Very Efficient Tone Reservation PAPR Reduction Fully Compatible With ATSC 3.0 Standard: Performance and Practical Implementation Analysis

• Main Authors: Naila Lahbabi, S. S. Krishna Chaitanya Bulusu, Jean-Francois Helard, Matthieu Crussiere
• Format: Article
• Language: English
• Published: IEEE 2018-01-01
• Series: IEEE Access
• Subjects: OFDM; broadcasting; peak-to-average power ratio; power control; ATSC 3.0; non-linear HPA
• Online Access: https://ieeexplore.ieee.org/document/8485685/

A common issue in any multicarrier communication system such as the American digital video broadcasting (ATSC 3.0) standard is the high peaks of the transmitted signal. This disadvantage constrains the high power amplifiers to be deployed in their linear region which lowers their power efficiency. To overcome this issue, various techniques aiming at reducing the signal fluctuations have been investigated. Recently, Tone Reservation (TR)-based algorithms have been studied and proposed for the second generation of digital video broadcasting (DVB-T2) and ATSC 3.0 standards. The algorithm is essentially based on an iterative gradient approach to cancel one peak of the time-domain signal at each iteration. In this paper, we propose a novel TR-based algorithm implementable and compatible with the ATSC 3.0 standard and named as grouped carrier peak windowing (GCPW). This algorithm is based on a new kernel definition targeting the cancellation of multiple signal peaks at a time which highly reduces the total number of iterations, therefore reducing the system global latency and being more suited for implementation in today’s ATSC 3.0 transmitters. Taking into account hardware resources requirements, we propose a new method to select the highest signal peaks to be considered in the PAPR reduction process. Hence, the system latency, complexity, and memory resources are reduced and better performance than the ATSC 3.0 gradient-based algorithm can be offered. The implementation of the GCPW algorithm in fixed-point architectures is also studied and optimized in this paper. We demonstrate through simulation results that the proposed algorithm offers very good performance/latency/complexity/memory tradeoff in both floating and fixed point implementations.