no code implementations • 14 May 2024 • Jungyeon Kim, Jinseok Choi, Jeonghun Park, Ahmed Alkhateeb, Namyoon Lee
Utilizing a robust downlink precoding technique, we establish that the proposed downlink channel reconstruction method is sufficient for attaining a sum-spectral efficiency comparable to perfect CSI.
no code implementations • 12 May 2024 • Hao Luo, Ahmed Alkhateeb
Compressive sensing is a promising solution for the channel estimation in multiple-input multiple-output (MIMO) systems with large antenna arrays and constrained hardware.
no code implementations • 1 Apr 2024 • Anıl Gürses, Gautham Reddy, Saad Masrur, Özgür Özdemir, İsmail Güvenç, Mihail L. Sichitiu, Alphan Şahin, Ahmed Alkhateeb, Rudra Dutta
Digital twins (DTs), which are virtual environments that simulate, predict, and optimize the performance of their physical counterparts, are envisioned to be essential technologies for advancing next-generation wireless networks.
no code implementations • 14 Feb 2024 • Jinseok Choi, Jeonghun Park, Namyoon Lee, Ahmed Alkhateeb
In this paper, we present a joint communication and radar beamforming framework for maximizing a sum spectral efficiency (SE) while guaranteeing desired radar performance with imperfect channel state information (CSI) in multi-user and multi-target ISAC systems.
1 code implementation • 29 Jan 2024 • Hao Luo, Ahmed Alkhateeb
In particular, using the RIS as a wireless imaging device, our system constructs the scene depth map of the environment, including the mobile user.
1 code implementation • 18 Jan 2024 • Hao Luo, Umut Demirhan, Ahmed Alkhateeb
Then, we study a joint beamforming design problem with the goal of minimizing the total transmit power while satisfying the tag detection and communication requirements.
no code implementations • 20 Aug 2023 • Tawfik Osman, Gouranga Charan, Ahmed Alkhateeb
The developed solution is evaluated on a real-world multi-modal mmWave V2V communication dataset comprising co-existing 360 camera and mmWave beam training data.
no code implementations • 14 Aug 2023 • Gouranga Charan, Muhammad Alrabeiah, Tawfik Osman, Ahmed Alkhateeb
The solutions developed so far, however, have mainly considered single-candidate scenarios, i. e., scenarios with a single candidate user in the visual scene, and were evaluated using synthetic datasets.
1 code implementation • 3 Aug 2023 • Hao Luo, Umut Demirhan, Ahmed Alkhateeb
Utilizing radar sensing for assisting communication has attracted increasing interest thanks to its potential in dynamic environments.
no code implementations • 20 Jul 2023 • Ian P. Roberts, Yu Zhang, Tawfik Osman, Ahmed Alkhateeb
Noteworthy strides continue to be made in the development of full-duplex millimeter wave (mmWave) communication systems, but most of this progress has been built on theoretical models and validated through simulation.
no code implementations • 18 Jun 2023 • Shuaifeng Jiang, Ahmed Alkhateeb, Daniel W. Bliss, Yu Rong
Radar as a remote sensing technology has been used to analyze human activity for decades.
no code implementations • 26 Jan 2023 • Ahmed Alkhateeb, Shuaifeng Jiang, Gouranga Charan
This article presents a vision where \textit{real-time} digital twins of the physical wireless environments are continuously updated using multi-modal sensing data from the distributed infrastructure and user devices, and are used to make communication and sensing decisions.
no code implementations • 18 Jan 2023 • Shuaifeng Jiang, Ahmed Alkhateeb
To address this challenge, we propose a novel direction that utilizes digital replicas of the physical world to reduce or even eliminate the MIMO channel acquisition overhead.
