Amin Khansefid

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This letter proposes a simple channel estimator for a multi-cell massive MIMO system with pilot contamination. Under moderate or strong pilot contamination, the existing least square (LS) channel estimator suffers from substantial performance degradation while the existing minimum mean square error (MMSE) channel estimator offers much improved performance(More)
Massive multi-input multi-output (MIMO) systems require channel state information (CSI) at base stations. In multicell environments, adjacent cells using the same spectrum cause a pilot contamination problem and degrade CSI quality. Under such practical environments, it is important to assess achievable rate of the system for a proper system design. There(More)
Emerging millimeter-wave massive MIMO systems are subject to strong radio frequency (RF) distortions and their compensation is crucial to meet the high performance targets of such systems. This paper presents novel pilot designs and related estimators for multi-input multi-output (MIMO) millimeter-wave systems characterized by frequency-selective channels,(More)
This paper considers massive MIMO uplink using maximum ratio combining (MRC) and zero forcing (ZF) receivers with perfect and imperfect channel state information (CSI). We develop pilot and data power allocation strategies among users under peak power constraint and prove their asymptotic optimality in maximizing the sum-rate lower bound. Then we(More)
In this paper, we consider massive MIMO uplink using maximum ratio combining (MRC) and zero forcing (ZF) receivers with perfect and imperfect channel state information (CSI). We derive lower and upper bounds on the achievable rates with arbitrary power allocation. Analytical and simulation results illustrate the accuracy and characteristics of the rate(More)
Massive MIMO systems offer large spectrum efficiency improvements but when applied to systems with noncontiguous bands as commonly encountered in practice, their performance gains are largely offset by the overhead in acquiring channel state information (CSI). This paper presents three schemes to enable overhead-efficient massive MIMO in noncontiguous bands(More)
Millimeter-wave (mmWave) massive MIMO systems enable very high data rate applications for 5G systems, but they also face the challenging issues of strong RF distortions and constraints on computational complexity due to very high sampling rate. The choice of waveform and its parameter settings plays an important role in addressing these challenges. This(More)
The study problem was learning a fuzzy decision tree to classify patients with adnexal mass into either of benign or malignant class prior to surgery using patients’ medical history, physical exam, laboratory tests, and ultrasonography. A learning algorithm was developed to learn a fuzzy decision tree in three steps. In the growing step, a binary decision(More)
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