From Spectrum Pooling to Space Pooling: Opportunistic Interference Alignment in MIMO Cognitive Networks

We describe a non-cooperative interference alignment (IA) technique which allows an opportunistic multiple input multiple output (MIMO) link (secondary) to harmlessly coexist with another MIMO link (primary) in the same frequency band. Assuming perfect channel knowledge at the primary receiver and transmitter, capacity is achieved by transmiting along the spatial directions (SD) associated with the singular values of its channel matrix using a water-filling power allocation (PA) scheme. Often, power limitations lead the primary transmitter to leave some of its SD unused. Here, it is shown that the opportunistic link can transmit its own data if it is possible to align the interference produced on the primary link with such unused SDs. We provide both a processing scheme to perform IA and a PA scheme which maximizes the transmission rate of the opportunistic link. The asymptotes of the achievable transmission rates of the opportunistic link are obtained in the regime of large numbers of antennas. Using this result, it is shown that depending on the signal-to-noise ratio and the number of transmit and receive antennas of the primary and opportunistic links, both systems can achieve transmission rates of the same order.Comment: Submitted to IEEE Trans. in Signal Processing. Revised on 23-11-0

On the Fictitious Play and Channel Selection Games

Considering the interaction through mutual interference of the different radio devices, the channel selection (CS) problem in decentralized parallel multiple access channels can be modeled by strategic-form games. Here, we show that the CS problem is a potential game (PG) and thus the fictitious play (FP) converges to a Nash equilibrium (NE) either in pure or mixed strategies. Using a 2-player 2-channel game, it is shown that convergence in mixed strategies might lead to cycles of action profiles which lead to individual spectral efficiencies (SE) which are worse than the SE at the worst NE in mixed and pure strategies. Finally, exploiting the fact that the CS problem is a PG and an aggregation game, we present a method to implement FP with local information and minimum feedback.Comment: In proc. of the IEEE Latin-American Conference on Communications (LATINCOM), Bogota, Colombia, September, 201

On The Duality Between State-Dependent Channels and Wiretap Channels

International audienceIn this paper, a duality between wiretap and state-dependent channels with non-causal channel state information at the transmitter is established. First, a common achievable scheme is described for a certain class of state-dependent and wiretap channels. Further, state-dependent and wiretap channels for which this scheme is capacity (resp. secrecy capacity) achieving are identified. These channels are said to be dual. This duality is used to establish the secrecy capacity of certain state-dependent wiretap channels with non-causal channel state information at the transmitter. Interestingly, combatting the eavesdropper or combatting the lack of state information at the receiver turn out to be two non-concurrent tasks

Sterile Protection against Plasmodium knowlesi in Rhesus Monkeys from a Malaria Vaccine: Comparison of Heterologous Prime Boost Strategies

Using newer vaccine platforms which have been effective against malaria in rodent models, we tested five immunization regimens against Plasmodium knowlesi in rhesus monkeys. All vaccines included the same four P. knowlesi antigens: the pre-erythrocytic antigens CSP, SSP2, and erythrocytic antigens AMA1, MSP1. We used four vaccine platforms for prime or boost vaccinations: plasmids (DNA), alphavirus replicons (VRP), attenuated adenovirus serotype 5 (Ad), or attenuated poxvirus (Pox). These four platforms combined to produce five different prime/boost vaccine regimens: Pox alone, VRP/Pox, VRP/Ad, Ad/Pox, and DNA/Pox. Five rhesus monkeys were immunized with each regimen, and five Control monkeys received a mock vaccination. The time to complete vaccinations was 420 days. All monkeys were challenged twice with 100 P. knowlesi sporozoites given IV. The first challenge was given 12 days after the last vaccination, and the monkeys receiving the DNA/Pox vaccine were the best protected, with 3/5 monkeys sterilely protected and 1/5 monkeys that self-cured its parasitemia. There was no protection in monkeys that received Pox malaria vaccine alone without previous priming. The second sporozoite challenge was given 4 months after the first. All 4 monkeys that were protected in the first challenge developed malaria in the second challenge. DNA, VRP and Ad5 vaccines all primed monkeys for strong immune responses after the Pox boost. We discuss the high level but short duration of protection in this experiment and the possible benefits of the long interval between prime and boost

