Mahdi Zamanighomi

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—In this paper, a two-user discrete memoryless multiple-access channel (DM-MAC) with correlated channel states, each known at one of the encoders is considered, in which each encoder transmits independent messages and tries to cooperate with the other one. To consider cooperating encoders, it is assumed that each encoder strictly-causally receives and(More)
In this paper, the degrees of freedom (DoF) regions of constant coefficient multiple antenna interference channels are investigated. First, we consider a K-user Gaussian interference channel with M k antennas at transmitter k, 1 ≤ k ≤ K, and N j antennas at receiver j, 1 ≤ j ≤ K, denoted as a (K, [M k ], [N j ]) channel. Relying on a result of simultaneous(More)
—In this paper, we present a new method for variable elimination in systems of inequations which is much faster than the Fourier-Motzkin Elimination (FME) method. In our method, a linear Diophantine problem is introduced which is dual to our original problem. The new Diophantine system is then solved, and the final result is calculated by finding the dual(More)
—We consider a constant K-user Gaussian interference channel with M antennas at each transmitter and N antennas at each receiver, denoted as a (K, M, N) channel. Relying on a result on simultaneous Diophantine approximation, a real interference alignment scheme with joint receive antenna processing is developed. The scheme is used to provide new proofs for(More)
We consider a single hop wireless X network with K transmitters and J receivers, all with single antenna. Each transmitter conveys for each receiver an independent message. The channel is assumed to have constant coefficients. We develop interference alignment scheme for this setup and derived several achievable degrees of freedom regions. We show that in(More)
We are developing a novel intradural spinal cord (SC) stimulator designed to improve the treatment of intractable pain and the sequelae of SC injury. In-vivo ovine models of neuropathic pain and moderate SC injury are being implemented for pre-clinical evaluations of this device, to be carried out via gait analysis before and after induction of the relevant(More)
Dimension reduction methods are commonly applied to high-throughput biological datasets. However, the results can be hindered by confounding factors, either biologically or technically originated. In this study, we propose a Principal Component Analysis-based approach to Adjust for Confounding variation (AC-PCA). We show that AC-PCA can adjust for(More)