Information Centric Modeling for Two-tier Cache Enabled Cellular Networks

In this article, we introduce a new metric called `information centric coverage probability' to characterize the performance of a two-tier cache enabled cellular network. The proposed metric unifies the dynamics of in-network caching and heterogeneous networking to provide a unified performance measure. Specifically, it quantifies the probability that a mobile user (MU) is covered at a desired rate when a certain content is requested from a global content library. In other words, it quantifies the percentage of time when an MU can be served locally without paying the traffic penalties at backhaul, fronthaul and core networks. Caching dynamics are modeled by considering that the content which is least recently used (LRU) is evicted while the requested content is stored in the cache. The considered two-tier cellular model leverages coordination between the macro base-station (MBS) and the small cell base-stations (SBSs) to maximize the resource efficiency. More specifically, coordination between macro and small cells enables an arbitrary SBS to exploit the caches at other SBSs in the neighborhood. Thus reducing the requirement for huge and expensive memory modules at individual SBSs. The spatial dynamics of cellular network are modeled by borrowing well established tools from stochastic geometry. Propagation uncertainties are explicitly factored in characterization by considering the small scale Rayleigh fading and the large scale power-law path-loss model. It is shown that the information centric coverage probability is a function of (i) the size of caches at the SBSs and the MBS; (ii) the content eviction strategy; (iii) the underlying popularity law for referenced objects; (iv) the size of the global content library; (v) desired downlink transmission rate; (vi) the amount of spectrum allocated to each tier; (vii) pathloss exponent; and (viii) the deployment density of the SBSs and the MBSs. Our analysis reveals that significant performance gains can be harnessed with appropriate dimensioning of both cache sizes and deployment density. Finally, identification of memory limited vs. QoS limited operational regime for two-tier cellular networks is considered

Cloud Empowered Cognitive Inter-cell Interference Coordination for Small Cellular Networks

In this article, we present a Cloud empowered Cognitive Inter-Cell Interference Coordination (C2-ICIC) scheme for small cellular networks. The scheme leverages a recently proposed cloud radio access network (C-RAN) architecture for enabling intra-tier coordination and relaxes the need for inter-tier coordination by adopting the phantom cell architecture. Employing tools from stochastic geometry, we characterize the downlink success probability for a Mobile User (MU) scheduled under the proposed coordination scheme. It is shown that, compared to un-coordinated scheduling, significant performance gains can be realized in ultra dense small cell deployment scenarios under the proposed C2-ICIC scheme. This is attributed to the robust interference protection provisioned by the scheme. It is demonstrated that the gains are particularly large for the users experiencing a weak received signal strength. Indeed, for these users, the received signal-to-interference ratio (SIR) can only be improved by reducing the experienced aggregate co-channel interference. The closed-form expression derived for the downlink success probability is employed to quantify the link level throughput under the proposed scheme. Finally, we briefly explore the design space of the C2-ICIC scheme in terms of interference protection cap which determines both the downlink throughput of the MU scheduled in the coordination mode and the transmission opportunity for the co-channel small cells

Sparse Reconstruction of Time-Frequency Representation using the Fractional Fourier Transform

This paper describes a novel method to approximate instantaneous frequency of non-stationary signals through an application of fractional Fourier transform (FRFT). FRFT enables us to build a compact and accurate chirp dictionary for each windowed signal, thus the proposed approach offers improved computational efficiency, and good performance when compared with chirp atom method

On the Analysis of Device-to-Device Overlaid Cellular Networks in the Uplink under 3GPP Propagation Model

In this article we employ the third generation partnership project (3GPP) recommended path loss models for the analysis of cellular networks overlaid with D2D communication and channel inversion power control in the uplink. We characterize the coverage and average network throughput with the help of stochastic geometry. More specifically, we develop tractable expressions for the coverage in cellular and D2D modes. Our theoretical results differ significantly from previous work, which uses simple power law path loss models. The traditional methodology does not account for the presence of line-of-sight (LoS), non-line-of-sight (NLoS) and free space (FS) links. We demonstrate that such classification of links significantly impacts the inference which can be derived from the analysis for the design of overlaid D2D networks. In particular, we show that, contrary to the previous findings, the average throughput of the network does not saturate with the increase in the density of base stations (BS), but there exists an optimal mode selection threshold and BS density which maximizes the average throughput

Nanopositioning of a diamond nanocrystal containing a single NV defect center

Precise control over the position of a single quantum object is important for many experiments in quantum science and nanotechnology. We report on a technique for high-accuracy positioning of individual diamond nanocrystals. The positioning is done with a home-built nanomanipulator under real-time scanning electron imaging, yielding an accuracy of a few nanometers. This technique is applied to pick up, move and position a single NV defect center contained in a diamond nanocrystal. We verify that the unique optical and spin properties of the NV center are conserved by the positioning process.Comment: 3 pages, 3 figures; high-resolution version available at http://www.ns.tudelft.nl/q

