the hybrid automatic repeat request protocol and the turbo decoder for each code block (CB) unchanged. In the proposed codes, every two consecutive CBs in a TB are coupled together by sharing partial information bits. This coding structure introduces irregular variable node degree distributions in the Tanner graph of the PIC-turbo codes. We propose a feedforward and feedback decoding scheme and a windowed decoding scheme to decode the whole TB by exploiting the coupled information between CBs. We calculate the extrinsic information transfer (EXIT) functions for the PIC-turbo codes by assuming that the coupled information are perfectly decoded. An SNR gain upper bound of the PIC-turbo codes over the LTE turbo codes for various coupling ratios is derived by the calculated EXIT charts. Numerical results show that the proposed codes achieve an SNR gain of 0.26-0.73 dB for various code parameters at a TB error rate level of 10-2, which complies with the derived SNR gain upper bound.

In this paper, a novel performance analysis frame-work of Maximum Likelihood (ML) receiver for Vertical Bell Labs Layered Space-Time (V-BLAST) architecture over correlated Rayleigh fading channel is presented. Based on the statistical property of squared Euclidean distance, the exact expressions for Pairwise Error Probability (PEP) over transmit, receive, and joint correlated fading channel are derived. The approximate expression of the PEPs for high signal-to-noise ration (SNR) region is used to quantitatively analyze the loss of the diversity order and the penalty of SNR. Three interesting results of this analysis are: 1) the loss caused by transmit and receive correlation is independent. 2) the transmit correlation has no impact on the diversity order, and the loss of SNR caused by transmit correlation is determined by the transmit correlation matrix and modulation scheme. 3) the loss of diversity order due to receive correlation is equals to the difference of the numbers of receiver antenna and the rank of receive correlation matrix, under the assumption that the receive correlation matrix has full rank, the penalty of SNR is jointly determined by the determinant of the receive correlation matrix and the number of receive antenna. Simulation results are given to corroborate the theoretical analysis.