The goals of cognitive science

In this paper cognitive science is defined as the study of intelligence as a computational process. The several disciplines which contribute to the study of cognitive science are briefly described so as to glean a birds-eye view of the subject of cognitive science.

A trust model for routing in MANETs: a cognitive agents based approach

Mobile ad hoc networks (MANETs) is one of the successful wireless network paradigms which offers unrestricted mobility without depending on any underlying infrastructure. MANETs have become an exciting and im- portant technology in recent years because of the rapid proliferation of variety of wireless devices, and increased use of ad hoc networks in various applications. Like any other networks, MANETs are also prone to variety of attacks majorly in routing side, most of the proposed secured routing solutions based on cryptography and authentication methods have greater overhead, which results in latency problems and resource crunch problems, especially in energy side. The successful working of these mechanisms also depends on secured key management involving a trusted third authority, which is generally difficult to implement in MANET environ-ment due to volatile topology. Designing a secured routing algorithm for MANETs which incorporates the notion of trust without maintaining any trusted third entity is an interesting research problem in recent years. This paper propose a new trust model based on cognitive reasoning,which associates the notion of trust with all the member nodes of MANETs using a novel Behaviors-Observations- Beliefs(BOB) model. These trust values are used for detec- tion and prevention of malicious and dishonest nodes while routing the data. The proposed trust model works with the DTM-DSR protocol, which involves computation of direct trust between any two nodes using cognitive knowledge. We have taken care of trust fading over time, rewards, and penalties while computing the trustworthiness of a node and also route. A simulator is developed for testing the proposed algorithm, the results of experiments shows incorporation of cognitive reasoning for computation of trust in routing effectively detects intrusions in MANET environment, and generates more reliable routes for secured routing of data.

Precoder optimization in cognitive radio with interference constraints

We consider precoding strategies at the secondary base station (SBS) in a cognitive radio network with interference constraints at the primary users (PUs). Precoding strategies at the SBS which satisfy interference constraints at the PUs in cognitive radio networks have not been adequately addressed in the literature so far. In this paper, we consider two scenarios: i) when the primary base station (PBS) data is not available at SBS, and ii) when the PBS data is made available at the SBS. We derive the optimum MMSE and Tomlinson-Harashima precoding (THP) matrix Alters at the SBS which satisfy the interference constraints at the PUs for the former case. For the latter case, we propose a precoding scheme at the SBS which performs pre-cancellation of the PBS data, followed by THP on the pre-cancelled data. The optimum precoding matrix filters are computed through an iterative search. To illustrate the robustness of the proposed approach against imperfect CSI at the SBS, we then derive robust precoding filters under imperfect CSI for the latter case. Simulation results show that the proposed optimum precoders achieve good bit error performance at the secondary users while meeting the interference constraints at the PUs.

A novel algorithm for cooperative distributed sequential spectrum sensing in Cognitive Radio

This paper considers cooperative spectrum sensing in Cognitive Radios. In our previous work we have developed DualSPRT, a distributed algorithm for cooperative spectrum sensing using Sequential Probability Ratio Test (SPRT) at the Cognitive Radios as well as at the fusion center. This algorithm works well, but is not optimal. In this paper we propose an improved algorithm- SPRT-CSPRT, which is motivated from Cumulative Sum Procedures (CUSUM). We analyse it theoretically. We also modify this algorithm to handle uncertainties in SNR's and fading.

Performance analysis of data and voice connections in a cognitive radio network

We study the performance of cognitive (secondary) users in a cognitive radio network which uses a channel whenever the primary users are not using the channel. The usage of the channel by the primary users is modelled by an ON-OFF renewal process. The cognitive users may be transmitting data using TCP connections and voice traffic. The voice traffic is given priority over the data traffic. We theoretically compute the mean delay of TCP and voice packets and also the mean throughput of the different TCP connections. We compare the theoretical results with simulations.

Antenna Selection in Interference-Constrained Underlay Cognitive Radios: SEP-Optimal Rule and Performance Benchmarking

In the underlay mode of cognitive radio, secondary users are allowed to transmit when the primary is transmitting, but under tight interference constraints that protect the primary. However, these constraints limit the secondary system performance. Antenna selection (AS)-based multiple antenna techniques, which exploit spatial diversity with less hardware, help improve secondary system performance. We develop a novel and optimal transmit AS rule that minimizes the symbol error probability (SEP) of an average interference-constrained multiple-input-single-output secondary system that operates in the underlay mode. We show that the optimal rule is a non-linear function of the power gain of the channel from the secondary transmit antenna to the primary receiver and from the secondary transmit antenna to the secondary receive antenna. We also propose a simpler, tractable variant of the optimal rule that performs as well as the optimal rule. We then analyze its SEP with L transmit antennas, and extensively benchmark it with several heuristic selection rules proposed in the literature. We also enhance these rules in order to provide a fair comparison, and derive new expressions for their SEPs. The results bring out new inter-relationships between the various rules, and show that the optimal rule can significantly reduce the SEP.

Interplay of structural distortions, dielectric effects and magnetic order in multiferroic GdMnO3

Multiferroic materials are characterized by simultaneous magnetic and ferroelectric ordering making them good candidates for magneto-electrical applications. We conducted thermal expansion and magnetostriction measurements in magnetic fields up to 14 T on perovskitic GdMnO3 by highresolution capacitive dilatometry in an effort to determine all longitudinal and transversal components of the magnetostriction tensor. Below the ordering temperature T (N) = 42 K, i.e., within the different complex (incommensurate or complex) antiferromagnetic phases, lattice distortions of up to 100 ppm have been found. Although no change of the lattice symmetry occurs, the measurements reveal strong magneto-structural phenomena, especially in the incommensurate sinusoidal antiferromagnetic phase. A strong anisotropy of the magnetoelastic properties was found, in good agreement with the type and propagation vector of the magnetic structure. We demonstrate that our capacitive dilatometry can detect lattice expansion effects and changes of the dielectric permittivity simultaneously because the sample is housed inside the capacitor. A separation of both effects is possible by shielding the sample. Dielectric transitions could be detected by this method and compared to the critical values of H and T in the magnetic phase diagram. Dielectric changes measured at 1 kHz excitation frequency are detected in GdMnO3 at about 180 K, and between 10 K and 25 K in the canted antiferromagnetic structure which is characterized by a complex magnetic order on both the Gd- and Mn-sites.

