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相关论文: Two-stage Method for Millimeter Wave Channel Estim…

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To develop a low-complexity multicast beamforming method for millimeter wave communications, we first propose a channel gain estimation method in this article. We use the beam sweeping to find the best codeword and its two neighboring…

信号处理 · 电气工程与系统科学 2022-03-15 Zhaohui Li , Chenhao Qi , Geoffrey Ye Li

This paper considers a wideband millimeter-wave MIMO system with fully digital transceivers at both the base station and the user equipment (UE), focusing on mobile scenarios. To reduce the baseband processing burden at the UE, we propose a…

信号处理 · 电气工程与系统科学 2026-03-30 Yasaman Khorsandmanesh , Emil Bjornson , Joakim Jalden , Bengt Lindoff

Millimeter Wave (mmWave) massive Multiple Input Multiple Output (MIMO) systems realizing directive beamforming require reliable estimation of the wireless propagation channel. However, mmWave channels are characterized by high variability…

信息论 · 计算机科学 2019-06-07 Evangelos Vlachos , George C. Alexandropoulos , John Thompson

This paper develops efficient channel estimation techniques for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems under practical hardware limitations, including an arbitrary array geometry and a hybrid hardware…

信号处理 · 电气工程与系统科学 2019-10-23 Yue Wang , Yu Zhang , Zhi Tian , Geert Leus , Gong Zhang

The problem of MIMO channel estimation at millimeter wave frequencies, both in a single-user and in a multi-user setting, is tackled in this paper. Using a subspace approach, we develop a protocol enabling the estimation of the right (resp.…

信息论 · 计算机科学 2019-06-24 Stefano Buzzi , Carmen D'Andrea

Millimeter-wave (mmWave) communications plays an important role for future cellular networks because of the vast amount of spectrum available in the underutilized mmWave frequency bands. To overcome the huge free space omnidirectional path…

信息论 · 计算机科学 2017-06-16 Wolfgang Utschick , Christoph Stöckle , Michael Joham , Jian Luo

We develop a two-stage deep learning pipeline architecture to estimate the uplink massive MIMO channel with one-bit ADCs. This deep learning pipeline is composed of two separate generative deep learning models. The first one is a supervised…

信号处理 · 电气工程与系统科学 2019-12-02 Eren Balevi , Jeffrey G. Andrews

Millimeter-wave (mm-Wave) cellular systems are a promising option for a very high data rate communication because of the large bandwidth available at mm-Wave frequencies. Due to the large path-loss exponent in the mm-Wave range of the…

信息论 · 计算机科学 2015-11-06 Saeid Haghighatshoar , Giuseppe Caire

In the conventional multiuser MIMO systems, user selection and scheduling has previously been used as an effective way to increase the sum rate performance of the system. However, the recent concepts of the massive MIMO systems (at…

信息论 · 计算机科学 2016-11-29 Waqas Ahmad , Geamel Alyami , Ivica Kostanic

This paper tackles the challenge of wideband MIMO channel estimation within indoor millimeter-wave scenarios. Our proposed approach exploits the integrated sensing and communication paradigm, where sensing information aids in channel…

信号处理 · 电气工程与系统科学 2023-09-27 Silvia Mura , Marouan Mizmizi , Umberto Spagnolini , Athina Petropulu

In this paper, we develop a low-complexity channel estimation for hybrid millimeter wave (mmWave) systems, where the number of radio frequency (RF) chains is much less than the number of antennas equipped at each transceiver. The proposed…

信息论 · 计算机科学 2017-02-28 Lou Zhao , Derrick Wing Kwan Ng , Jinhong Yuan

The speed at which millimeter-Wave (mmWave) channel estimation can be carried out is critical for the adoption of mmWave technologies. This is particularly crucial because mmWave transceivers are equipped with large antenna arrays to combat…

信息论 · 计算机科学 2021-04-12 Yahia Shabara , Eylem Ekici , C. Emre Koksal

Configuring the hybrid precoders and combiners in a millimeter wave (mmWave) multiuser (MU) multiple-input multiple-output (MIMO) system is challenging in frequency selective channels. In this paper, we develop a system that uses…

Millimeter-wave (mmWave) channels, which occupy frequency ranges much higher than those being used in previous wireless communications systems, are utilized to meet the increased throughput requirements that come with 5G communications. The…

信号处理 · 电气工程与系统科学 2023-02-16 Esen Özbay

Channel estimation for millimeter-wave (mmWave) massive MIMO with hybrid precoding is challenging, since the number of radio frequency (RF) chains is usually much smaller than that of antennas. To date, several channel estimation schemes…

信息论 · 计算机科学 2023-10-20 Zhen Gao , Linglong Dai , Chen Hu , Zhaocheng Wang

In this paper, a two-stage channel estimation scheme for two-way MIMO relay systems with a single relay antenna is proposed. The backward channel is estimated by using linear minimum mean square estimator (LMMSE) at the first stage, where…

信息论 · 计算机科学 2021-12-15 Huiming Chen , Xiaohan Zhong

Channel estimation is useful in millimeter wave (mmWave) MIMO communication systems. Channel state information allows optimized designs of precoders and combiners under different metrics such as mutual information or…

In mmWave massive multiple-input multiple-output (mMIMO) systems, hybrid digital/analog beamforming has been recognized as an economic means to overcome the severe mmWave propagation loss. To facilitate beamforming for mmWace mMIMO, there…

信号处理 · 电气工程与系统科学 2019-12-19 Shijian Gao , Xiang Cheng , Liuqing Yang

Fast channel estimation in millimeter-wave (mmWave) systems is a fundamental enabler of high-gain beamforming, which boosts coverage and capacity. The channel estimation stage typically involves an initial beam training process where a…

信息论 · 计算机科学 2021-04-06 Sandra Roger , Maximo Cobos , Carmen Botella-Mascarell , Gabor Fodor

In this work, we address the problem of channel estimation and precoding / combining for the so-called hybrid millimeter wave (mmWave) MIMO architecture. Our proposed channel estimation scheme exploits channel reciprocity in TDD MIMO…

信息论 · 计算机科学 2016-11-15 Hadi Ghauch , Mats Bengtsson , Taejoon Kim , Mikael Skoglund