Indoor intrusion detection is a critical task for home security. Previous works in intrusion detection suffer from the problems such as blind spots in non-line-of-sight (NLOS) areas, restricted device locations, massive offline training required, and privacy concern. In this article, we design and implement an omnidirectional indoor intrusion detection system, named AudioGuard , using only a pair of speaker and microphone. AudioGuard is able to detect both line-of-sight (LOS) and NLOS intrusions. Our observation of acoustic signal propagation in an indoor environment shows that there exist abundant multipath reflections and human movement introduces Doppler shift in echo signals. We hence capture periodical Doppler shift caused by intruder's walking motion to detect intrusion. Specifically, we first extract the Doppler shift embedded in echo signals, and we then propose a periodicity polarization method to cancel out the impact of the change of radial angle and the distance on periodicity of Doppler shift. Finally, we detect intrusion by measuring periodicity of Doppler shift over time. Extensive experiments show that AudioGuard achieves a miss report rate of 0% and 1.75% for LOS and NLOS intrusion, respectively, and a false alarm rate of 4.17%.

In recent years, we have seen efforts made to monitor respiration for multiple users. Existing approaches capture chest movement relying on signals directly reflected from chest or separate breath waves based on breath rate difference between subjects. However, several limitations exist: 1) they may fail when subjects face away from the transceiver or are blocked by obstacles or other subjects; 2) they may fail to separate subjects' breath waves with the same or similar rates (i.e., breath rate differenceMultiResp, a multi-user respiration monitoring system using acoustic signal. By fully leveraging the abundant acoustic signals reflected indirectly from subjects' chest,MultiRespcan robustly capture chest movement even when they face away from the transceiver or are blocked. By extracting fine-grained breath rate and phase difference between different subjects,MultiRespcan separate the breath waves with the same or similar rates and adapt to dynamic change of subject number during monitoring. Extensive experiments show thatMultiRespis able to accurately monitor the respiration of multiple users with a median error of 0.3 bpm in various indoor scenarios, however, it fails when the sound pressure is lower than 55 dB or body movement is happening.

Contactless respiration monitoring using wireless signals has drawn much attention in recent years. Many approaches have been proposed, however, they may not work when there is a lack of signals directly reflected from target's chest, e.g., a target faces away from the transceiver or a target is blocked by furniture. In this paper, we design and implement a novel omnimonitoring system for human respiration,OmniRespMonitor, using a pair of speaker and microphone. Different from Radio Frequency (RF) signal, acoustic signals cannot penetrate through walls and furniture. The multipath reflection in an indoor environment will result in highly abundant acoustic signals. In this case, even though there are lack of acoustic signals directly reflected by a target's chest, indirectly-reflected acoustic signals can still be received by the microphone. We can therefore monitor the target's respiration by extracting this subtle variation of indirectly reflected signals. To achieve this, we model chest movement using truncated System Frequency Response (SFR). We then develop a global search method based on the autocorrelation function to extract minute chest movement from SFR sequences. Finally, we dynamically synthesize the chest movement information to recover the breathing wave in real time. We conduct extensive experiments with both humans and animals (goat), the results show thatOmniResMonitoris able to monitor single target's respiration within 5 meters in indoor environments in various challenging scenarios there are lack of directly-reflected acoustic signals.

Orthogonal frequency division multiplexing access (OFDMA) which can make full use of frequency resources by using adaptive modulation and coding (AMC) and multi-user diversity, is a promising technology for the next generation wireless communication system. The flexibility of OFDMA also makes the radio resource management (RRM) more complicated. This paper proposes a modified largest weighted delay first (M-LWDF) packet scheduling algorithm with subcarrier allocation for the real time service in the multiuser OFDMA systems. The simulation result shows that it can maximize the system throughput and guarantee the QoS (quality of service) of different users.