Sum‐throughput maximization for overlay cognitive wireless powered network with energy harvesting capability

Abstract

In this article, a novel time division multiple access (TDMA)-based approach for optimal resource allocation in an overlay cognitive wireless powered communication network is proposed. In this network, power in the secondary network (SN) is provided by the primary network (PN) in addition to its own wireless network. Using the TDMA and a harvest-then-transmit protocol, the time and power allocation for downlink wireless energy transfer (WET) and uplink wireless information transmission (WIT) are jointly optimized to maximize the sum-throughput in SN. Quality of service in PN and power and time in SN, as the main constrains are considered for sum-throughput maximization in this network. This is a non-convex problem which gets converted to a convex problem using active interference-temperature control technique. Moreover, a new closed-form expression which results in sub-optimal power and time-allocation (SO-PT-A) is addressed. The performance of proposed algorithm is compared with the equal time allocation (ETA) and fixed TDMA-allocation (FTDMA-A) algorithms which impose some special constraints for optimal power and time allocation. The simulation results depict that the SO-PT-A algorithm outperforms the ETA and FTDMA-A algorithms. Eventually, the performance of the SO-PT-A algorithm is evaluated with other well-known algorithms considering different values of the average and maximum transmit power of the hybrid-access point (H-AP), the number of secondary users (SUs) and path loss exponent.

Stability and performance analysis of wireless powered communication networks

“…Similar researches on such throughput maximization problems can be found in recent papers. [11][12][13] On the other hand, several different medium access control (MAC) protocols such as RF-MAC and PP-MAC were reviewed and compared in Iannello et al 14 and Sherazi et al 15 According to the comparison among various MAC protocols, 15 RF-MAC 16 is obviously superior to other MAC protocols because it considers many key issues such as adjusting the energy charging threshold, energy-aware access priority, requesting and granting energy, etc. In addition, the work 17 proposed a novel optimal scheduling strategy, named energy harvesting Markov decision process (EHMDP), to decrease data loss.…”