Reliability performance analysis of half-duplex and full-duplex schemes with self-energy recycling

Abstract. Radio frequency energy harvesting (EH) has emerged as a promising option for improving the energy efficiency of current and future networks. Self-energy recycling (sER), as a variant of EH, has also appeared as a suitable alternative that allows to reuse part of the transmitted energy via an energy loop. In this work we study the benefits of using sER in terms of reliability improvements and compare the performance of full-duplex (FD) and half-duplex (HD) schemes when using multi-antenna techniques at the base station side. We also assume a model for the hardware energy consumption, making the analysis more realistic since most works only consider the energy spent on transmission. In addition to spectral efficiency enhancements, results show that FD performs better than HD in terms of reliability. We maximize the outage probability of the worst link in the network using a dynamic FD scheme where a small base station (SBS) determines the optimal number of antennas for transmission and reception. This scheme proves to be more efficient than classical HD and FD modes. Results show that the use of sER at the SBS introduces changes on the distribution of antennas for maximum fairness when compared to the setup without sER. Moreover, we determine the minimum number of active radio frequency chains required at the SBS in order to achieve a given reliability target

Machine learning techniques for self-interference cancellation in full-duplex systems

Full-duplex (FD), enabling remote parties to transfer information simultaneously in both directions and in the same bandwidth, has been envisioned as an important technology for the next-generation wireless networks. This is due to the ability to leverage both time and frequency resources and theoretically double the spectral efficiency. Enabling the FD communications is, however, highly challenging due to the self-interference (SI), a leakage signal from the FD transmitter (Tx) to its own receiver (Rx). The power of the SI is significantly higher when compared with the signal of interest (SoI) from a remote node due to the proximity of the Tx to its co-located Rx. The SI signal is thus swamping the SoI and degrading the FD system's performance. Traditional self-interference cancellation (SIC) approaches, spanning the propagation, analog, and/or digital domains, have been explored to cancel the SI in FD transceivers. Particularly, digital domain cancellation is typically performed using model-driven approaches, which have proven to be effective for SIC; however, they could impose additional cost, hardware, memory, and/or computational requirements. Motivated by the aforementioned, this thesis aims to apply data-driven machine learning (ML)-assisted SIC approaches to cancel the SI in FD transceivers|in the digital domain|and address the extra requirements imposed by the traditional methods. Specifically, in Chapter 2, two grid-based neural network (NN) structures, referred to as ladder-wise grid structure and moving-window grid structure, are proposed to model the SI in FD transceivers with lower memory and computational requirements than the literature benchmarks. Further reduction in the computational complexity is provided in Chapter 3, where two hybrid-layers NN structures, referred to as hybrid-convolutional recurrent NN and hybrid-convolutional recurrent dense NN, are proposed to model the FD SI. The proposed hybrid NN structures exhibit lower computational requirements than the grid-based structures and without degradation in the SIC performance. In Chapter 4, an output-feedback NN structure, referred to as the dual neurons-` hidden layers NN, is designed to model the SI in FD transceivers with less memory and computational requirements than the grid-based and hybrid-layers NN structures and without any additional deterioration to the SIC performance. In Chapter 5, support vector regressors (SVRs), variants of support vector machines, are proposed to cancel the SI in FD transceivers. A case study to assess the performance of SVR-based approaches compared to the classical and other ML-based approaches, using different performance metrics and two different test setups, is also provided in this chapter. The SVR-based SIC approaches are able to reduce the training time compared to the NN-based approaches, which are, contrarily, shown to be more efficient in terms of SIC, especially when high transmit power levels are utilized. To further enhance the performance/complexity of the ML approaches provided in Chapter 5, two learning techniques are investigated in Chapters 6 and 7. Specifically, in Chapter 6, the concept of residual learning is exploited to develop an NN structure, referred to as residual real-valued time-delay NN, to model the FD SI with lower computational requirements than the benchmarks of Chapter 5. In Chapter 7, a fast and accurate learning algorithm, namely extreme learning machine, is proposed to suppress the SI in FD transceivers with a higher SIC performance and lower training overhead than the benchmarks of Chapter 5. Finally, in Chapter 8, the thesis conclusions are provided and the directions for future research are highlighted

