As one of the main driving forces behind modern ubiquitous communication and computing, new 5G wireless technologies aim for substantially broader coverage (10-100x number of connected devices) with special focus on supporting low-power Internet-of-Things (IoT) devices, which will further propel the ongoing revolution within the telecommunications and high-tech industries for the next decade. One key technique underpinning the latest development of 5G and beyond standards is the use of multi-hop wireless connections and advanced backhauling to enable flexible extension of range and coverage area. Nonetheless, the industry-standard multi-hop communication schemes are still based on concepts developed 40 years ago, which incur intolerably high complexity and long delay with respect to the high throughput (1-10Gbps) and low latency (1ms) requirements of 5G networks and beyond. There is thus an urgent need for new multi-hop communication paradigms that simultaneously optimize throughput, delay, and complexity.
This project proposes a new multi-hop communication paradigm called transcoding, a much needed revamp of the 40-year old industry standard called decode-and-forward. Specifically, transcoding takes a back-to-basics approach, which reexamines and analyzes the causes of the long-delay and high-complexity of the decode-&-forward policies. New strategies will then be designed accordingly, which will substantially improve the delay-tradeoff performance of multi-hop communications while significantly lowering the complexity. By breaking away from the decode-&-forward paradigm, the fundamentally new design philosophy of transcoding takes full advantage of the exciting recent development in single-hop wireless communications and in information theory. The results of this project will lead to new structured, low-complexity multi-hop "transcoders" that achieve high-throughput and low-latency necessary for the emerging 5G and IoT applications. The approaches and activities in this project include theoretical capacity analysis, new signal processing designs, network resource optimization, and testbed implementation and performance verification.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
