Abstract-Fast varying active transmitter sets are a key feature of wireless communication networks with very short transmissions arising in machine-to-machine communications. A consequence is that the interference is dynamic, leading to nonGaussian statistics. In this paper, we study the behavior of largescale communication networks in the presence of isotropic α-stable interference, which forms a model for dynamic interference. We first characterize the achievable rate of each link by considering a non-Gaussian input distribution, which is shown to outperform a Gaussian input. Moreover, we analyze the area spectral efficiency, which is the total rate per square meter. Our analysis suggests that analogously to the common model of slowly varying active transmitter sets, dense networks maximize the area spectral efficiency.
Parallel channels form a basic building block for communication systems, including those based on OFDM and CDMA. While parallel Gaussian noise channels have been widely studied, parallel impulsive noise channels have received significantly less attention despite their importance in a range of modern communication systems. In this paper, this problem is addressed and a power allocation strategy is developed for parallel symmetric α-stable noise channels-a key class of impulsive noise channels. We show that our strategy can improve achievable rates by up to a factor of 1.5 over the standard waterfilling algorithm that assumes the noise is Gaussian.
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