273 research outputs found
EVM as generic QoS trigger for heterogeneous wieless overlay network
Fourth Generation (4G) Wireless System will integrate heterogeneous wireless
overlay systems i.e. interworking of WLAN/ GSM/ CDMA/ WiMAX/ LTE/ etc with
guaranteed Quality of Service (QoS) and Experience (QoE).QoS(E) vary from
network to network and is application sensitive. User needs an optimal mobility
solution while roaming in Overlaid wireless environment i.e. user could
seamlessly transfer his session/ call to a best available network bearing
guaranteed Quality of Experience. And If this Seamless transfer of session is
executed between two networks having different access standards then it is
called Vertical Handover (VHO). Contemporary VHO decision algorithms are based
on generic QoS metrics viz. SNR, bandwidth, jitter, BER and delay. In this
paper, Error Vector Magnitude (EVM) is proposed to be a generic QoS trigger for
VHO execution. EVM is defined as the deviation of inphase/ quadrature (I/Q)
values from ideal signal states and thus provides a measure of signal quality.
In 4G Interoperable environment, OFDM is the leading Modulation scheme (more
prone to multi-path fading). EVM (modulation error) properly characterises the
wireless link/ channel for accurate VHO decision. EVM depends on the inherent
transmission impairments viz. frequency offset, phase noise,
non-linear-impairment, skewness etc. for a given wireless link. Paper provides
an insight to the analytical aspect of EVM & measures EVM (%) for key
management subframes like association/re-association/disassociation/ probe
request/response frames. EVM relation is explored for different possible
NAV-Network Allocation Vectors (frame duration). Finally EVM is compared with
SNR, BER and investigation concludes EVM as a promising QoS trigger for OFDM
based emerging wireless standards.Comment: 12 pages, 7 figures, IJWMN 2010 august issue vol. 2, no.
Modeling the International-Trade Network: A Gravity Approach
This paper investigates whether the gravity model (GM) can explain the
statistical properties of the International Trade Network (ITN). We fit data on
international-trade flows with a GM specification using alternative fitting
techniques and we employ GM estimates to build a weighted predicted ITN, whose
topological properties are compared to observed ones. Furthermore, we propose
an estimation strategy to predict the binary ITN with a GM. We find that the GM
successfully replicates the weighted-network structure of the ITN, only if one
fixes its binary architecture equal to the observed one. Conversely, the GM
performs very badly when asked to predict the presence of a link, or the level
of the trade flow it carries, whenever the binary structure must be
simultaneously estimated
Modeling the International-Trade Network: A Gravity Approach
This paper investigates whether the gravity model (GM) can explain the statistical properties of the International Trade Network (ITN). We fit data on international-trade flows with a GM specification using alternative fitting techniques and we employ GM estimates to build a weighted predicted ITN, whose topological properties are compared to observed ones. Furthermore, we propose an estimation strategy to predict the binary ITN with a GM. We find that the GM successfully replicates the weighted-network structure of the ITN, only if one fixes its binary architecture equal to the observed one. Conversely, the GM performs very badly when asked to predict the presence of a link, or the level of the trade flow it carries, whenever the binary structure must be simultaneously estimated.International Trade Network; Gravity Equation; Weighted Network Analysis; Topological Properties; Econophysics
The Multi-Network of International Trade: A Commodity-Specific Analysis
We study the topological properties of the multi-network of commodity-specific trade relations among world countries over the 1992-2003 period, comparing them with those of the aggregate-trade network, known in the literature as the international trade network (ITN). We show that link-weight distributions of commodity-specific networks are extremely heterogeneous and (quasi) log-normality of aggregate link-weight distribution is generated as a sheer outcome of aggregation. Commodity-specific networks also display average connectivity, clustering and centrality levels very different from their aggregate counterpart. We also find that ITN complete connectivity is mainly achieved through the presence of many weak links that keep commodity-specific networks together, and that the correlation structure existing between topological statistics within each single network is fairly robust and mimics that of the aggregate network. Finally, we employ cross-commodity correlations between link weights to build taxonomies of commodities. Our results suggest that on the top of a relatively time-invariant ''intrinsic'' taxonomy (based on inherent between-commodity similarities), the roles played by different commodities in the ITN have become more and more dissimilar, possibly as the result of an increased trade specialization.Weighted directed networks; International trade network; Multi-networks; Commodity-specific trade; Econophysics
Null Models of Economic Networks: The Case of the World Trade Web
In all empirical-network studies, the observed properties of economic
networks are informative only if compared with a well-defined null model that
can quantitatively predict the behavior of such properties in constrained
graphs. However, predictions of the available null-model methods can be derived
analytically only under assumptions (e.g., sparseness of the network) that are
unrealistic for most economic networks like the World Trade Web (WTW). In this
paper we study the evolution of the WTW using a recently-proposed family of
null network models. The method allows to analytically obtain the expected
value of any network statistic across the ensemble of networks that preserve on
average some local properties, and are otherwise fully random. We compare
expected and observed properties of the WTW in the period 1950-2000, when
either the expected number of trade partners or total country trade is kept
fixed and equal to observed quantities. We show that, in the binary WTW,
node-degree sequences are sufficient to explain higher-order network properties
such as disassortativity and clustering-degree correlation, especially in the
last part of the sample. Conversely, in the weighted WTW, the observed sequence
of total country imports and exports are not sufficient to predict higher-order
patterns of the WTW. We discuss some important implications of these findings
for international-trade models.Comment: 39 pages, 46 figures, 2 table
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