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.

Providing QoS in a cognitive radio network

We consider the problem of wireless channel allocation (whenever the channels are free) to multiple cognitive radio users in a Cognitive Radio Network (CRN) so as to satisfy their Quality of Service (QoS) requirements efficiently. The CRN base station may not know the channel states of all the users. The multiple channels are available at random times. In this setup Opportunistic Splitting can be an attractive solution. A disadvantage of this algorithm is that it requires the metrics of all users to be an independent, identically distributed sequence. However we use a recently generalized version of this algorithm in which the optimal parameters are learnt on-line through stochastic approximation and metrics can be Markov. We provide scheduling algorithms which maximize weighted-sum system throughput or are throughput or delay optimal. We also consider the scenario when some traffic streams are delay sensitive.

Modeling Time-Varying Aggregate Interference in Cognitive Radio Systems, and Application to Primary Exclusive Zone Design

Accurately characterizing the time-varying interference caused to the primary users is essential in ensuring a successful deployment of cognitive radios (CR). We show that the aggregate interference at the primary receiver (PU-Rx) from multiple, randomly located cognitive users (CUs) is well modeled as a shifted lognormal random process, which is more accurate than the lognormal and the Gaussian process models considered in the literature, even for a relatively dense deployment of CUs. It also compares favorably with the asymptotically exact stable and symmetric truncated stable distribution models, except at high CU densities. Our model accounts for the effect of imperfect spectrum sensing, which depends on path-loss, shadowing, and small-scale fading of the link from the primary transmitter to the CU; the interweave and underlay modes or CR operation, which determine the transmit powers of the CUs; and time-correlated shadowing and fading of the links from the CUs to the PU-Rx. It leads to expressions for the probability distribution function, level crossing rate, and average exceedance duration. The impact of cooperative spectrum sensing is also characterized. We validate the model by applying it to redesign the primary exclusive zone to account for the time-varying nature of interference.

Antenna Selection with Power Adaptation in Interference-Constrained Cognitive Radios

The performance of an underlay cognitive radio (CR) system, which can transmit when the primary is on, is curtailed by tight constraints on the interference it can cause to the primary receiver. Transmit antenna selection (AS) improves the performance of underlay CR by exploiting spatial diversity but with less hardware. However, the selected antenna and its transmit power now both depend on the channel gains to the secondary and primary receivers. We develop a novel Chernoffbound based optimal AS and power adaptation (CBBOASPA) policy that minimizes an upper bound on the symbol error probability (SEP) at the secondary receiver, subject to constraints on the average transmit power and the average interference to the primary. The optimal antenna and its power are presented in an insightful closed form in terms of the channel gains. We then analyze the SEP of CBBOASPA. Extensive benchmarking shows that the SEP of CBBOASPA for both MPSK and MQAM is one to two orders of magnitude lower than several ad hoc AS policies and even optimal AS with on-off power control.

Multimodal therapy for complete regression of malignant melanoma using constrained nonlinear optimal dynamic inversion

Using a realistic nonlinear mathematical model for melanoma dynamics and the technique of optimal dynamic inversion (exact feedback linearization with static optimization), a multimodal automatic drug dosage strategy is proposed in this paper for complete regression of melanoma cancer in humans. The proposed strategy computes different drug dosages and gives a nonlinear state feedback solution for driving the number of cancer cells to zero. However, it is observed that when tumor is regressed to certain value, then there is no need of external drug dosages as immune system and other therapeutic states are able to regress tumor at a sufficiently fast rate which is more than exponential rate. As model has three different drug dosages, after applying dynamic inversion philosophy, drug dosages can be selected in optimized manner without crossing their toxicity limits. The combination of drug dosages is decided by appropriately selecting the control design parameter values based on physical constraints. The process is automated for all possible combinations of the chemotherapy and immunotherapy drug dosages with preferential emphasis of having maximum possible variety of drug inputs at any given point of time. Simulation study with a standard patient model shows that tumor cells are regressed from 2 x 107 to order of 105 cells because of external drug dosages in 36.93 days. After this no external drug dosages are required as immune system and other therapeutic states are able to regress tumor at greater than exponential rate and hence, tumor goes to zero (less than 0.01) in 48.77 days and healthy immune system of the patient is restored. Study with different chemotherapy drug resistance value is also carried out. (C) 2014 Elsevier Ltd. All rights reserved.

Interference-Constrained Optimal Power-Adaptive Amplify-and-Forward Relaying and Selection for Underlay Cognitive Radios

In an underlay cognitive radio (CR) system, a secondary user can transmit when the primary is transmitting but is subject to tight constraints on the interference it causes to the primary receiver. Amplify-and-forward (AF) relaying is an effective technique that significantly improves the performance of a CR by providing an alternate path for the secondary transmitter's signal to reach the secondary receiver. We present and analyze a novel optimal relay gain adaptation policy (ORGAP) in which the relay is interference aware and optimally adapts both its gain and transmit power as a function of its local channel gains. ORGAP minimizes the symbol error probability at the secondary receiver subject to constraints on the average relay transmit power and on the average interference caused to the primary. It is different from ad hoc AF relaying policies and serves as a new and fundamental theoretical benchmark for relaying in an underlay CR. We also develop a near-optimal and simpler relay gain adaptation policy that is easy to implement. An extension to a multirelay scenario with selection is also developed. Our extensive numerical results for single and multiple relay systems quantify the power savings achieved over several ad hoc policies for both MPSK and MQAM constellations.

