Theory of Non-Equilibrium Sationary States as a Theory of Resonances

We study a small quantum system (e.g. a simplified model for an atom or molecule) interacting with two bosonic or fermionic reservoirs (say, photon or phonon fields). We show that the combined system has a family of stationary states, parametrized by two numbers $T_1$, $T_2$ (``reservoir temperatures''). If $T_1\neq T_2$, then these states are non-equilibrium, stationary states (NESS). In the latter case we show that they have nonvanishing heat fluxes and positive entropy production. Furthermore, we show that these states are dynamically asymptotically stable. The latter means that the evolution with an initial condition, normal with respect to any state where the reservoirs are in equilibria at temperatures $T_1$ and $T_2$, converges to the corresponding NESS. Our results are valid for the temperatures satisfying the bound $\min(T_1, T_2) > g^{2+\alpha}$, where $g$ is the coupling constant and $0< \alpha<1$ is a power related to the infra-red behaviour of the coupling functions.Comment: 1 figure. To appear in Ann. H. Poincar

Incumbent user active area detection for Licensed Shared Access

© 2015 IEEE. Licensed Shared Access is a European standardisation effort which promotes repository based quasi-static hierarchical spectrum sharing. In this scheme the sharing time base is in the order of months if not years. For widespread use of Licensed Shared Access, shrinking the sharing time base is crucial. In this paper we propose a scheme to reduce the sharing time base to seconds or minutes scale. We present a new technique named lightweight Radio Environment Map based on a Kalman Filter derived from geo-location aware spectrum measurements, which can be run at the shared access licensee end. Our objective is to determine the active area of a static or slowly moving incumbent. We consider a challenging scenario where a large fraction of measurements is missing and the available measurements are highly distorted. Performance of our incumbent active area detection approach is evaluated by simulating a low power incumbent in an urban cellular environment. Simulation results show a substantial improvement of missed detection area in comparison to the counterpart that does not use our lightweight Radio Environment Map

Radiative distortion of kinematic edges in cascade decays

Kinematic edges of cascade decays of new particles produced in high-energy collisions may provide important constraints on the involved particles' masses. For the exemplary case of gluino decay g˜→qq¯χ˜ into a pair of quarks and a neutralino through a squark resonance, we study the hadronic invariant mass distribution in the vicinity of the kinematic edge. We perform a next-to-leading order calculation in the strong coupling αs and the ratio of squark width and squark mass Γq˜/mq˜, based on a systematic expansion in Γq˜/mq˜. The separation into hard, collinear and soft contributions elucidates the process-dependent and universal features of distributions in the edge region, represented by on-shell decay matrix elements, universal jet functions and a soft function that depends on the resonance propagator and soft Wilson lines.The work of M.B. has been supported in part by the Bundesministerium für Bildung und Forschung (BMBF) under project no. 05H15W0CAA. L.J. was partially supported by the DFG contract STU 615/1-1, and M.U. is partially supported by the STFC grant ST/L000385/1 and her research is funded by a Royal Society Dorothy Hodgkin Research Fellowship

Iteratively reweighted compressive sensing based algorithm for spectrum cartography in cognitive radio networks

© 2014 IEEE. Spectrum cartography is the process of constructing a map showing Radio Frequency signal strength over a finite geographical area. In our previous work we formulated spectrum cartography as a compressive sensing problem and we illustrated how cartography can be used in the context of discovering spectrum holes in space that can be exploited locally in cognitive radio networks. This paper investigates the performance of compressive sensing based approach to cartography in a fading environment where realtime channel estimation is not feasible. To accommodate for lack of channel information we take an iterative approach. We extend the well-known iteratively reweighted ℓ1 minimisation approach by exploiting spatial correlation between two points in space. We evaluate the performance in an urban environment where Rayleigh fading is prominent. Our numerical results show a significant improvement in the probability of accurately making a spectrum sensing decision, in comparison to the well-known weighted approach and the traditional compressive sensing based method