The Alestle - Vol. 49 No. 15 - 09/05/1996

Vol. 49 No. 1

Central Florida Future, Vol. 19 No. 65, May 27, 1987

People fear touch of man who might have AIDS; MCI, others going all out after college phone hackers; Campus murder raises questions; News: Professor visits USSR, talks with Soviet space officials (with photos); News clips; Opinion: When will our leaders be sorry for their wrongs?; The other side of nowhere: Buyer beware, vultures abound (by Tim Ball); Future world: I don\u27t know how to tell you this (by Chris Richcreek); Health Bolt (presented by the UCF Student Health and Wellness Center); Features; 12 Knights in Sports Festival? (with photo of Michelle Akers, Amy Allmann, Jean Varas, Sandy Carter; Lady Knights [soccer] go for championship run this fall.https://stars.library.ucf.edu/centralfloridafuture/1707/thumbnail.jp

Restriction-Modification and CRISPR-Cas Systems: Cooperation Between Innate and Adaptive Immunity in Prokaryotes

Bacteria have evolved numerous mechanisms to resist the constant assault of viruses (called bacteriophages, or simply phages) that can infect and kill them. Restriction-modification (RM) systems represent one such strategy. Generally, these systems provide defense by coordinating the activities of two distinct enzymes: a restriction endonuclease and a methyltransferase. Both enzymes recognize the same short DNA sequences. The methyltransferase modifies these target sites in the host chromosome, which prevents the restriction endonuclease from cleaving the host’s own DNA. In contrast, foreign phage DNA is usually not methylated at these sequences. Consequently, upon injection into the host, the viral DNA is recognized and cleaved by the restriction endonuclease, preventing the progression of the phage’s life cycle. Therefore, RM systems are considered a part of the innate immune response because they can provide defense against any phage, including ones that have never been encountered previously, as long as they harbor RM target sites. Clustered regularly interspaced short palindromic repeats (CRISPR) loci and their associated genes (cas) form another defense system that destroys foreign DNA. The CRISPR array consists of a series of repetitive DNA sequences separated by unique DNA sequences known as spacers. During phage infection, short DNA fragments are taken from the viral DNA and integrated into the CRISPR locus to form new spacers. These sequences are then transcribed into CRISPR RNAs (crRNAs). In type II-A CRISPRCas systems, the crRNAs guide the Cas9 nuclease to a matching viral DNA target for cleavage. As such, unlike RM systems, CRISPR-Cas systems represent an adaptive immune response because they require an initial exposure to a virus in order to become successfully immunized through the acquisition of new spacer sequences. CRISPR-Cas and RM are two of the most prevalent types of defense systems found in bacteria and often co-exist together in a single host. Yet, how they may interact with each other in the context of immunity during bacteriophage infection is poorly understood. Here, in my thesis work, I investigate the interplay between RM and type II-A CRISPR-Cas systems. First, I demonstrate that RM systems provide a weak and temporary protection that stimulates CRISPR spacer acquisition, enabling the cells to survive the viral infection. Then, I go on to show that the restriction activity of the RM system is critical for this process and that the rate of spacer acquisition is correlated to the number of RM target sites in the phage genome. To further uncover the mechanistic link between restriction and the acquisition of new spacers, I implement next-generation sequencing to demonstrate that spacers are preferentially extracted at the dsDNA breaks (DSBs) generated by the restriction endonuclease. Additionally, I show that the host DNA repair complex, AddAB, can process these breaks, which further enhances spacer acquisition. Finally, I follow the dynamics between RM and CRISPR-Cas during the chain of events that occur upon viral infection. I demonstrate that although the RM system provides an immediate line of defense due to its ability to recognize a broad range of foreign invaders, it is ultimately overcome by the rapid emergence of methylated phages, resulting in the death of much of the bacterial population. However, the early RM immune response creates substrates for spacer acquisition by the CRISPR-Cas system in a subset of cells. By using these newly acquired spacers which specify the viral sequences for lethal cleavage by Cas9, these cells can now extinguish the methylated phages, resulting in the survival and regrowth of the population. Collectively, my thesis reveals the molecular mechanisms connecting RM and CRISPR-Cas systems in providing a synergistic anti-phage defense. Reminiscent of eukaryotic immunity, I demonstrate that RM systems provide an initial, short-lived innate immune response, which stimulates a secondary, more robust adaptive immune response by CRISPR-Cas. This work highlights an example of cooperation between RM and CRISPR-Cas, which are two of the most common bacterial defense systems. However, prokaryotes have been shown to harbor a multitude of other putative antiphage defense systems, which can often exist together in a single host. I predict that future studies will likely uncover many more fascinating instances of immune interaction among other sets of defense systems

Daily Eastern News: November 01, 2006

https://thekeep.eiu.edu/den_2006_nov/1009/thumbnail.jp