CRISPR screens identify gene targets at breast cancer risk loci

Background: Genome-wide association studies (GWAS) have identified > 200 loci associated with breast cancer risk. The majority of candidate causal variants are in noncoding regions and likely modulate cancer risk by regulating gene expression. However, pinpointing the exact target of the association, and identifying the phenotype it mediates, is a major challenge in the interpretation and translation of GWAS. Results: Here, we show that pooled CRISPR screens are highly effective at identifying GWAS target genes and defining the cancer phenotypes they mediate. Following CRISPR mediated gene activation or suppression, we measure proliferation in 2D, 3D, and in immune-deficient mice, as well as the effect on DNA repair. We perform 60 CRISPR screens and identify 20 genes predicted with high confidence to be GWAS targets that promote cancer by driving proliferation or modulating the DNA damage response in breast cells. We validate the regulation of a subset of these genes by breast cancer risk variants. Conclusions: We demonstrate that phenotypic CRISPR screens can accurately pinpoint the gene target of a risk locus. In addition to defining gene targets of risk loci associated with increased breast cancer risk, we provide a platform for identifying gene targets and phenotypes mediated by risk variants.Natasha K. Tuano, Jonathan Beesley, Murray Manning, Wei Shi, Laura Perlaza, Jimenez, Luis F. Malaver, Ortega, Jacob M. Paynter, Debra Black, Andrew Civitarese, Karen McCue, Aaron Hatzipantelis, Kristine Hillman, Susanne Kaufmann, Haran Sivakumaran, Jose M. Polo, Roger R. Reddel, Vimla Band, Juliet D. French, Stacey L. Edwards, David R. Powell, Georgia Chenevix, Trench, and Joseph Rosenblu

Why Functional Pre-Erythrocytic and Bloodstage Malaria Vaccines Fail: A Meta-Analysis of Fully Protective Immunizations and Novel Immunological Model

Background: Clinically protective malaria vaccines consistently fail to protect adults and children in endemic settings, and at best only partially protect infants. Methodology/Principal Findings: We identify and evaluate 1916 immunization studies between 1965-February 2010, and exclude partially or nonprotective results to find 177 completely protective immunization experiments. Detailed reexamination reveals an unexpectedly mundane basis for selective vaccine failure: live malaria parasites in the skin inhibit vaccine function. We next show published molecular and cellular data support a testable, novel model where parasite-host interactions in the skin induce malaria-specific regulatory T cells, and subvert early antigen-specific immunity to parasite-specific immunotolerance. This ensures infection and tolerance to reinfection. Exposure to Plasmodium-infected mosquito bites therefore systematically triggers immunosuppression of endemic vaccine-elicited responses. The extensive vaccine trial data solidly substantiate this model experimentally. Conclusions/Significance: We conclude skinstage-initiated immunosuppression, unassociated with bloodstage parasites, systematically blocks vaccine function in the field. Our model exposes novel molecular and procedural strategies to significantly and quickly increase protective efficacy in both pipeline and currently ineffective malaria vaccines, and forces fundamental reassessment of central precepts determining vaccine development. This has major implications fo

Platform for Plasmodium vivax vaccine discovery and development

Plasmodium vivax is the most prevalent malaria parasite on the American continent. It generates a global burden of 80-100 million cases annually and represents a tremendous public health problem, particularly in the American and Asian continents. A malaria vaccine would be considered the most cost-effective measure against this vector-borne disease and it would contribute to a reduction in malaria cases and to eventual eradication. Although significant progress has been achieved in the search for Plasmodium falciparum antigens that could be used in a vaccine, limited progress has been made in the search for P. vivax components that might be eligible for vaccine development. This is primarily due to the lack of in vitro cultures to serve as an antigen source and to inadequate funding. While the most advanced P. falciparum vaccine candidate is currently being tested in Phase III trials in Africa, the most advanced P. vivax candidates have only advanced to Phase I trials. Herein, we describe the overall strategy and progress in P. vivax vaccine research, from antigen discovery to preclinical and clinical development and we discuss the regional potential of Latin America to develop a comprehensive platform for vaccine development

HOW CAN IGNORANT BUT PATIENT COGNITIVE TERMINALS LEARN THEIR STRATEGY AND UTILITY?

This paper aims to contribute to bridge the gap between existing theoretical results in distributed radio resource allocation policies based on equilibria in games (assuming complete information and rational players) and practical design of signal processing algorithms for self-configuring wireless networks. For this purpose, the framework of learning theory in games is exploited. Here, a new learning algorithm based on mild information assumptions at the transmitters is presented. This algorithm possesses attractive convergence properties not available for standard reinforcement learning algorithms and in addition, it allows each transmitter to learn both its optimal strategy and the values of its expected utility for all its actions. A detailed convergence analysis is conducted. In particular, a framework for studying heterogeneous wireless networks where transmitters do not learn at the same rate is provided. The proposed algorithm, which can be applied to any wireless network verifying the information assumptions stated, is applied to the case of multiple access channels in order to provide some numerical results. 1