1 code implementation • 24 Nov 2022 • Shuaifeng Jiang, Ahmed Hindy, Ahmed Alkhateeb
Can reconfigurable intelligent surfaces (RISs) operate in a standalone mode that is completely transparent to the 3GPP 5G initial access process?
no code implementations • 22 Nov 2022 • Sajad Rezaie, João Morais, Ahmed Alkhateeb, Carles Navarro Manchón
However, this design requires a specific model for each user-device beam codebook, where a model learned for a device with a particular codebook can not be reused for another device with a different codebook.
no code implementations • 17 Nov 2022 • Shunyao Wu, Chaitali Chakrabarti, Ahmed Alkhateeb
Given this future blockage prediction capability, the paper also shows that the developed solutions can achieve an order of magnitude saving in network latency, which further highlights the potential of the developed blockage prediction solutions for wireless networks.
no code implementations • 17 Nov 2022 • Ahmed Alkhateeb, Gouranga Charan, Tawfik Osman, Andrew Hredzak, João Morais, Umut Demirhan, Nikhil Srinivas
This article presents the DeepSense 6G dataset, which is a large-scale dataset based on real-world measurements of co-existing multi-modal sensing and communication data.
1 code implementation • 15 Nov 2022 • Abdelrahman Taha, Hao Luo, Ahmed Alkhateeb
In this paper, we propose to employ RIS-aided wireless sensing systems for scene depth estimation.
no code implementations • 14 Nov 2022 • Gouranga Charan, Andrew Hredzak, Ahmed Alkhateeb
Millimeter wave (mmWave) and terahertz (THz) drones have the potential to enable several futuristic applications such as coverage extension, enhanced security monitoring, and disaster management.
no code implementations • 14 Nov 2022 • Shuaifeng Jiang, Ahmed Hindy, Ahmed Alkhateeb
Reconfigurable intelligent surfaces (RISs) have attracted increasing interest due to their ability to improve the coverage, reliability, and energy efficiency of millimeter wave (mmWave) communication systems.
no code implementations • 27 Oct 2022 • Gouranga Charan, Ahmed Alkhateeb
In this paper, we define the \textit{user identification} task as a key enabler for realistic vision-aided communication systems that can operate in crowded scenarios and support multi-user applications.
no code implementations • 15 Sep 2022 • Gouranga Charan, Umut Demirhan, João Morais, Arash Behboodi, Hamed Pezeshki, Ahmed Alkhateeb
In this paper, along with the detailed descriptions of the problem statement and the development dataset, we provide a baseline solution that utilizes the user position data to predict the optimal beam indices.
no code implementations • 9 Sep 2022 • Yu Zhang, Tawfik Osman, Ahmed Alkhateeb
Furthermore, a hardware proof-of-concept prototype based on mmWave phased arrays is built and used to implement and evaluate the developed online beam learning solutions in realistic scenarios.
no code implementations • 3 Aug 2022 • Umut Demirhan, Ahmed Alkhateeb
The article also presents real-world results for some of these machine learning roles based on the large-scale real-world dataset DeepSense 6G, which could be adopted in investigating a wide range of integrated sensing and communication problems.
no code implementations • 23 Jul 2022 • Weihua Xu, Feifei Gao, Xiaoming Tao, Jianhua Zhang, Ahmed Alkhateeb
Visual information, captured for example by cameras, can effectively reflect the sizes and locations of the environmental scattering objects, and thereby can be used to infer communications parameters like propagation directions, receiver powers, as well as the blockage status.
no code implementations • 24 May 2022 • Gouranga Charan, Andrew Hredzak, Christian Stoddard, Benjamin Berrey, Madhav Seth, Hector Nunez, Ahmed Alkhateeb
Millimeter-wave (mmWave) and terahertz (THz) communication systems typically deploy large antenna arrays to guarantee sufficient receive signal power.
1 code implementation • 18 May 2022 • João Morais, Arash Behboodi, Hamed Pezeshki, Ahmed Alkhateeb
Millimeter-wave (mmWave) communication systems rely on narrow beams for achieving sufficient receive signal power.
no code implementations • 22 Mar 2022 • Sajad Rezaie, João Morais, Elisabeth de Carvalho, Ahmed Alkhateeb, Carles Navarro Manchón
While initial beam alignment (BA) in millimeter-wave networks has been thoroughly investigated, most research assumes a simplified terminal model based on uniform linear/planar arrays with isotropic antennas.
