# A System-Level Methodology for the Design of Reliable Low-Power Wireless Sensor Networks
To this end, a background noise model and a modified log-normal path loss model to estimate the RSS are introduced. A mapping function between the packets-received-ratio (PRR), background noise, and RSS is then proposed. Through a case study, the work demonstrates the feasibility of the solution and increases the reliability by computing the maximum deployment distance between sensor nodes. Yet, the energy consumption cost is not quantitatively evaluated and optimized as the work mentions that the nodes are energy-limited devices. Moreover, the latency is not clearly addressed. After adjusting the wireless link parameters, bit and packet errors can still occur. Therefore, as previously mentioned, FEC, ARQ schemes, or both are used. As FEC has a limited ability to correct errors, the authors in [47] propose a dynamic error control scheme based on link parameters such as BER and ambient noise in WSN. Through simulations, it is reported that throughput and retransmission probability are improved. An energy model that showcases the efficiency of the proposed technique is not reported in that work. As ARQ-based protocols suffer from feedback error, work in [39] studies different approaches allowing to increase feedback channel time diversity and attain different reliability regions with respect to feedback channel error rate such as the \(L\)-REP-ACK scheme. The latter is a modified version of the stop-and-wait (SAW) ARQ scheme. Then, the work proposes a new method of acknowledging packet delivery for retransmission protocols, which is based on backwards composite acknowledgment from multiple packets while relying on collaboration between transmitter (TX) and receiver (RX) nodes. Therefore, depending on channel quality, the scheduler of the wireless channel would be able to configure ultra-reliable communication when needed. The proposed solution does not require increasing the time diversity order of the feedback channel and, thus, does not incur energy consumption and latency overheads. Moreover, the work investigates the advantages and disadvantages of blind retransmissions and shows that, in extremely unreliable feedback channel conditions, an open-loop solution is viable, in terms of reliability, while noting the energy consumption downside. However, in none of the studied solutions does the work quantitatively evaluate the energy consumption nor the latency overheads. As in most cases, a good compromise between reliability, latency, and energy consumption needs to be found and the evaluation of these three performance metrics needs to be carried out simultaneously. In [48], the work studies the possibility of achieving a 0.99999 packet success probability within a 1 ms latency, while bearing in mind the capacity of the network. To this end, the work avoids the reliance on imperfect and error-prone feedback channels and proposes a novel scheme based on blind retransmissions coupled with successive interference cancellation to receive the remaining non-decoded data with a low latency penalty, when compared with the feedback-based retransmission schemes. Finally, it is reported that depending on the number of users sharing the resources, the novel scheme can be more resource efficient than a conservative single shot transmission. However, the work assumes fast processing and transmitting/receiving times. This assumption can also lead to a significant communication range reduction when operating at high data rates. The remainder of this paper is structured as follows: Section 2 presents the sensor node's energy model and modeling framework. Section 3 explains the proposed wireless link characterization approach and presents the proposed path-loss model. Section 4 describes how the achievable data rate can be estimated. Section 5 presents the theory behind the reliability performance of different data transfer techniques. Section 6 summarizes the methodology and includes two case studies where the reliability-latency-energy trade-off is highlighted. Finally, Section 7 concludes the paper.