Performance analysis of cooperative transmission for cognitive wireless relay networks

In this paper, we consider cooperative transmission in cognitive wireless relay networks (CWRNs) over frequency-selective fading channels. We propose a new distributed space-time-frequency block code (DSTFBC) for a two-hop nonregenerative CWRN, where a primary source node and multiple secondary source nodes convey information data to their desired primary destination node and multiple secondary destination nodes via multiple cognitive relay nodes with dynamic spectrum access. The proposed DSTFBC is designed to achieve spatial diversity gain as well as allow for low-complexity decoupling detection at the receiver. Pairwise error probability is then analysed to study the achievable diversity gain of the proposed DSTFBC for different channel models including Rician fading and mixed Rayleigh-Rician fading

Distributed space-time-frequency block code for cognitive wireless relay networks

In this study, the authors consider cooperative transmission in cognitive wireless relay networks (CWRNs) over frequency-selective fading channels. They propose a new distributed space-time–frequency block code (DSTFBC) for a two-hop non-regenerative CWRN, where a primary source node and multiple secondary source nodes convey information data to their desired primary destination node and multiple secondary destination nodes via multiple cognitive relay nodes with dynamic spectrum access. The proposed DSTFBC is designed to achieve spatial diversity gain as well as allow for low-complexity decoupling detection at the receiver. Pairwise error probability is then analysed to study the achievable diversity gain of the proposed DSTFBC for different channel models including Rician fading and mixed Rayleigh–Rician fading

A hybrid double-threshold based cooperative spectrum sensing over fading channels

This paper investigates double-threshold based energy detector for cooperative spectrum sensing mechanisms in cognitive wireless radio networks. We first propose a hybrid double-threshold based energy detector (HDTED) to improve the sensing performance at secondary users (SUs) by exploiting both the local binary/energy decisions and global binary decisions feedback from the fusion centre (FC). Significantly, we derive closed-form expressions and bounds for the probabilities of missed detection and false alarm considering a practical scenario where all channel links suffer from Rayleigh fading and background noise. The derived expressions not only show the improved performance achieved with the HDTED scheme but also enable us to analyse the impacts of the number of the SUs and the fading channels on the cooperative spectrum sensing performance. Furthermore, based on the derived bounds, we propose an optimal SU selection algorithm for forwarding the local decisions to the FC, which helps reduce the number of forwarding bits for a lower-complexity signaling. Finally, numerical results are provided to demonstrate the validity of the analytical findings

Towards connecting people, locations and real-world events in a cellular network

The success of personal mobile communication technologies has led an emerging expansion of the telecommunication infrastructure but also to an explosion to mobile broadband data traffic as more and more people completely rely on their mobile devices, either for work or entertainment. The continuously interaction of their mobile devices with the mobile network infrastructure creates digital traces that can be easily logged by the network operators. These digital traces can be further used, apart from billing and resource management, for large-scale population monitoring using mobile traffic analysis. They could be integrated into intelligent systems that could help at detecting exceptional events such as riots, protests or even at disaster preventions with minimal costs and improve people safety and security, or even save lives. In this paper we study the use of fully anonymized and highly aggregate cellular network data, like Call Detail Records (CDRs) to analyze the telecommunication traffic and connect people, locations and events. The results show that by analyzing the CDR data exceptional spatio-temporal patterns of mobile data can be correlated to real-world events. For example, high user network activity was mapped to religious festivals, such as Ramadan, Le Grand Magal de Touba and the Tivaouane Maouloud festival. During the Ramadan period it was noticed that the communication pattern doubled during the night with a slow start during the morning and along the day. Furthermore, a peak increase in the number of voice calls and voice calls duration in the area of Kafoutine was mapped to the Casamance Conflict in the area which resulted in four deaths. Thus, these observations could be further used to develop an intelligent system that detects exceptional events in real-time from CDRs data monitoring. Such system could be used in intelligent transportation management, urban planning, emergency situations, network resource allocation and performance optimization, etc

Efficient Model Learning for Human-Robot Collaborative Tasks

We present a framework for learning human user models from joint-action demonstrations that enables the robot to compute a robust policy for a collaborative task with a human. The learning takes place completely automatically, without any human intervention. First, we describe the clustering of demonstrated action sequences into different human types using an unsupervised learning algorithm. These demonstrated sequences are also used by the robot to learn a reward function that is representative for each type, through the employment of an inverse reinforcement learning algorithm. The learned model is then used as part of a Mixed Observability Markov Decision Process formulation, wherein the human type is a partially observable variable. With this framework, we can infer, either offline or online, the human type of a new user that was not included in the training set, and can compute a policy for the robot that will be aligned to the preference of this new user and will be robust to deviations of the human actions from prior demonstrations. Finally we validate the approach using data collected in human subject experiments, and conduct proof-of-concept demonstrations in which a person performs a collaborative task with a small industrial robot

Functional rescue of dystrophin deficiency in mice caused by frameshift mutations using Campylobacter jejuni Cas9

Duchenne muscular dystrophy (DMD) is a fatal, X-linked muscle wasting disease caused by mutations in the DMD gene. In 51% of DMD cases, a reading frame is disrupted because of deletion of several exons. Here, we show that CjCas9 derived from Campylobacter jejuni can be used as a gene editing tool to correct an out-of-frame Dmd exon in Dmd knockout mice. Herein, we used Cas9 derived from S. pyogenes to generate Dmd knockout (KO) mice with a frameshift mutation in Dmd gene. Then, we expressed CjCas9, its single-guide RNA, and the eGFP gene in the tibialis anterior muscle of the Dmd KO mice using an all-in-one adeno-associated virus (AAV) vector. CjCas9 cleaved the target site in the Dmd gene efficiently in vivo and induced small insertions or deletions at the target site. This treatment resulted in conversion of the disrupted Dmd reading frame from out-of-frame to in-frame, leading to the expression of dystrophin in the sarcolemma. Importantly, muscle strength was enhanced in the CjCas9-treated muscles, without off-target mutations, indicating high efficiency and specificity of CjCas9. This work suggests that in vivo DMD frame correction, mediated by CjCas9 has great potential for the treatment of DMD and other neuromuscular diseases

Circular strings in Kerr-AdS5AdS_5 black holes

The quest for extension of holographic correspondence to the case of finite temperature naturally includes Kerr-AdS black holes and their field theory duals. We probe the five-dimensional Kerr-AdS space time by pulsating strings. First we find particular pulsating string solutions and then semi-classically quantize the theory. For the string with large values of energy, we use the Bohr-Sommerfeld analysis to find the energy of the string as a function of a large quantum number. We obtain the wave function of the problem and thoroughly study the corrections to the energy, which according to the holographic dictionary are related to anomalous dimensions of certain operators in the dual gauge theory. The interpretation of results from holographic point of view is not straightforward since the dual theory is at finite temperature. Nevertheless, near or at conformal point the expressions can be thought of as the dispersion relations of stationary states.Comment: 32 pp, 1 figure; v2: Sec.3 improved, Sec.4 recalculated for a general case, typos corrected, Appendix B included; v3: Sec.3 corrected, new figure of an effective potential added, typos correcte

Bounds on Lorentz and CPT Violation from the Earth-Ionosphere Cavity

Electromagnetic resonant cavities form the basis of many tests of Lorentz invariance involving photons. The effects of some forms of Lorentz violation scale with cavity size. We investigate possible signals of violations in the naturally occurring resonances formed in the Earth-ionosphere cavity. Comparison with observed resonances places the first terrestrial constraints on coefficients associated with dimension-three Lorentz-violating operators at the level of 10^{-20} GeV.Comment: 8 pages REVTe