On the Usage of Geolocation-Aware Spectrum Measurements for Incumbent Location and Transmit Power Detection

© 2017 IEEE. Determining the geographical area that needs to be excluded due to incumbent activity is critical to realize high spectral utilization in spectrum sharing networks. This can be achieved by estimating the incumbent location and transmit power. However, keeping the hardware complexity of sensing nodes to a minimum and scalability are critical for spectrum sharing applications with commercial intent. We present a discrete-space l1-norm minimization solution based on geolocation-aware energy detection measurements. In practice, the accuracy of geolocation tagging is limited. We capture the impact as a basis mismatch and derive the necessary condition that needs to be satisfied for successful detection of multiple incumbents' location and transmit power. We find the upper bound for the probability of eliminating the impact of limited geolocation tagging accuracy in a lognormal shadow fading environment, which is applicable to all generic I1-norm minimization techniques. We propose an algorithm based on orthogonal matching pursuit that decreases the residual in each iteration by allowing a selected set of basis vectors to rotate in a controlled manner. Numerical evaluation of the proposed algorithm in a Licensed Shared Access (LSA) network shows a significant improvement in the probability of missed detection and false alarm

Running Scaling Dimensions in Holographic Renormalization Group Flows

Holographic renormalization group flows can be interpreted in terms of effective field theory. Based on such an interpretation, a formula for the running scaling dimensions of gauge-invariant operators along such flows is proposed. The formula is checked for some simple examples from the AdS/CFT correspondence, but can be applied also in non-AdS/non-CFT cases.Comment: 14 pages, 2 figure

The Impact on Full Duplex D2D Communication of Different LTE Transmission Techniques

© 2017 IEEE. To augment capacity of spectrum limited cellular systems, 3GPP proposed Licensed Assisted Access (LAA-LTE) while efforts are underway to standardize the standalone MulteFire (a small cell standalone version of LTE). LAA is expected to boost capacity of LTE via unlicensed spectrum (5GHz). On the other hand, recent advances in Self Interference Suppression (SIS) techniques allow radios to transmit and receive simultaneously on the same channel (i.e., in-band Full-Duplex, FD). As part of future wireless networks, Device-to-device (D2D) communications would find its great potential through this FD capability. However, due to high induced aggregate interference from FD and its impact on medium access probability, the rigorous and critical analysis is needed to find an optimum trade-off between performance efficiency and overheads. Using stochastic geometry and the random graph theory, in this article, we analyze the impact of different LTE network paradigms with HD/FD D2D devices. Moreover, the impact of state- of-the-art coexistence techniques (discontinuous transmission and listen-before-talk) recommended for LTE in unlicensed spectrum over HD/FD D2D network is also discussed. The analysis is supported with extensive simulation results that reveal insights of the coexistence mechanism efficiency employed by LTE, the impact of SIS and the cost of FD operation in D2D

An efficient backoff algorithm based on the theory of confidence interval estimation

Copyright © 2016 The Institute of Electronics, Information and Communication Engineers. Channel state estimation-based backoff algorithms for channel access are being widely studied to solve wireless channel accessing and sharing problem especially in super dense wireless networks. In such algorithms, the precision of the channel state estimation determines the performance. How to make the estimation accurate in an efficient way to meet the system requirements is essential in designing the new channel access algorithms. In this paper, we first study the distribution and properties of inaccurate estimations using a novel biased estimation analysis model. We then propose an efficient backoff algorithm based on the theory of confidence interval estimation (BA-CIE), in which the minimum sample size is deduced to improve the contention window tuning efficiency, while a fault-tolerance interval structure is applied to reduce the inaccurate estimations so as to improve the contention window tuning accuracy. Our simulation results show that the throughput of our proposed BA-CIE algorithm can achieve 99% the theoretical maximum throughput of IEEE 802.11 networks, thanks to the improved contention window tuning performance