Research Terms
L2Relay is a novel packet relay protocol for Wi-Fi networks that can improve the performance and extend the range of the network. It is designed to be a layer 2 solution that has direct control over many layer 2 functionalities such as carrier sense. The device solves unique problems including link measurement, rate adaptation, relayer selection, and relayer collision detection.
Commercial range extenders that are easy to install are currently available on the market. However, they extend the range by capturing and rebroadcasting all transmitted packets, which is known to reduce network throughput in many cases because the node may be close to the Access Point (AP) and may be able to receive from the AP directly such that the rebroadcasting of the packets is completely unnecessary.
An L2Relay device runs an intelligent protocol that selectively repeats packets only when necessary, thus practically never degrades the network performance. L2Relay is designed for ubiquitous compatibility without the need of any modification to the nodes and the AP; as a result, an L2Relay device can be easily installed by simply plugging into a wall outlet in any Wi-Fi network and bring immediate benefits.
L2Relay has many distinct features due to the requirement of not modifying the AP and the nodes, as well as exploiting the Layer 2 information. Our solutions to link measurement, rate adaptation, relayer selection, and relayer collision detection are completely different from the academic prototype solutions that require the AP to act as a central controller, such as CoopMAC. In addition, our solutions are novel because they are based on the Layer 2 information. In wireless networks, Layer 2 is the data link layer which handles issues such as medium access. The existing academic prototype solutions are implemented above the Layer 2, such that they suffer many restrictions and do not have access to much useful infonnation such as the medium idle time. On the contrary, L2Relay functions within Layer 2 and has access to such information, which enables it to solve many problems very efficiently.
A wireless communication technology for Low Power Wide Area Networks (LPWAN). The Internet of Things (IoT) applications depend on LPWAN to connect a large number of low power devices to the Internet over long distances. ZCNET achieves significantly higher capacity (20x over LoRa), while using less resources. ZCNET supports 8 parallel channels within a single frequency band that do not severely interfere with each other, and ZCNET can resolve collisions inside a channel by using a small range for each node. ZCNET has been extensively tested with real-world experiments on the USRP and trace-based simulations.
Professor Zhang and his team have developed A reliable fall detection system has tremendous value to the well-being of seniors living alone. We design and implement MultiSense, a novel fall detection system, which has the following desirable features. First, it does not require the human to wear any device, therefore convenient to seniors. Second, it has been tested in typical settings including living rooms and bathrooms, and has shown very good accuracy. Third, it is built with inexpensive components, with expected hardware cost around $150 to cover a typical room. Therefore, it has a key advantage over the current commercial fall detection systems which all require the human to wear some device, as well as over academic research prototypes which have various limitations such as lower accuracy. The high accuracy is achieved mainly by combining senses from multiple types of sensors that complement each other, which includes a motion sensor, a heat sensor, and a floor vibration sensor. Roughly speaking, the activities confusing to some sensors are often not confusing to others, and vice versa; therefore, combining multiple types of sensors can bring the performance to a level that can meet the requirements in practice.
TnB is designed for LoRa networks to improve capacity and communication performance. LoRa is currently the strongest contender as the technology for Low Power Wide Area Networks (LPWAN), where many nodes connect to base stations over long distances. TnB improves the capacity of a LoRa network by more than 2-3-fold, due to a novel algorithm that can decode packets that are transmitted by multiple nodes simultaneously and do so more reliably. An intelligent algorithm decodes error correction codes used in LoRa and can quickly correct the number of errors. There is no need for modification in TnB so a network operator can simply replace its base station hardware and experience immediate performance improvements.
CSIApx is a very simple algorithm for the compression of the Channel State Information (CSI) of OFDM systems. The algorithm is guided by rigid mathematical findings and has with bounded performance. It is very suitable to be implemented in hardware because it involves only a small number of complex multiplications, similar to that of a digital FIR filter. In the illustrated embodiment CSIApx has been extensively tested with both experimental data and the Wi-Fi channel model, and the results confirm that while dramatically reducing the computation complexity, CSIApx still significantly outperforms the existing solutions both in compression ratio and accuracy, in nearly all cases.
Accordingly, the present invention provides an improved system and method for compressing the CSI for OFDM that is accurate and computationally easy to implement.