The E3 architecture: enabling future cellular networks with cognitive and self‐x capabilities

Future mobile networks are expected to be complex heterogeneous systems. On the one hand this will enable users to take advantage of a number of different access technologies. On the other hand it will seriously affect network management procedures since more extensive operations and decisions will have to be dealt with. To tackle these challenges a number of new dynamic mechanisms need to be designed. It is imperative that certain network management tasks have to be performed without human intervention to reduce the OPEX costs and achieve faster responses in different events. To achieve this goal, the introduction of self‐x functionalities, combined with cognitive mechanisms and the ability to reconfigure network entities and terminals, is required. Moreover, the introduction of a new pilot channel needs to be considered to assist the terminals in selecting the most suitable radio access technology according to their requirements. We present the functional architecture of an evolved network that was designed in the context of the EU‐funded IP project ‘E³: End‐to‐End Efficiency’. This architecture aims to enhance existing procedures usually performed in traditional operation and maintenance systems (e.g. spectrum management, network planning, configuration actions). We explain the rationale of our design and provide specific examples to illustrate the role of the different functional entities and their interfaces. A considerable part of this architecture has recently been approved as a feasibility study by the ETSI Committee Reconfigurable Radio System. Copyright © 2010 John Wiley & Sons, Ltd.     

A data mining approach to classify serum creatinine values in patients undergoing continuous ambulatory peritoneal dialysis

Wireless Networks - Continuous ambulatory peritoneal dialysis (CAPD) is a treatment used by patients in the end-stage of chronic kidney diseases. Those patients need to be monitored using blood...     

Deformation-based mapping of volume change from serial brain MRI in the presence of local tissue contrast change

This paper is motivated by the analysis of serial structural magnetic resonance imaging (MRI) data of the brain to map patterns of local tissue volume loss or gain over time, using registration-based deformation tensor morphometry. Specifically, we address the important confound of local tissue contrast changes which can be induced by neurodegenerative or neurodevelopmental processes. These not only modify apparent tissue volume, but also modify tissue integrity and its resulting MRI contrast parameters. In order to address this confound we derive an approach to the voxel-wise optimization of regional mutual information (RMI) and use this to drive a viscous fluid deformation model between images in a symmetric registration process. A quantitative evaluation of the method when compared to earlier approaches is included using both synthetic data and clinical imaging data. Results show a significant reduction in errors when tissue contrast changes locally between acquisitions. Finally, examples of applying the technique to map different patterns of atrophy rate in different neurodegenerative conditions is included.     

Efficient disparity vector prediction schemes with modified P frame for 2D camera arrays

An efficient disparity estimation algorithm for multi-view video sequences, recorded by a two-dimensional camera array in which the cameras are spaced equidistantly, is presented. Because of the strong geometrical relationship among views, the disparity vectors of a certain view can for most blocks be derived from the disparity vectors of other views. A frame constructed using that idea is called a D frame in this work. Three new prediction schemes which contain D frames are proposed for encoding 5 × 3 multi-view video sequences. The schemes are applied to several multi-view image sequences taken from a camera-array and they are compared in terms of quality, bit-rate and complexity. The experimental results show that the proposed prediction schemes significantly decrease the complexity of the encoder at a very low cost of quality and/or bit-rate.     

Background memory area estimation for multidimensional signalprocessing systems

Memory cost is responsible for a large amount of the chip and/or board area of customized video and image processing system realizations. In this paper, we present a novel technique-founded on data-flow analysis which allows one to address the problem of background memory size evaluation for a given nonprocedural algorithm specification, operating on multidimensional signals with affine indexes. Most of the target applications are characterized by a huge number of signals, so a new polyhedral data-flow model operating on groups of scalar signals is proposed. These groups are obtained by a novel analytical partitioning technique, allowing to select a desired granularity, depending on the application complexity. The method incorporates a way to tradeoff memory size with computational and controller complexity     

Kirigami/Origami‐Based Soft Deployable Reflector for Optical Beam Steering

The beam steering mechanism has been a key element for various applications ranging from sensing and imaging to solar tracking systems. However, conventional beam steering systems are bulky and complex and present significant challenges for scaling up. This work introduces the use of soft deployable reflectors combining a soft deployable structure with simple kirigami/origami reflective films. This structure can be used as a macroscale beam steering mechanism that is both simple and compact. This work first develops a soft deployable structure that is easily scalable by patterning of soft linear actuators. This soft deployable structure is capable of increasing its height several folds by expanding in a continuous and controllable manner, which can be used as a frame to deform the linearly stretchable kirigami/origami structures integrated into the structure. Experiments on the reflective capability of the reflectors are conducted and show a good fit to the modeling results. The proposed principles for deployment and for beam steering can be used to realize novel active beam steering devices, highlighting the use of soft robotic principles to produce scalable morphing structures.     

