390 research outputs found
Pilot Clustering in Asymmetric Massive MIMO Networks
We consider the uplink of a cellular massive MIMO network. Since the spectral
efficiency of these networks is limited by pilot contamination, the pilot
allocation across cells is of paramount importance. However, finding efficient
pilot reuse patterns is non-trivial especially in practical asymmetric base
station deployments. In this paper, we approach this problem using coalitional
game theory. Each cell has its own unique pilots and can form coalitions with
other cells to gain access to more pilots. We develop a low-complexity
distributed algorithm and prove convergence to an individually stable coalition
structure. Simulations reveal fast algorithmic convergence and substantial
performance gains over one-cell coalitions and full pilot reuse.Comment: Published in Proc. of IEEE International Workshop on Signal
Processing Advances in Wireless Communications (SPAWC '15), 5 pages, 1
tables, 5 figure
Optimal Multiuser Transmit Beamforming: A Difficult Problem with a Simple Solution Structure
Transmit beamforming is a versatile technique for signal transmission from an
array of antennas to one or multiple users [1]. In wireless communications,
the goal is to increase the signal power at the intended user and reduce
interference to non-intended users. A high signal power is achieved by
transmitting the same data signal from all antennas, but with different
amplitudes and phases, such that the signal components add coherently at the
user. Low interference is accomplished by making the signal components add
destructively at non-intended users. This corresponds mathematically to
designing beamforming vectors (that describe the amplitudes and phases) to have
large inner products with the vectors describing the intended channels and
small inner products with non-intended user channels.
While it is fairly easy to design a beamforming vector that maximizes the
signal power at the intended user, it is difficult to strike a perfect balance
between maximizing the signal power and minimizing the interference leakage. In
fact, the optimization of multiuser transmit beamforming is generally a
nondeterministic polynomial-time (NP) hard problem [2]. Nevertheless, this
lecture shows that the optimal transmit beamforming has a simple structure with
very intuitive properties and interpretations. This structure provides a
theoretical foundation for practical low-complexity beamforming schemes.
(See this lecture note for the complete abstract/introduction)Comment: Accepted for publication as lecture note in IEEE Signal Processing
Magazine, 11 pages, 3 figures. The results can be reproduced using the
following Matlab code: https://github.com/emilbjornson/optimal-beamformin
Interference Alignment-Aided Base Station Clustering using Coalition Formation
Base station clustering is necessary in large interference networks, where
the channel state information (CSI) acquisition overhead otherwise would be
overwhelming. In this paper, we propose a novel long-term throughput model for
the clustered users which addresses the balance between interference mitigation
capability and CSI acquisition overhead. The model only depends on statistical
CSI, thus enabling long-term clustering. Based on notions from coalitional game
theory, we propose a low-complexity distributed clustering method. The
algorithm converges in a couple of iterations, and only requires limited
communication between base stations. Numerical simulations show the viability
of the proposed approach.Comment: 2nd Prize, Student Paper Contest. Copyright 2015 SS&C. Published in
the Proceedings of the 49th Asilomar Conference on Signals, Systems and
Computers, Nov 8-11, 2015, Pacific Grove, CA, US
Gender and Overconfidence
Do males differ from females in terms of self-confidence? The structure of the Economics I exam at Stockholm University provides an opportunity to shed some light on this question. By answering an extra, optional question, the students can aim for a higher mark. We find a clear gender difference in that male students are more inclined than female students to take this opportunity. This difference in selfassessment is more pronounced among younger than among older students.Overconfidence; gender differences; exam behavior; exam results
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