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The problem of wideband massive MIMO channel estimation is considered. Targeting for low complexity algorithms as well as small training overhead, a compressive sensing (CS) approach is pursued. Unfortunately, due to the Kronecker-type…

Massive multiple-input multiple-output (MIMO) systems require downlink channel state information (CSI) at the base station (BS) to achieve spatial diversity and multiplexing gains. In a frequency division duplex (FDD) multiuser massive MIMO…

信号处理 · 电气工程与系统科学 2020-09-09 Mahdi Boloursaz Mashhadi , Qianqian Yang , Deniz Gunduz

We propose a novel method for massive Multiple-Input Multiple-Output (massive MIMO) in Frequency Division Duplexing (FDD) systems. Due to the large frequency separation between Uplink (UL) and Downlink (DL), in FDD systems channel…

信息论 · 计算机科学 2018-08-28 Mahdi Barzegar Khalilsarai , Saeid Haghighatshoar , Xinping Yi , Giuseppe Caire

A major obstacle for widespread deployment of frequency division duplex (FDD)-based Massive multiple-input multiple-output (MIMO) communications is the large signaling overhead for reporting full downlink (DL) channel state information…

In this paper, we study blind channel-and-signal estimation by exploiting the burst-sparse structure of angular-domain propagation channels in massive MIMO systems. The state-of-the-art approach utilizes the structured channel sparsity by…

信息论 · 计算机科学 2019-09-04 Hang Liu , Xiaojun Yuan , Ying-Jun Angela Zhang

Orthogonal delay-Doppler division multiplexing~(ODDM) modulation has recently been regarded as a promising technology to provide reliable communications in high-mobility situations. Accurate and low-complexity channel estimation is one of…

信号处理 · 电气工程与系统科学 2025-07-29 Dezhi Wang , Chongwen Huang , Xiaojun Yuan , Sami Muhaidat , Lei Liu , Xiaoming Chen , Zhaoyang Zhang , Chau Yuen , Mérouane Debbah

In frequency-division duplex (FDD) massive multiple-input multiple-output (MIMO) systems, the growing number of base station antennas leads to prohibitive feedback overhead for downlink channel state information (CSI). To address this…

信号处理 · 电气工程与系统科学 2024-06-25 Yifan Ma , Hengtao He , Shenghui Song , Jun Zhang , Khaled B. Letaief

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…

信息论 · 计算机科学 2013-10-08 Hien Quoc Ngo , Erik G. Larsson , Thomas L. Marzetta

Channel covariance is emerging as a critical ingredient of the acquisition of instantaneous channel state information (CSI) in multi-user Massive MIMO systems operating in frequency division duplex (FDD) mode. In this context, channel…

信息论 · 计算机科学 2016-02-19 Alexis Decurninge , Maxime Guillaud , Dirk Slock

Low-complexity carrier frequency offset (CFO) estimation and compensation in multi-user massive multiple-input multiple-output (MIMO) systems is a challenging problem. The existing CFO estimation algorithms incur tremendous increase in…

信息论 · 计算机科学 2015-05-05 Sudarshan Mukherjee , Saif Khan Mohammed

In frequency division duplex (FDD) multiple-input multiple-output (MIMO) wireless communication systems, the acquisition of downlink channel state information (CSI) is essential for maximizing spatial resource utilization and improving…

信号处理 · 电气工程与系统科学 2025-04-16 Yiran Guo , Wei Chen , Bo Ai

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…

信息论 · 计算机科学 2015-04-01 Hien Quoc Ngo , Erik G. Larsson

Massive multiple-input multiple-output (MIMO) systems deploying a large number of antennas at the base station considerably increase the spectrum efficiency by serving multiple users simultaneously without causing severe interference.…

信息论 · 计算机科学 2019-02-19 Yu Han , Qi Liu , Chao-Kai Wen , Shi Jin , Kai-Kit Wong

Extremely large-scale multiple-input multiple-output (XL-MIMO) enables the formation of narrow beams, effectively mitigating path loss in high-frequency communications. This capability makes the integration of wideband high-frequency…

信号处理 · 电气工程与系统科学 2025-05-27 Peicong Zheng , Xuantao Lyu , Ye Wang , Yi Gong

This paper considers the transceiver design for uplink massive multiple-input multiple-output (MIMO) systems with channel sparsity in the angular domain. Recent progress has shown that sparsity-learning-based blind signal detection is able…

信息论 · 计算机科学 2019-06-05 Wenjing Yan , Xiaojun Yuan

In a frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) system, the acquisition of downlink channel state information (CSI) at base station (BS) is a very challenging task due to the overwhelming overheads…

信号处理 · 电气工程与系统科学 2019-08-27 Yuwen Yang , Feifei Gao , Geoffrey Ye Li , Mengnan Jian

In this paper, we propose an efficient downlink channel reconstruction scheme for a frequency-division-duplex multi-antenna system by utilizing uplink channel state information combined with limited feedback. Based on the spatial…

信息论 · 计算机科学 2018-05-21 Yu Han , Tien-Hao Hsu , Chao-Kai Wen , Kai-Kit Wong , Shi Jin

To achieve the more promising passive beamforming gains in the double-intelligent reflecting surface (IRS) assisted system over the conventional single-IRS system, channel estimation is practically indispensable but also a more challenging…

信息论 · 计算机科学 2020-10-14 Beixiong Zheng , Changsheng You , Rui Zhang

We consider a multiuser (MU) multiple-input multiple-output (MIMO) time-division duplexing (TDD) system in which the base station (BS) is equipped with a large number of antennas for communicating with single-antenna mobile users. In such a…

信息论 · 计算机科学 2013-12-05 Ko-Feng Chen , Yen-Cheng Liu , Yu T. Su

Downlink channel estimation in massive MIMO systems is well known to generate a large overhead in frequency division duplex (FDD) mode as the amount of training generally scales with the number of transmit antennas. Using instead an…

信息论 · 计算机科学 2019-02-20 François Rottenberg , Rui Wang , Jianzhong Zhang , Andreas F. Molisch