8,601 research outputs found
Capacity scaling law by multiuser diversity in cognitive radio systems
This paper analyzes the multiuser diversity gain in a cognitive radio (CR)
system where secondary transmitters opportunistically utilize the spectrum
licensed to primary users only when it is not occupied by the primary users. To
protect the primary users from the interference caused by the missed detection
of primary transmissions in the secondary network, minimum average throughput
of the primary network is guaranteed by transmit power control at the secondary
transmitters. The traffic dynamics of a primary network are also considered in
our analysis. We derive the average achievable capacity of the secondary
network and analyze its asymptotic behaviors to characterize the multiuser
diversity gains in the CR system.Comment: 5 pages, 2 figures, ISIT2010 conferenc
On the minimum distance of elliptic curve codes
Computing the minimum distance of a linear code is one of the fundamental
problems in algorithmic coding theory. Vardy [14] showed that it is an \np-hard
problem for general linear codes. In practice, one often uses codes with
additional mathematical structure, such as AG codes. For AG codes of genus
(generalized Reed-Solomon codes), the minimum distance has a simple explicit
formula. An interesting result of Cheng [3] says that the minimum distance
problem is already \np-hard (under \rp-reduction) for general elliptic curve
codes (ECAG codes, or AG codes of genus ). In this paper, we show that the
minimum distance of ECAG codes also has a simple explicit formula if the
evaluation set is suitably large (at least of the group order). Our
method is purely combinatorial and based on a new sieving technique from the
first two authors [8]. This method also proves a significantly stronger version
of the MDS (maximum distance separable) conjecture for ECAG codes.Comment: 13 page
The Financial Deepening-Productivity Nexus in China: 1987-2001
The financial intermediation-growth nexus is a widely studied topic in the literature of development economics. Deepening financial intermediation may promote economic growth by mobilizing more investments, and lifting returns to financial resources, which raises productivity. Relying on provincial panel data from China, this paper attempts to examine if regional productivity growth is accounted for by the deepening process of financial development. Towards this end, an appropriate measurement of financial depth is constructed and then included as a determinant of productivity growth. It finds that a significant and positive nexus exists between financial deepening and productivity growth. Given the divergent pattern of financial deepening between coastal and inland provinces, this finding also helps explain the rising regional disparity in China.growth, financial development, productivity, China
Information Cascades on Arbitrary Topologies
In this paper, we study information cascades on graphs. In this setting, each
node in the graph represents a person. One after another, each person has to
take a decision based on a private signal as well as the decisions made by
earlier neighboring nodes. Such information cascades commonly occur in practice
and have been studied in complete graphs where everyone can overhear the
decisions of every other player. It is known that information cascades can be
fragile and based on very little information, and that they have a high
likelihood of being wrong.
Generalizing the problem to arbitrary graphs reveals interesting insights. In
particular, we show that in a random graph , for the right value of
, the number of nodes making a wrong decision is logarithmic in . That
is, in the limit for large , the fraction of players that make a wrong
decision tends to zero. This is intriguing because it contrasts to the two
natural corner cases: empty graph (everyone decides independently based on his
private signal) and complete graph (all decisions are heard by all nodes). In
both of these cases a constant fraction of nodes make a wrong decision in
expectation. Thus, our result shows that while both too little and too much
information sharing causes nodes to take wrong decisions, for exactly the right
amount of information sharing, asymptotically everyone can be right. We further
show that this result in random graphs is asymptotically optimal for any
topology, even if nodes follow a globally optimal algorithmic strategy. Based
on the analysis of random graphs, we explore how topology impacts global
performance and construct an optimal deterministic topology among layer graphs
An Empirical Analysis about Population, Technological Progress, and Economic Growth in Taiwan
This paper empirically analyzed the relationship between population, technological progress, and economic growth in Taiwan from 1954 to 2005, using the LA-VAR (lag-augmented vector autoregression) model. The empirical results reveal that a major conformational change in the economic development of Taiwan after 2000.
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