Nowadays wireless networking is becoming more and more popular in our daily life. Compared with wired counterpart, wireless communication suffers a lot from the problems like interference in surrounding environment, low transmission rate, etc. Research literature tries different ways of enhancing wireless network performance. Particularly in Physical layer (PHY), many novel technologies have been proposed, such as Multiple Input Multiple Output (MIMO), zigzag decoding, full duplex antenna, etc.

Pursuing the same goal of enhancing wireless networking performance, two of my research projects, namely SimCast and TiM, enhance the performance of wireless networking in PHY.

SimCast is a cross-layer design for achieving efficient concurrent video uploading/downloading in MU-MIMO WLANs....[ Read more ]

Nowadays wireless networking is becoming more and more popular in our daily life. Compared with wired counterpart, wireless communication suffers a lot from the problems like interference in surrounding environment, low transmission rate, etc. Research literature tries different ways of enhancing wireless network performance. Particularly in Physical layer (PHY), many novel technologies have been proposed, such as Multiple Input Multiple Output (MIMO), zigzag decoding, full duplex antenna, etc.

Pursuing the same goal of enhancing wireless networking performance, two of my research projects, namely SimCast and TiM, enhance the performance of wireless networking in PHY.

SimCast is a cross-layer design for achieving efficient concurrent video uploading/downloading in MU-MIMO WLANs. Wireless video stream delivery is choppy. This problem becomes much severer in MU-MIMO's simultaneous video transmission within the same band. Conventional schemes achieve graceful video delivery by harnessing from high data redundancy. However, with concurrent transmission in the same band, the leverage of high data redundancy leads to high probability of collisions and packets loss, which limits the performance. In concurrent video transmission, achieving efficiency over varied link condition is the main issue. To address this issue, I propose S̲i̲m̲Cast (S̲i̲m̲ultaneous). The key idea of SimCast is to harness frequency diversity of the channel and spatial similarity of users.

TiM is a novel 3D modulation scheme to achieve fine-grained rate adaptation in wireless networking. Channel condition varies frequently in wireless networks. To achieve good performance, devices need rate adaptation. In rate adaptation, choosing proper modulation schemes based on channel conditions is vital to the transmission performance. However, due to the natural character of discrete modulation types and continuous varied link conditions, we cannot make a one-to-one mapping from modulation schemes to channel conditions. This matching gap causes either over-select or underselect modulation schemes which limits throughput performance. To fill-in the gap, I propose TiM (T̲i̲me-line M̲odulation), a novel 3-Dimensional modulation scheme by adding time dimension into current amplitude-phase domain schemes. With estimation of channel condition, TiM changes base-band data transmission time by artificially interpolating values between original data points without changing amplitude-phase domain modulation type.

Recent research has extended the functionality of wireless signals into a new realm. More precisely, they push the limit of ISM (Industrial Scientific and Medical) band from data delivery to radiometric detection, including motion detection, recognition, localization, and even classification. By detecting and analyzing signal reflection, these approaches enable Wi-Fi signals to "See" or "Sense" target objects. This kind of sensing works via wireless signals can be collectively referred to as "Wi-Fi Radar".

WiHear system follows the "Wi-Fi Radar" trend, which bridges communication between human speaking and wireless signals. My WiHear system enables Wi-Fi signals to "hear" our talks without deploying any devices. To achieve this, WiHear needs to detect and analyze fine-grained radio reflections from mouth movements. WiHear solves this micro-movement detection problem by introducing Mouth Motion Profile that leverages partial multipath effects and wavelet packet transformation. Since Wi-Fi signals do not require line-of-sight, WiHear can "hear" people talks within the radio range. Further, WiHear can simultaneously "hear" multiple people's talks leveraging MIMO technology.