Rate Control for Wireless-Powered Communication Network With Reliability and Delay Constraints

Abstract

We consider a two-phase Wireless-Powered Communication Network under Nakagami-m fading, where a wireless energy transfer process first powers a sensor node that then uses such energy to transmit its data in the wireless information transmission phase. We explore a fixed transmit rate scheme designed to cope with the reliability and delay constraints of the system while attaining closed-form approximations for the optimum wireless energy transfer and wireless information transmission blocklength. Then, a more-elaborate rate control strategy exploiting the readily available battery charge information is proposed and the results evidence its outstanding performance when compared with the fixed transmit rate, for which no battery charge information is available. It even reaches an average rate performance close to that of an ideal scheme requiring full Channel State Information at transmitter side. Numerical results show the positive impact of a greater number of antennas at the destination, and evidence that the greater the reliability constraints, the smaller the message sizes on average, and the smaller the optimum information blocklengths. Finally, we corroborate the appropriateness of using the asymptotic blocklength formulation as an approximation of the non-asymptotic finite blocklength results.Index Terms-WPCN, reliability and delay constraints, rate control, finite blocklength.

Toward Efficient 6G IoT Networks: A Perspective on Resource Optimization Strategies, Challenges, and Future Directions

“…In [117], the joint optimization problem of Fixed Transmit Rate (FTR) in wireless communication networks with reliability constraints has been investigated. Emulation consequences indicate that the devised rate control concept could accomplish greater reliability constraints in multiple antennas.…”

“…To achieve a high reliability and high rate communication network, numerous effective optimization strategies for optimizing reliability and rate simultaneously for 5G and 6G IoT communication systems have been given in this section [117], [118], [119]. The three papers collectively address challenges related to optimizing reliability in wireless communication networks, employing various techniques and approaches.…”

“…The three papers collectively address challenges related to optimizing reliability in wireless communication networks, employing various techniques and approaches. Paper [117] focuses on joint optimization of FTR with reliability constraints, utilizing a rate control concept. In contrast, [118] investigates power allocation in fading channels to enhance reliability and sum rate in PD-NOMA networks, while [119] identifies transmission rate optimization for ultrareliability constraints in URLLC using EVT.…”

“…In contrast, [118] investigates power allocation in fading channels to enhance reliability and sum rate in PD-NOMA networks, while [119] identifies transmission rate optimization for ultrareliability constraints in URLLC using EVT. While each paper demonstrates improvements in reliability, common limitations include considering imperfect CSI [117], addressing IoT device mobility [118], and enhancing real-time algorithm performance [119]. Addressing these factors would enhance the practical applicability and effectiveness of the proposed methods.…”

Statistical Tools and Methodologies for Ultrareliable Low-Latency Communication—A Tutorial

“…The average error probability for block fading channels is given by ε = E γ [ϵ(γ)]. 16 Interestingly, it has been shown in [14], [112], and [113] that the effect of the fading on (49) vanishes the FBL impact on two cases, when the following hold: 1) k is not extremely small and 2) there is not a strong LOS component (e.g., as in Rayleigh fading). In such cases, the asymptotic outage probability is a good approximation for ε, i.e., ε = Pr[γ < 2 k/N − 1] = F γ (2 k/N − 1), as shown in Fig.…”