A Physical Layer Security (PLS) approach through Address Fed Mapping Crest Factor Reduction applicable for 5G/6G signals

The privacy and security of 5G/6G infrastructures are receiving great attention together with power consumption and efficiency. Here, Physical Layer Security (PLS) is considered and a technique named Address Fed Mapping (AFM) is proposed which not only enhances the physical layer security, but also reduces the effect of high Peak to Average Power Ratio (PAPR), which results in efficiency improvement in OFDM based signals used in beyond 5G and 6G. The AFM is designed based on the idea of randomly generated signals, modifying the original signal to reduce PAPR. Instead of a typical randomization algorithm, a unique key is generated based on Channel response that is known only transmitter-receiver pairs. This key is used to pick a signal and send it. It is shown that the proposed AFM technique reduces PAPR, which improves the energy efficiency of the system

SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2

Abstract Background Since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. Methods We present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September–27 September 2021) and 15 (19 October–5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month. Results We identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI 8–23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England. Conclusions As SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals. </jats:sec