Cognitive radio implementation for a frequency hopping primary signal

Frequency hopping communications, used in the military present significant opportunities for spectrum reuse via the cognitive radio technology. We propose a MAC which incorporates hop instant identification, and supports network discovery and formation, QOS Scheduling and secondary communications. The spectrum sensing algorithm is optimized to deal with the problem of spectral leakage. The algorithms are implemented in a SDR platform based test bed and measurement results are presented.

Subject independent human action recognition using spatio-depth information and meta-cognitive RBF network

In this paper, we present a machine learning approach for subject independent human action recognition using depth camera, emphasizing the importance of depth in recognition of actions. The proposed approach uses the flow information of all 3 dimensions to classify an action. In our approach, we have obtained the 2-D optical flow and used it along with the depth image to obtain the depth flow (Z motion vectors). The obtained flow captures the dynamics of the actions in space time. Feature vectors are obtained by averaging the 3-D motion over a grid laid over the silhouette in a hierarchical fashion. These hierarchical fine to coarse windows capture the motion dynamics of the object at various scales. The extracted features are used to train a Meta-cognitive Radial Basis Function Network (McRBFN) that uses a Projection Based Learning (PBL) algorithm, referred to as PBL-McRBFN, henceforth. PBL-McRBFN begins with zero hidden neurons and builds the network based on the best human learning strategy, namely, self-regulated learning in a meta-cognitive environment. When a sample is used for learning, PBLMcRBFN uses the sample overlapping conditions, and a projection based learning algorithm to estimate the parameters of the network. The performance of PBL-McRBFN is compared to that of a Support Vector Machine (SVM) and Extreme Learning Machine (ELM) classifiers with representation of every person and action in the training and testing datasets. Performance study shows that PBL-McRBFN outperforms these classifiers in recognizing actions in 3-D. Further, a subject-independent study is conducted by leave-one-subject-out strategy and its generalization performance is tested. It is observed from the subject-independent study that McRBFN is capable of generalizing actions accurately. The performance of the proposed approach is benchmarked with Video Analytics Lab (VAL) dataset and Berkeley Multimodal Human Action Database (MHAD). (C) 2013 Elsevier Ltd. All rights reserved.

SEP-optimal antenna selection for average interference constrained underlay cognitive radios

In the underlay mode of cognitive radio, secondary users can transmit when the primary is transmitting, but under tight interference constraints, which limit the secondary system performance. Antenna selection (AS)-based multiple antenna techniques, which require less hardware and yet exploit spatial diversity, help improve the secondary system performance. In this paper, we develop the optimal transmit AS rule that minimizes the symbol error probability (SEP) of an average interference-constrained secondary system that operates in the underlay mode. We show that the optimal rule is a non-linear function of the power gains of the channels from secondary transmit antenna to primary receiver and secondary transmit antenna to secondary receive antenna. The optimal rule is different from the several ad hoc rules that have been proposed in the literature. We also propose a closed-form, tractable variant of the optimal rule and analyze its SEP. Several results are presented to compare the performance of the closed-form rule with the ad hoc rules, and interesting inter-relationships among them are brought out.

Optimal Joint Antenna Selection and Power Adaptation in Underlay Cognitive Radios

Transmit antenna selection (AS) is a popular, low hardware complexity technique that improves the performance of an underlay cognitive radio system, in which a secondary transmitter can transmit when the primary is on but under tight constraints on the interference it causes to the primary. The underlay interference constraint fundamentally changes the criterion used to select the antenna because the channel gains to the secondary and primary receivers must be both taken into account. We develop a novel and optimal joint AS and transmit power adaptation policy that minimizes a Chernoff upper bound on the symbol error probability (SEP) at the secondary receiver subject to an average transmit power constraint and an average primary interference constraint. Explicit expressions for the optimal antenna and power are provided in terms of the channel gains to the primary and secondary receivers. The SEP of the optimal policy is at least an order of magnitude lower than that achieved by several ad hoc selection rules proposed in the literature and even the optimal antenna selection rule for the case where the transmit power is either zero or a fixed value.

SEP-Optimal Transmit Power Policy for Peak Power and Interference Outage Probability Constrained Underlay Cognitive Radios

In underlay cognitive radio (CR), a secondary user (SU) can transmit concurrently with a primary user (PU) provided that it does not cause excessive interference at the primary receiver (PRx). The interference constraint fundamentally changes how the SU transmits, and makes link adaptation in underlay CR systems different from that in conventional wireless systems. In this paper, we develop a novel, symbol error probability (SEP)-optimal transmit power adaptation policy for an underlay CR system that is subject to two practically motivated constraints, namely, a peak transmit power constraint and an interference outage probability constraint. For the optimal policy, we derive its SEP and a tight upper bound for MPSK and MQAM constellations when the links from the secondary transmitter (STx) to its receiver and to the PRx follow the versatile Nakagami-m fading model. We also characterize the impact of imperfectly estimating the STx-PRx link on the SEP and the interference. Extensive simulation results are presented to validate the analysis and evaluate the impact of the constraints, fading parameters, and imperfect estimates.