Low-Complexity Learning for Dynamic Spectrum Access in Multi-User Multi-Channel Networks

Department of Computer Science and EngineeringIn cognitive radio Networks (CRNs), dynamic spectrum access allows (unlicensed) users to identify and access unused channels opportunistically, thus improves spectrum utility. In this paper, we address the user-channel allocation problem in multi-user multi-channel CRNs without a prior knowledge of channel statistics. A reward of a channel is stochastic with unknown distribution, and statistically different for each user. Each user either explores a channel to learn the channel statistics, or exploits the channel with the highest expected reward based on information collected so far. Further, a channel should be accessed exclusively by one user at a time due to a collision. Using multi-armed bandit framework, we develop provably efficient solutions whose computational complexities are linear to the number of users and channels.ope

Microinstabilities in the Transition Region of Weak Quasi-perpendicular Intracluster Shocks

Microinstabilities play important roles in both entropy generation and particle acceleration in collisionless shocks. Recent studies have suggested that in the transition region of quasi-perpendicular (Q(perpendicular to)) shocks in the high-beta (beta = P-gas/P-B) intracluster medium (ICM), the ion temperature anisotropy due to the reflected-gyrating ions could trigger the Alfven ion cyclotron (AIC) instability and the ion-mirror instability, while the electron temperature anisotropy induced by magnetic field compression could excite the whistler instability and the electron-mirror instability. Adopting the numerical estimates for ion and electron temperature anisotropies found in the particle-in-cell (PIC) simulations of Q(perpendicular to) shocks with sonic Mach numbers, M-s = 2-3, we carry out a linear stability analysis for these microinstabilities. The kinetic properties of the microinstabilities and the ensuing plasma waves on both ion and electron scales are described for wide ranges of parameters, including beta and the ion-to-electron mass ratio. In addition, the nonlinear evolution of the induced plasma waves are examined by performing 2D PIC simulations with periodic boundary conditions. We find that for beta approximate to 20-100, the AIC instability could induce ion-scale waves and generate shock surface ripples in supercritical shocks above the AIC critical Mach number, M-AIC* approximate to 2.3. Also, electron-scale waves are generated primarily by the whistler instability in these high-beta shocks. The resulting multiscale waves from electron to ion scales are thought to be essential in the electron injection to diffusive shock acceleration in Q(perpendicular to) shocks in the ICM

Combined admixture mapping and association analysis identifies a novel blood pressure genetic locus on 5p13: contributions from the CARe consortium

Admixture mapping based on recently admixed populations is a powerful method to detect disease variants with substantial allele frequency differences in ancestral populations. We performed admixture mapping analysis for systolic blood pressure (SBP) and diastolic blood pressure (DBP), followed by trait-marker association analysis, in 6303 unrelated African-American participants of the Candidate Gene Association Resource (CARe) consortium. We identified five genomic regions (P< 0.001) harboring genetic variants contributing to inter-individual BP variation. In follow-up association analyses, correcting for all tests performed in this study, three loci were significantly associated with SBP and one significantly associated with DBP (P< 10−5). Further analyses suggested that six independent single-nucleotide polymorphisms (SNPs) contributed to the phenotypic variation observed in the admixture mapping analysis. These six SNPs were examined for replication in multiple, large, independent studies of African-Americans [Women's Health Initiative (WHI), Maywood, Genetic Epidemiology Network of Arteriopathy (GENOA) and Howard University Family Study (HUFS)] as well as one native African sample (Nigerian study), with a total replication sample size of 11 882. Meta-analysis of the replication set identified a novel variant (rs7726475) on chromosome 5 between the SUB1 and NPR3 genes, as being associated with SBP and DBP (P< 0.0015 for both); in meta-analyses combining the CARe samples with the replication data, we observed P-values of 4.45 × 10−7 for SBP and 7.52 × 10−7 for DBP for rs7726475 that were significant after accounting for all the tests performed. Our study highlights that admixture mapping analysis can help identify genetic variants missed by genome-wide association studies because of drastically reduced number of tests in the whole genome

Low-complexity Learning for Dynamic Spectrum Access in Multi-User Multi-Channel Networks

