Bidirectional intra-network mutual Ambient Backscatter Communications in distributed wireless wearable measurement networks. (October 2021) - Mao, Zhi; Hu, Fengye; Ling, Zhuang; Li, Shuang
Abstract: In this paper, a novel bidirectional backscatter-aided transmission protocol is proposed for wireless powered distributed wearable measurement networks, where we consider channel detection, backscatter-aided wireless power transfer (WPT) and backscatter-aided information transfer. First, the channel detection phase is allocated for both the AP and sensors to get the knowledge of channel state information (CSI) at the beginning of each time block. In the backscatter-aided WPT phase, all sensors harvest radio frequency (RF) energy by converting RF signals from the AP with time-division-multiple-access (TDMA). Finally, the backscatter-aided information transfer phase is allocated to sensors for transmitting their independent information to the AP by TDMA and the harvested energy at each sensor is consumed in this phase. The signals from/to a sensor to/from the AP will be reflected by all other sensors and the optimal reflection coefficient at helping sensors can be calculated according to CSI. Considering fairness among sensors, we maximize sum throughput with energy harvesting constraints and max–min throughput by jointly optimizing the time allocation and the reflection coefficients. Sum and max–min throughput maximization problems are formulated as two convex optimization problems. A low-complexity algorithm is designed to obtain optimal solutions of sum throughput maximization problem with the fairness constraint, and the optimal solutions for max–min throughput maximization are derived as closed-form expressions. Numerical results illustrate the effectiveness of the proposed protocol. Graphical abstract: Highlights: A novel bidirectional backscatter-aided transmission protocol is proposed. Sum and max–min throughput maximization problems with fairness constraints are investigated. The optimal solutions for sum and max–min throughput maximization are obtained.