Energy Harvesting Empowered Cognitive Metro-cellular Networks

Harvesting energy from natural (solar, wind, vibration etc.) and synthesized (microwave power transfer) sources is envisioned as a key enabler for realizing green wireless networks. Energy efficient scheduling is one of the prime objectives of cognitive radio platforms. To that end, in this article, we present a comprehensive analytical framework to characterize the performance of a cognitive metro-cellular network empowered by solar energy harvesting. The proposed model considers both spatial and temporal dynamics of the energy field and the mobile user traffic. Channel uncertainties are also captured in terms of large scale path-loss and small-scale Rayleigh fading. A new metric called `energy outage probability' which characterizes the self-sustainable operation of the base stations under energy harvesting is proposed and quantified. It is shown that the energy outage probability is strongly coupled with the path-loss exponent, required quality-of-service, base station and user density. Moreover, the energy outage probability varies both on daily and yearly basis depending on the solar geometry. It is shown that even in winter time BSs can run for 10-15 hours without any purchase of energy from the power grid

Deterministic nano-assembly of a coupled quantum emitter - photonic crystal cavity system

The interaction of a single quantum emitter with its environment is a central theme in quantum optics. When placed in highly confined optical fields, such as those created in optical cavities or plasmonic structures, the optical properties of the emitter can change drastically. In particular, photonic crystal (PC) cavities show high quality factors combined with an extremely small mode volume. Efficiently coupling a single quantum emitter to a PC cavity is challenging because of the required positioning accuracy. Here, we demonstrate deterministic coupling of single Nitrogen-Vacancy (NV) centers to high-quality gallium phosphide PC cavities, by deterministically positioning their 50 nm-sized host nanocrystals into the cavity mode maximum with few-nanometer accuracy. The coupling results in a 25-fold enhancement of NV center emission at the cavity wavelength. With this technique, the NV center photoluminescence spectrum can be reshaped allowing for efficient generation of coherent photons, providing new opportunities for quantum science.Comment: 13 pages, 4 figure

Breaking the Area Spectral Efficiency Wall in Cognitive Underlay Networks

In this article, we develop a comprehensive analytical framework to characterize the area spectral efficiency of a large scale Poisson cognitive underlay network. The developed framework explicitly accommodates channel, topological and medium access uncertainties. The main objective of this study is to launch a preliminary investigation into the design considerations of underlay cognitive networks. To this end, we highlight two available degrees of freedom, i.e., shaping medium access or transmit power. While from the primary user's perspective tuning either to control the interference is equivalent, the picture is different for the secondary network. We show the existence of an area spectral efficiency wall under both adaptation schemes. We also demonstrate that the adaptation of just one of these degrees of freedom does not lead to the optimal performance. But significant performance gains can be harnessed by jointly tuning both the medium access probability and the transmission power of the secondary networks. We explore several design parameters for both adaptation schemes. Finally, we extend our quest to more complex point-to-point and broadcast networks to demonstrate the superior performance of joint tuning policies

M2M meets D2D: Harnessing D2D Interfaces for the Aggregation of M2M Data

Direct device-to-device (D2D) communication presents as an effective technique to reduce the load at the base station (BS) while ensuring reliable localized communication. In this paper, we propose a large-scale M2M data Aggregation and Trunking (MAT) scheme, whereby the user equipments (UEs) aggregate M2M data from the nearby MTDs and trunk this data along with their own data to the BS in the cellular uplink. We develop a comprehensive stochastic geometry framework by considering a Poisson hard sphere model for UE coverage. The main motivation of this model is to capture the fact that a UE can gather data from short range, low-power MTDs located only in its close proximity while ensuring that an MTD is associated to at most one UE. We explore the inherent trade-off between the time reserved for aggregation and successful trunking of data to the BS and compare our results with the baseline case where no aggregation mechanism is used. We show that while the baseline case of connecting a bulk of MTDs directly with the BS is prohibitive, MAT scheme can efficiently gather data from selected MTDs in a distributed manner

Robotic Mobility Diversity Algorithm with Continuous Search Space

Small scale fading makes the wireless channel gain vary significantly over small distances and in the context of classical communication systems it can be detrimental to performance. But in the context of mobile robot (MR) wireless communications, we can take advantage of the fading using a mobility diversity algorithm (MDA) to deliberately locate the MR at a point where the channel gain is high. There are two classes of MDAs. In the first class, the MR explores various points, stops at each one to collect channel measurements and then locates the best position to establish communications. In the second class the MR moves, without stopping, along a continuous path while collecting channel measurements and then stops at the end of the path. It determines the best point to establish communications. Until now, the shape of the continuous path for such MDAs has been arbitrarily selected and currently there is no method to optimize it. In this paper, we propose a method to optimize such a path. Simulation results show that such optimized paths provide the MDAs with an increased performance, enabling them to experience higher channel gains while using less mechanical energy for the MR motion