A Low-Cost and Low-Power Messaging System Based on the LoRa Wireless Technology

Mobile Networks and Applications - In this paper we describe a low-cost and low-power consumption messaging system based on LoRa technology. More that one billion people worldwide cannot access...     

Secure Distributed Key Generation for Discrete-Log Based Cryptosystems

A Distributed Key Generation (DKG) protocol is an essential component of threshold cryptosystems required to initialize the cryptosystem securely and generate its private and public keys. In the case of discrete-log-based (dlog-based) threshold signature schemes (ElGamal and its derivatives), the DKG protocol is further used in the distributed signature generation phase to generate one-time signature randomizers (r = g^k). In this paper we show that a widely used dlog-based DKG protocol suggested by Pedersen does not guarantee a uniformly random distribution of generated keys: we describe an efficient active attacker controlling a small number of parties which successfully biases the values of the generated keys away from uniform. We then present a new DKG protocol for the setting of dlog-based cryptosystems which we prove to satisfy the security requirements from DKG protocols and, in particular, it ensures a uniform distribution of the generated keys. The new protocol can be used as a secure replacement for the many applications of Pedersen's protocol. Motivated by the fact that the new DKG protocol incurs additional communication cost relative to Pedersen's original protocol, we investigate whether the latter can be used in specific applications which require relaxed security properties from the DKG protocol. We answer this question affirmatively by showing that Pedersen's protocol suffices for the secure implementation of certain threshold cryptosystems whose security can be reduced to the hardness of the discrete logarithm problem. In particular, we show Pedersen's DKG to be sufficient for the construction of a threshold Schnorr signature scheme. Finally, we observe an interesting trade-off between security (reductions), computation, and communication that arises when comparing Pedersen's DKG protocol with ours.     

Tokens vs. Signals: On Conformance between Formal Models of Dataflow and Hardware

Designing hardware often involves several types of modeling and analysis, e.g., in order to check system correctness, to derive performance properties such as throughput, to optimize resource usages (e.g., buffer sizes), and to synthesize parts of a circuit (e.g., control logic). Working directly with low-level hardware models such as finite-state machines (FSMs) to answer such questions is often infeasible, e.g., due to state explosion. Instead, designers often use dataflow models such as SDF and CSDF, which are more abstract than FSMs, and less expensive to use since they come with more efficient analysis algorithms. However, dataflow models are only abstractions of the real hardware, and often omit critical information. This raises the question, when can one say that a certain dataflow model faithfully captures a given piece of hardware? The question is of more than simply academic interest. Indeed, as illustrated in this paper, dataflow-based analysis outcomes may sometimes be defensive (e.g., buffers that are too big) or even incorrect (e.g., buffers that are too small). To answer the question of faithfully capturing hardware using dataflow models, we develop a formal conformance relation between the heterogeneous formalisms of (1) finite-state machines with synchronous semantics, typically used to model synchronous hardware, and (2) asynchronous processes communicating via queues, used as a formal model for dataflow. The conformance relation preserves performance properties such as worst-case throughput and latency.     

Efficient computer analysis of ideal switched-capacitor circuits using matrix compaction techniques

In this paper we describe how three simple observations can be used in order to obtain an efficient algorithm for the computer analysis of ideal switched-capacitor circuits. the resulting algorithm is linear in the number of phases. the first observation uses the structure of the r-domain MNA-matrix to come up with a new LU-decomposition scheme which is gradual per timeslot. the second observation allows a great reduction in size of the z-domain MNA-matrix by a matrix compaction algorithm which also operates gradually per timeslot and which can be interleaved with the first gradual LU-decomposition process. This leads to a small matrix which can then be used for a time- and direct frequency-domain analysis. Third, the computations of transfer functions, aliasing functions and sensitivities can be optimized by applying appropriate excitations and making appropriate combinations of the terms in the expressions. These algorithms have been implemented in the SC-analysis program DIANA.SC. the usefulness and efficiency of the program is then illustrated with some examples.