Optimum MCS for high-throughput long-range ambient backscatter communication networks

Ambient backscatter is a promising solution for future Internet of Things (IoT) composed of massive low-power wireless devices without external power sources. It is challenging to accommodate these devices with high throughput and long range because of the low efficiency inherent in ambient backscatter. To tackle the challenging issue, we propose an optimum modulation and coding scheme (MCS) for ambient backscatter communication networks (ABCN). We model and analyze the ABCN embedded by semi-passive tags with M-ary modulation and full-duplex WiFi access points as reader. The coverage and network capacity are derived, by which the effect of various system parameters including reflection coefficient, code rate, and cluster size is investigated. It is shown that the optimum MCS for the ABCN will provide highly increased throughput and range for future IoT networks and smart home/office.