In Cognitive Radio Networks (CRNs), dynamic spectrum access allows (unlicensed) users to identify and access unused channels opportunistically, thus improves spectrum utility. In this paper, we address the user-channel allocation problem in multi-user multi-channel CRNs without a prior knowledge of channel statistics. A reward of a channel is stochastic with unknown distribution, and statistically different for each user. Each user either explores a channel to learn the channel statistics, or exploits the channel with the highest expected reward based on information collected so far. Further, a channel should be accessed exclusively by one user at a time due to a collision. Using multi-armed bandit framework, we develop a provably efficient solution whose computational complexity is O(NK), where N denotes the number of users and K denotes the number of channels

Combinatorial multi-armed bandits in cognitive radio networks: A brief overview

Combinatorial multi-armed bandit (MAB) problem can be used to formulate sequential decision problems with exploration-exploitation tradeoff. Dynamic spectrum access (DSA) in cognitive radio (CR) networks is one of important applications. In this work, we briefly overview combinatorial MAB problems with its possible applications to CR networks. We first investigate the standard MAB problems where a single player either explores an arm to gather information to improve its decision strategy, or exploits the arm based on the information that it has collected at each round. Then, we study the taxonomy of combinatorial MAB problems, in particular for multi-player scenarios with independent and identically distributed (i.i.d.) rewards. Finally, we discuss limitations of existing works and interesting open problems

Joint Scheduling of Data Transmission and Wireless Power Transfer in Multi-Channel Device-to-Device Networks

As the mobile traffic explodes, direct device-to-device communications attract much attention as one of next-generation technologies to increase the spatial spectrum efficiency in multichannel wireless networks. On the other hand, as battery-powered mobile devices interrupt user experience due to limited battery capacity, wireless power transfer has emerged as a convenient and perpetual power supply. However, current circuit technologies cannot support both energy harvesting and information decoding at the same time, and thus the time-division-multiple-access approach is often used for either data transmission or power transfer at a time, which requires joint scheduling of data transmissions and wireless power transfer. In this paper, we investigate the joint scheduling problem of multi-channel data transmissions and wireless power transfer, formulate the joint problem using a unified framework, and identify new difficulties in efficient resource allocation. We also develop a preliminary solution that achieves good empirical performance in single-hop D2D network scenarios.close

Pricing for past channel state information in multi-channel cognitive radio networks

Cognitive Radio (CR) networks have received much attention as a solution to the spectrum inefficiency problem of current license-based regulatory management. In CR networks, Secondary User (SU) can use a spectrum vacancy that can be detected by either sensing-before-transmission or database access. However, sensing inaccuracy or long access time to database often becomes a major obstacle to timely detect the spectrum vacancy. In this paper, we develop a hybrid detection framework in multi-channel CR networks, where an SU can selectively sense a channel for spectrum vacancy by accessing the spectrum history of Markovian channels. We focus on the value of the channel history information offered by the Primary Provider (PP) of each channel, and consider a market for the information between multiple PPs and SU. We investigate the interplay between of the PPs and the SU through their pricing and buying decisions for the information, in the presence of sensing inaccuracy, i.e., false alarm and miss detection

A learning-based distributed algorithm for scheduling in multi-hop wireless networks

We address the joint problem of learning and scheduling in multi-hop wireless network without a prior knowledge on link rates. Previous scheduling algorithms need the link rate information, and learning algorithms often require a centralized entity and polynomial complexity. These become a major obstacle to develop an efficient learning-based distributed scheme for resource allocation in large-scale multi-hop networks. In this work, by incorporating with learning algorithm, we develop provably efficient scheduling scheme under packet arrival dynamics without a priori link rate information. We extend the results to distributed implementation and evaluation their performance through simulations

Firehose Instability in Astrophysical and Space Environments

The firehose instability is driven by a pressure anisotropy in a magnetized plasma when the plasma has T??? &gt; T???, that is, the temperature along the magnetic field is higher than the perpendicular temperature. Such condition occurs commonly in astrophysical and space environments, for instance, when there are beams aligned with the background magnetic field. Recently, it was argued that around weak quasi-perpendicular shocks in high-?? plasmas of the intracluster medium, shock-reflected electrons propagating upstream cause the temperature anisotropy of T??? &gt; T???. This electron temperature anisotropy can trigger the electron firehose instability (EFI). In the study, the kinetic properties of the EFI are first examined by the linear stability analysis based on the kinetic Vlasov-Maxwell theory and then further investigated by 2D Particle-in-Cell (PIC) simulations, especially focusing on those in high-?? (??~100) plasmas. We then discuss the implication of our work on electron acceleration in ICM shocks in clusters of galaxies