Buffer-Aided Distributed Compressed Transmission and Fusion Under Energy and Reliability Constraints

The distributed diversity reception with quantization and fusion has garnered considerable attention for improved reliability. In this paper, we introduce a novel buffer-aided distributed compressed transmission and fusion (DCTF) technique to cope with the fading effect and to improve the energy consumption of wireless sensor networks (WSNs). Exploiting the transmission flexibility enabled by data buffering, we design an optimal communication protocol by maximizing the average fusion rate at the FC subject to reliability, spectral efficiency, and energy consumption constraints. Unlike prior distributed reception schemes, our approach does not require any subjective quantization level setting; the compression rate in our approach is optimized by maximizing the average fusion rate. Based on the optimized compression rate, we develop two adaptive protocols, namely, adaptive multi-rate (AMR) and its simplified version, adaptive on-off (AOO). In contrast to the non-buffered scheme, the flexibility offered by buffering is exploited in our approach to lower the battery drainage in conjunction with opportunistic energy harvesting (EH). Through Monte-Carlo simulations we evaluate the performance of the proposed protocols under different scenarios and in comparison to the non-adaptive benchmark. Findings reveal that the proposed methodologies outperform conventional schemes in terms of reliability, energy consumption, and average fusion rate.