5,386 research outputs found
Payments for Environmental Services: Some Nuts and Bolts
Payments for environmental services (PES) are part of a new and more direct conservation paradigm, explicitly recognizing the need to bridge the interests of landowners and outsiders. Eloquent theoretical assessments have praised the absolute advantages of PES over traditional conservation approaches. Some pilot PES exist in the tropics, but many fi eld practitioners and prospective service buyers and sellers remain skeptical about the concept. This paper aims to help demystify PES for non-economists, starting with a simple and coherent defi nition of the term. It then provides practical 'how-to' hints for PES design. It considers the likely niche for PES in the portfolio of conservation approaches. This assessment is based on a literature review, combined with fi eld observations from research in Latin America and Asia. It concludes that service users will continue to drive PES, but their willingness to pay will only rise if schemes can demonstrate clear additionality vis-à-vis carefully established baselines, if trust-building processes with service providers are sustained, and PES recipients' livelihood dynamics is better understood. PES best suits intermediate and/or projected threat scenarios, often in marginal lands with moderate conservation opportunity costs. People facing credible but medium-sized environmental degradation are more likely to become PES recipients than those living in relative harmony with Nature. The choice between PES cash and in-kind payments is highly context-dependent. Poor PES recipients are likely to gain from participation, though their access might be constrained and non-participating landless poor could lose out. PES is a highly promising conservation approach that can benefi t buyers, sellers and improv
Analysis of Alternative Metrics for the PAPR Problem in OFDM Transmission
The effective PAPR of the transmit signal is the standard metric to capture
the effect of nonlinear distortion in OFDM transmission. A common rule of thumb
is the log barrier where is the number of subcarriers which has been
theoretically analyzed by many authors. Recently, new alternative metrics have
been proposed in practice leading potentially to different system design rules
which are theoretically analyzed in this paper. One of the main findings is
that, most surprisingly, the log barrier turns out to be much too
conservative: e.g. for the so-called amplifier-oriented metric the scaling is
rather . To prove this result, new upper bounds on the PAPR
distribution for coded systems are presented as well as a theorem relating PAPR
results to these alternative metrics.Comment: 5 pages, IEEE International Symposium on Information Theory (ISIT),
2011, accepted for publicatio
Adaptation to Income over Time: A Weak Point of Subjective Well-Being
This article holds the view that intertemporal comparisons of subjective well-being measures are only meaningful when the underlying standards of judgment are unaltered. This is a weak point of such measures. The study investigates the change in the satisfaction judgments resulting from adaptation to income over time. Adaptation is defined to be desensitization (sensitization) to the hedonic effect of income resulting from an upward (downward) adjustment of the standards. A framework is introduced that provides empirical estimates for the rate of adaptation using data from the Socio-Economic Panel Study (SOEP).Adaptation, financial satisfaction, subjective well-being, standards of judgment
Upper Bounds and Duality Relations of the Linear Deterministic Sum Capacity for Cellular Systems
The MAC-BC duality of information theory and wireless communications is an
intriguing concept for efficient algorithm design. However, no concept is known
so far for the important cellular channel. To make progress on this front, we
consider in this paper the linear deterministic cellular channel. In
particular, we prove duality of a network with two interfering MACs in each
cell and a network with two interfering BCs in each cell. The operational
region is confined to the weak interference regime. First, achievable schemes
as well as upper bounds will be provided. These bounds are the same for both
channels. We will show, that for specific cases the upper bound corresponds to
the achievable scheme and hence establishing a duality relationship between
them.Comment: 6 pages, to appear in IEEE ICC 2014, Sydney, Australi
Enabling the Multi-User Generalized Degrees of Freedom in the Gaussian Cellular Channel
There has been major progress over the last decade in understanding the
classical interference channel (IC). Recent key results show that constant bit
gap capacity results can be obtained from linear deterministic models (LDMs).
However, it is widely unrecognized that the time-invariant, frequency-flat
cellular channel, which contains the IC as a special case, possesses some
additional generalized degrees of freedom (GDoF) due to multi-user operation.
This was proved for the LDM cellular channel very recently but is an open
question for the corresponding Gaussian counterpart. In this paper, we close
this gap and provide an achievable sum-rate for the Gaussian cellular channel
which is within a constant bit gap of the LDM sum capacity. We show that the
additional GDoFs from the LDM cellular channel carry over. This is enabled by
signal scale alignment. In particular, the multi-user gain reduces the
interference by half in the 2-user per cell case compared to the IC.Comment: 5 pages, to appear in IEEE ITW 2014, Hobart, Australi
Autonomous Algorithms for Centralized and Distributed Interference Coordination: A Virtual Layer Based Approach
Interference mitigation techniques are essential for improving the
performance of interference limited wireless networks. In this paper, we
introduce novel interference mitigation schemes for wireless cellular networks
with space division multiple access (SDMA). The schemes are based on a virtual
layer that captures and simplifies the complicated interference situation in
the network and that is used for power control. We show how optimization in
this virtual layer generates gradually adapting power control settings that
lead to autonomous interference minimization. Thereby, the granularity of
control ranges from controlling frequency sub-band power via controlling the
power on a per-beam basis, to a granularity of only enforcing average power
constraints per beam. In conjunction with suitable short-term scheduling, our
algorithms gradually steer the network towards a higher utility. We use
extensive system-level simulations to compare three distributed algorithms and
evaluate their applicability for different user mobility assumptions. In
particular, it turns out that larger gains can be achieved by imposing average
power constraints and allowing opportunistic scheduling instantaneously, rather
than controlling the power in a strict way. Furthermore, we introduce a
centralized algorithm, which directly solves the underlying optimization and
shows fast convergence, as a performance benchmark for the distributed
solutions. Moreover, we investigate the deviation from global optimality by
comparing to a branch-and-bound-based solution.Comment: revised versio
Performance Limits of Compressive Sensing Channel Estimation in Dense Cloud RAN
Towards reducing the training signaling overhead in large scale and dense
cloud radio access networks (CRAN), various approaches have been proposed based
on the channel sparsification assumption, namely, only a small subset of the
deployed remote radio heads (RRHs) are of significance to any user in the
system. Motivated by the potential of compressive sensing (CS) techniques in
this setting, this paper provides a rigorous description of the performance
limits of many practical CS algorithms by considering the performance of the,
so called, oracle estimator, which knows a priori which RRHs are of
significance but not their corresponding channel values. By using tools from
stochastic geometry, a closed form analytical expression of the oracle
estimator performance is obtained, averaged over distribution of RRH positions
and channel statistics. Apart from a bound on practical CS algorithms, the
analysis provides important design insights, e.g., on how the training sequence
length affects performance, and identifies the operational conditions where the
channel sparsification assumption is valid. It is shown that the latter is true
only in operational conditions with sufficiently large path loss exponents.Comment: 6 pages, two-column format; ICC 201
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