1403/01/10
محمدجواد عزیزی پور

محمدجواد عزیزی پور

مرتبه علمی: استادیار
ارکید:
تحصیلات: دکترای تخصصی
اسکاپوس:
دانشکده: دانشکده مهندسی و فناوری
نشانی: دانشکده مهندسی و فناوری، گروه مهندسی برق
تلفن: 01135305111

مشخصات پژوهش

عنوان
Compressed channel estimation for FDD massive MIMO systems without prior knowledge of sparse channel model
نوع پژوهش
JournalPaper
کلیدواژه‌ها
Channel Estimation, FDD Systems, Massive MIMO, Pilot Overhead
سال
2019
مجله IET Communications
شناسه DOI
پژوهشگران Mohammad Javad Azizipour ، Kamal Mohamed-pour

چکیده

In this study, a new greedy-based algorithm for sparse channel estimation in frequency-division duplexing massive multiple-input multiple-output (MIMO) systems is introduced. The proposed algorithm is able to acquire the channel with no information about the channel model such as the sparsity order, statistical bound on sparsity support, and special features of the channel. In other words, the authors assume that the massive channel is totally unknown and then exploit the inherent property of correlation between measurements and the sensing matrix to estimate the channel, which is available at the user side. By utilising this property, a halting parameter is defined as the halting threshold instead of known prior information assumed in the conventional greedy algorithms. Furthermore, the lower and upper bounds of the halting parameter are obtained that helps the algorithm to take the suitable values of this parameter and by considering the lower bound as the values of the halting parameter, the algorithm can prevent from missing the original channel bins. Simulation results demonstrate that the proposed algorithm outperforms its counterparts in terms of normalised mean square error while it faces a completely unknown massive MIMO channel.