N
Norman C. Beaulieu
Researcher at Beijing University of Posts and Telecommunications
Publications - 717
Citations - 18248
Norman C. Beaulieu is an academic researcher from Beijing University of Posts and Telecommunications. The author has contributed to research in topics: Fading & Rayleigh fading. The author has an hindex of 63, co-authored 716 publications receiving 17301 citations. Previous affiliations of Norman C. Beaulieu include Hainan University & University of Western Ontario.
Papers
More filters
Journal ArticleDOI
A comparison of SNR estimation techniques for the AWGN channel
D.R. Pauluzzi,Norman C. Beaulieu +1 more
TL;DR: The performances of several signal-to noise ratio (SNR) estimation techniques reported in the literature are compared to identify the "best" estimator and some known estimator structures are modified to perform better on the channel of interest.
Journal ArticleDOI
Autoregressive modeling for fading channel simulation
TL;DR: The general applicability of the autoregressive stochastic models method is demonstrated by examples involving the accurate synthesis of nonisotropic fading channel models, and performance comparisons are made with popular fading generation techniques.
Journal ArticleDOI
Resource Allocation in Spectrum-Sharing OFDMA Femtocells With Heterogeneous Services
TL;DR: The resource allocation problem in both the uplink and the downlink for two-tier networks comprising spectrum-sharing femtocells and macrocells is investigated and an iterative subchannel and power allocation algorithm considering heterogeneous services and cross-tier interference is proposed.
Journal ArticleDOI
Resource Allocation for Cognitive Small Cell Networks: A Cooperative Bargaining Game Theoretic Approach
TL;DR: A cooperative Nash bargaining resource allocation algorithm is developed, and is shown to converge to a Pareto-optimal equilibrium for the cooperative game and the existence, uniqueness, and fairness of the solution to this game model are proved.
Journal ArticleDOI
Estimating the distribution of a sum of independent lognormal random variables
TL;DR: Four methods that can be used to approximate the distribution function (DF) of a sum of independent lognormal random variables (RVs) are compared and the results show that the simpler Wilkinson's approach gives a more accurate estimate.