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We consider the massive MIMO downlink with time-division duplex (TDD) operation and conjugate beamforming transmission. To reliably decode the desired signals, the users need to know the effective channel gain. In this paper, we propose a…

Information Theory · Computer Science 2015-04-01 Hien Quoc Ngo , Erik G. Larsson

Massive MIMO OFDM waveforms help support a large number of users in the same time-frequency resource and also provide significant array gain for uplink reception in cellular systems. However, channel estimation in such large antenna systems…

Information Theory · Computer Science 2024-06-04 P Aswathylakshmi , Radha Krishna Ganti

We study downlink channel estimation in a multi-cell Massive multiple-input multiple-output (MIMO) system operating in time-division duplex. The users must know their effective channel gains to decode their received downlink data. Previous…

Information Theory · Computer Science 2021-11-30 Amin Ghazanfari , Trinh Van Chien , Emil Björnson , Erik G. Larsson

We consider a massive MU-MIMO downlink time-division duplex system where a base station (BS) equipped with many antennas serves several single-antenna users in the same time-frequency resource. We assume that the BS uses linear precoding…

Information Theory · Computer Science 2013-10-08 Hien Quoc Ngo , Erik G. Larsson , Thomas L. Marzetta

We consider a cell-free massive MIMO system with multiple antennas on the users and access points. In previous works, the downlink spectral efficiency (SE) has been evaluated using the hardening bound that requires no downlink pilots. This…

Signal Processing · Electrical Eng. & Systems 2024-04-30 Eren Berk Kama , Junbeom Kim , Emil Björnson

We study downlink (DL) channel estimation in a multi-cell Massive multiple-input multiple-output (MIMO) system operating in a time-division duplex. The users must know their effective channel gains to decode their received DL data signals.…

Information Theory · Computer Science 2021-09-07 Amin Ghazanfari , Trinh Van Chien , Emil Björnson , Erik G. Larsson

Downlink beamforming in Massive MIMO either relies on uplink pilot measurements - exploiting reciprocity and TDD operation, or on the use of a predetermined grid of beams with user equipments reporting their preferred beams, mostly in FDD…

Information Theory · Computer Science 2017-04-04 Jose Flordelis , Fredrik Rusek , Fredrik Tufvesson , Erik G. Larsson , Ove Edfors

In this paper, we analyze the performance of the uplink communication of massive multi-cell multiple-input multiple-output (MIMO) systems under the effects of pilot contamination and delayed channels because of terminal mobility. The base…

Information Theory · Computer Science 2016-11-17 Anastasios K. Papazafeiropoulos , Hien Quoc Ngo , Tharm Ratnarajah

We consider a cell-free massive multiple-input multiple-output (MIMO) system with multiple antennas on the users and access points (APs). In previous works, the downlink spectral efficiency (SE) has been evaluated using the hardening bound…

Information Theory · Computer Science 2026-01-01 Eren Berk Kama , Junbeom Kim , Emil Björnson

Massive Multiple-Input Multiple-Output (massive MIMO) is a variant of multi-user MIMO in which the number of antennas at each Base Station (BS) is very large and typically much larger than the number of users simultaneously served. Massive…

Information Theory · Computer Science 2017-08-16 Mahdi Barzegar Khalilsarai , Saeid Haghighatshoar , Giuseppe Caire

We propose a strategy for orthogonal downlink pilot assignment in cell-free massive MIMO (multiple-input multiple-output) that exploits knowledge of the channel state information, the channel hardening degree at each user, and the mobility…

Information Theory · Computer Science 2019-09-04 Giovanni Interdonato , Pål Frenger , Erik G. Larsson

Transmitter channel state information (CSIT) is indispensable for the spectral efficiency gains offered by massive multiple-input multiple-output (MIMO) systems. In a frequency-division-duplexing (FDD) massive MIMO system, CSIT is typically…

Information Theory · Computer Science 2023-02-10 Deokhwan Han , Jeonghun Park , Namyoon Lee

The concept of deploying a large number of antennas at the base station, often called massive multiple-input multiple-output (MIMO), has drawn considerable interest because of its potential ability to revolutionize current wireless…

Information Theory · Computer Science 2015-06-17 Junil Choi , David J. Love , Patrick Bidigare

Pilot contamination problem in massive MIMO networks operating in time-division duplex (TDD) mode can limit their expected capacity to a great extent. This paper addresses this problem in cosine modulated multitone (CMT) based massive MIMO…

Information Theory · Computer Science 2014-06-20 Arman Farhang , Amir Aminjavaheri , Nicola Marchetti , Linda E. Doyle , Behrouz Farhang-Boroujeny

This paper introduces a hybrid pilot-aided channel estimation technique for mitigating the effect of pilot contamination for the uplink of multi-cell multiuser massive MIMO systems. The proposed hybrid pilot is designed such that it enjoys…

Information Theory · Computer Science 2016-12-23 Jiaming Li , Chau Yuen , Dong Li , Han Zhang , Xianda Wu

In this work we extend the concept of uplink-downlink rate balancing to frequency division duplex (FDD) massive MIMO systems. We consider a base station with large number antennas serving many single antenna users. We first show that any…

Information Theory · Computer Science 2016-05-04 Itsik Bergel , Yona Perets , Shlomo Shamai

This paper proposes and analyzes novel deep learning methods for downlink (DL) single-user multiple-input multiple-output (SU-MIMO) and multi-user MIMO (MU-MIMO) systems operating in time division duplex (TDD) mode. A motivating application…

Information Theory · Computer Science 2024-02-05 Juseong Park , Foad Sohrabi , Amitava Ghosh , Jeffrey G. Andrews

In this paper, we investigate the downlink throughput performance of a massive multiple-input multiple-output (MIMO) system that employs superimposed pilots for channel estimation. The component of downlink (DL) interference that results…

Information Theory · Computer Science 2019-04-16 Karthik Upadhya , Sergiy A. Vorobyov , Mikko Vehkapera

Massive multiple-input multiple-output (MIMO) is one of the key technologies in future generation networks. Owing to their considerable spectral and energy efficiency gains, massive MIMO systems provide the needed performance to cope with…

Information Theory · Computer Science 2017-10-09 Salah Eddine Hajri , Mohamad Assaad , Maialen Larrañaga

For downlink massive multiple-input multiple-output (MIMO) operating in time-division duplex protocol, users can decode the signals effectively by only utilizing the channel statistics as long as channel hardening holds. However, in a…

Information Theory · Computer Science 2022-05-17 Tung T. Vu , Trinh Van Chien , Canh T. Dinh , Hien Quoc Ngo , Michail Matthaiou
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