A powerful PTS strategy boosted by a novel discrete crow search algorithm for reducing the PAPR of UFMC signals

Abstract

As being one of the main waveform candidates developed for meeting the demands of fifth generation (5G) and beyond telecommunication technologies, universal filtered multicarrier (UFMC) has various appealing features contributing to overcome many obstacles in wireless communication. However, due to the usage of multiple subcarriers, UFMC signals suffer from having high peak-to-average power ratio (PAPR), which has to be kept at low level to prevent the communication quality from being deteriorated. To overcome the problem of high PAPR in the UFMC signals, an advanced version of partial transmit sequence (PTS) was created for PAPR alleviation by integrating an intelligent optimization algorithm in place of its random phase generator. To this end, crow search algorithm (CSA) was utilized. Initially, its novel discrete version called DCSA was developed to make it suitable to be employed in phase sequence optimization, which is a type of combinatorial optimization problem to be solved in discrete space. After the integration of DCSA into the conventional PTS, an advanced PTS variant named DCSA-PTS was created for the UFMC. Optimizing the phase sequences via the DCSA instead of generating them in a random way enhances the performance of PTS scheme. Thanks to the DCSA-based phase optimization, it becomes possible to attain better phase combinations in smaller number of searches. The advantage of using DCSA as a phase optimizer is supported by the simulation results. Due to the superior phase optimization performance of our novel DCSA, the proposed DCSA-PTS strategy clearly outperforms the other schemes considered in this paper.