The power of diversity over large solution spaces

We consider a team of agents with limited problem-solving ability facing a disjunctive task over a large solution space. We provide sufficient conditions for the following four statements. First, two heads are better than one: a team of two agents will solve the problem even if neither agent alone would be able to. Second, teaming up does not guarantee success: if the agents are not sufficiently creative, even a team of arbitrary size may fail to solve the problem. Third, "defendit numerus": when the agent's problem-solving ability is adversely affected by the complexity of the solution space, the solution of the problem requires only a mild increase in the size of the team. Fourth, groupthink impairs the power of diversity: if agents' abilities are positively correlated, a larger team is necessary to solve the problem.Problem-solving; Bounded rationality; Theory of teams; Groupthink

Diversity Combining for RF Energy Harvesting

RF energy harvesting (RFEH) is a promising technology for energy requirements of wireless communication nodes. However, providing sufficient amount of energy to ensure self-sufficient devices based on RFEH may be challenging. In this paper, the use of diversity combining in RFEH systems is proposed to increase the amount of harvested energy. The power consumption of diversity combining process is also taken into account to analyze the net benefit of diversity combining. Performances of RFEH systems are investigated for selection combining (SC), equal gain combining (EGC), and maximal ratio combining (MRC) techniques. Simulations are conducted to compare the numerical results of SC, EGC, and MRC, and the results show that although the diversity combining techniques can improve the energy harvesting performance, the power consumption parameters have a critical importance while determining the suitable technique

Estimation Diversity and Energy Efficiency in Distributed Sensing

Distributed estimation based on measurements from multiple wireless sensors is investigated. It is assumed that a group of sensors observe the same quantity in independent additive observation noises with possibly different variances. The observations are transmitted using amplify-and-forward (analog) transmissions over non-ideal fading wireless channels from the sensors to a fusion center, where they are combined to generate an estimate of the observed quantity. Assuming that the Best Linear Unbiased Estimator (BLUE) is used by the fusion center, the equal-power transmission strategy is first discussed, where the system performance is analyzed by introducing the concept of estimation outage and estimation diversity, and it is shown that there is an achievable diversity gain on the order of the number of sensors. The optimal power allocation strategies are then considered for two cases: minimum distortion under power constraints; and minimum power under distortion constraints. In the first case, it is shown that by turning off bad sensors, i.e., sensors with bad channels and bad observation quality, adaptive power gain can be achieved without sacrificing diversity gain. Here, the adaptive power gain is similar to the array gain achieved in Multiple-Input Single-Output (MISO) multi-antenna systems when channel conditions are known to the transmitter. In the second case, the sum power is minimized under zero-outage estimation distortion constraint, and some related energy efficiency issues in sensor networks are discussed.Comment: To appear at IEEE Transactions on Signal Processin

2-D Coherence Factor for Sidelobe and Ghost Suppressions in Radar Imaging

The coherence factor (CF) is defined as the ratio of coherent power to incoherent power received by the radar aperture. The incoherent power is computed by the multi-antenna receiver based on only the spatial variable. In this respect, it is a one-dimensional (1-D) CF, and thereby the image sidelobes in down-range cannot be effectively suppressed. We propose a two-dimensional (2-D) CF by supplementing the 1-D CF by an incoherent sum dealing with the frequency dimension. In essence, we employ both spatial diversity and frequency diversity which, respectively, enhance imaging quality in cross range and range. Simulations and experimental results are provided to demonstrate the performance advantages of the proposed approach.Comment: 7 pages, 21 figure

Fundamental Limits in Correlated Fading MIMO Broadcast Channels: Benefits of Transmit Correlation Diversity

We investigate asymptotic capacity limits of the Gaussian MIMO broadcast channel (BC) with spatially correlated fading to understand when and how much transmit correlation helps the capacity. By imposing a structure on channel covariances (equivalently, transmit correlations at the transmitter side) of users, also referred to as \emph{transmit correlation diversity}, the impact of transmit correlation on the power gain of MIMO BCs is characterized in several regimes of system parameters, with a particular interest in the large-scale array (or massive MIMO) regime. Taking the cost for downlink training into account, we provide asymptotic capacity bounds of multiuser MIMO downlink systems to see how transmit correlation diversity affects the system multiplexing gain. We make use of the notion of joint spatial division and multiplexing (JSDM) to derive the capacity bounds. It is advocated in this paper that transmit correlation diversity may be of use to significantly increase multiplexing gain as well as power gain in multiuser MIMO systems. In particular, the new type of diversity in wireless communications is shown to improve the system multiplexing gain up to by a factor of the number of degrees of such diversity. Finally, performance limits of conventional large-scale MIMO systems not exploiting transmit correlation are also characterized.Comment: 29 pages, 8 figure

Fluctuations in models of biological macroevolution

Fluctuations in diversity and extinction sizes are discussed and compared for two different, individual-based models of biological coevolution. Both models display power-law distributions for various quantities of evolutionary interest, such as the lifetimes of individual species, the quiet periods between evolutionary upheavals larger than a given cutoff, and the sizes of extinction events. Time series of the diversity and measures of the size of extinctions give rise to flicker noise. Surprisingly, the power-law behaviors of the probability densities of quiet periods in the two models differ, while the distributions of the lifetimes of individual species are the same.Comment: 7 pages, 5 figure