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 $N$ 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