Group Testing-Based Spectrum Hole Search for Cognitive Radios

This paper investigates the use of adaptive group testing to find a spectrum hole of a specified bandwidth in a given wideband of interest. We propose a group testing-based spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy by testing a group of adjacent subbands in a single test. This is enabled by a simple and easily implementable sub-Nyquist sampling scheme for signal acquisition by the cognitive radios (CRs). The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent subbands. Energy-based hypothesis tests are used to provide an occupancy decision over the group of subbands, and this forms the basis of the proposed algorithm to find contiguous spectrum holes of a specified bandwidth. We extend this framework to a multistage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including noncontiguous spectrum hole search. Furthermore, we provide the analytical means to optimize the group tests with respect to the detection thresholds, number of samples, group size, and number of stages to minimize the detection delay under a given error probability constraint. Our analysis allows one to identify the sparsity and SNR regimes where group testing can lead to significantly lower detection delays compared with a conventional bin-by-bin energy detection scheme; the latter is, in fact, a special case of the group test when the group size is set to 1 bin. We validate our analytical results via Monte Carlo simulations.

Combined inhalation and oral supplementation of Vitamin A and Vitamin D: A possible prevention and therapy for tuberculosis

Tuberculosis is continuing as a problem of mankind. With evolution, MDR and XDR forms of tuberculosis have emerged from drug sensitive strain. MDR and XDR strains are resistant to most of the antibiotics, making the management more difficult. BCG vaccine is not providing complete protection against tuberculosis. Therefore new infections are spreading at a tremendous rate. At the present moment there is experimental evidence to believe that Vitamin A and Vitamin D has anti-mycobacterial property. It is in this context, we have hypothesized a host based approach using the above vitamins that can cause possible prevention and cure of tuberculosis with minimal chance of resistance or toxicity. (C) 2015 Elsevier Ltd. All rights reserved.

A novel Monoclonal Antibody against Notch1 Targets Leukemia-associated Mutant Notch1 and Depletes Therapy Resistant Cancer Stem Cells in Solid Tumors

Higher Notch signaling is known to be associated with hematological and solid cancers. We developed a potential immunotherapeutic monoclonal antibody (MAb) specific for the Negative Regulatory Region of Notch1 (NRR). The MAb604.107 exhibited higher affinity for the ``Gain-offunction'' mutants of Notch1 NRR associated with T Acute lymphoblastic Leukemia (T-ALL). Modeling of the mutant NRR with 12 amino-acid insertion demonstrated ``opening'' resulting in exposure of the S2-cleavage site leading to activated Notch1 signaling. The MAb, at low concentrations (1-2 mu g/ml), inhibited elevated ligand-independent Notch1 signaling of NRR mutants, augmented effect of Thapsigargin, an inhibitor of mutant Notch1, but had no effect on the wild-type Notch1. The antibody decreased proliferation of the primary T-ALL cells and depleted leukemia initiating CD34/CD44 high population. At relatively high concentrations, (10-20 mu g/ml), the MAb affected Notch1 signaling in the breast and colon cancer cell lines. The Notch-high cells sorted from solid-tumor cell lines exhibited characteristics of cancer stem cells, which were inhibited by the MAb. The antibody also increased the sensitivity to Doxorubucinirubicin. Further, the MAb impeded the growth of xenografts from breast and colon cancer cells potentiated regression of the tumors along with Doxorubucin. Thus, this antibody is potential immunotherapeutic tool for different cancers.

Soft Real Time Implementation of a Cognitive Radio Testbed for Frequency Hopping Primary Satisfying QoS Requirements

The Cognitive Radio (CR) is a promising technology which provides a novel way to subjugate the issue of spectrum underutilization caused due to the fixed spectrum assignment policies. In this paper we report the design and implementation of a soft-real time CR MAC, consisting of multiple secondary users, in a frequency hopping (Fit) primary scenario. This MAC is capable of sensing the spectrum and dynamically allocating the available frequency bands to multiple CR users based on their QoS requirements. As the primary is continuously hopping, a method has also been implemented to detect the hop instant of the primary network. Synchronization usually requires real time support, however we have been able to achieve this with a soft-real time technique which enables a fully software implementation of CR MAC layer. We demonstrate the wireless transmission and reception of video over this CR testbed through opportunistic spectrum access. The experiments carried out use an open source software defined radio package called GNU Radio and a basic radio hardware component USRP.