no code implementations • 10 Mar 2022 • Shuaifeng Jiang, Gouranga Charan, Ahmed Alkhateeb
A machine learning (ML) model that leverages the LiDAR sensory data to predict the current and future beams was developed.
no code implementations • 3 Mar 2022 • Gouranga Charan, Ahmed Alkhateeb
This paper provides the first real-world evaluation of using visual (RGB camera) data and machine learning for proactively predicting millimeter wave (mmWave) dynamic link blockages before they happen.
no code implementations • 8 Dec 2021 • Tugba Erpek, Yalin E. Sagduyu, Ahmed Alkhateeb, Aylin Yener
This paper presents a novel approach for the joint design of a reconfigurable intelligent surface (RIS) and a transmitter-receiver pair that are trained together as a set of deep neural networks (DNNs) to optimize the end-to-end communication performance at the receiver.
no code implementations • 29 Nov 2021 • Shuaifeng Jiang, Ahmed Alkhateeb
Our proposed approach is evaluated on a large-scale real-world dataset, where it achieves an accuracy of $64. 47\%$ (and a normalized receive power of $97. 66\%$) in predicting the future beam.
no code implementations • 29 Nov 2021 • Umut Demirhan, Ahmed Alkhateeb
The sensitivity of these high-frequency LOS links to blockages, however, challenges the reliability and latency requirements of these communication networks.
no code implementations • 18 Nov 2021 • Shunyao Wu, Chaitali Chakrabarti, Ahmed Alkhateeb
If used for proactive hand-off, the proposed solutions can potentially provide an order of magnitude saving in the network latency, which highlights a promising direction for addressing the blockage challenges in mmWave/sub-THz networks.
no code implementations • 18 Nov 2021 • Umut Demirhan, Ahmed Alkhateeb
This awareness could be utilized to reduce or even eliminate the beam training overhead in millimeter wave (mmWave) and sub-terahertz (THz) MIMO communication systems, which enables a wide range of highly-mobile low-latency applications.
no code implementations • 16 Nov 2021 • Shunyao Wu, Muhammad Alrabeiah, Chaitali Chakrabarti, Ahmed Alkhateeb
In this paper, we propose a novel solution that relies only on in-band mmWave wireless measurements to proactively predict future dynamic line-of-sight (LOS) link blockages.
no code implementations • 15 Nov 2021 • Gouranga Charan, Tawfik Osman, Andrew Hredzak, Ngwe Thawdar, Ahmed Alkhateeb
Enabling highly-mobile millimeter wave (mmWave) and terahertz (THz) wireless communication applications requires overcoming the critical challenges associated with the large antenna arrays deployed at these systems.
no code implementations • 16 Sep 2021 • Georgios C. Trichopoulos, Panagiotis Theofanopoulos, Bharath Kashyap, Aditya Shekhawat, Anuj Modi, Tawfik Osman, Sanjay Kumar, Anand Sengar, Arkajyoti Chang, Ahmed Alkhateeb
These results, among others, draw useful insights into the design and performance of RIS systems and provide an important proof for their potential gains in real-world far-field wireless communication environments.
no code implementations • 18 Mar 2021 • Muhammad Alrabeiah, Umut Demirhan, Andrew Hredzak, Ahmed Alkhateeb
To demonstrate the potential of the proposed framework, a wireless network scenario with two coexisting URLL and eMBB services is considered, and two deep learning algorithms are designed to utilize RGB video frames and predict incoming service type and its request time.
no code implementations • 22 Feb 2021 • Nof Abuzainab, Muhammad Alrabeiah, Ahmed Alkhateeb, Yalin E. Sagduyu
To integrate RISs into THz drone communications, we propose a novel deep learning solution based on a recurrent neural network, namely the Gated Recurrent Unit (GRU), that proactively predicts the serving base station/RIS and the serving beam for each drone based on the prior observations of drone location/beam trajectories.
Information Theory Networking and Internet Architecture Information Theory
1 code implementation • 18 Feb 2021 • Gouranga Charan, Muhammad Alrabeiah, Ahmed Alkhateeb
This paper presents a complete machine learning framework for enabling proaction in wireless networks relying on visual data captured, for example, by RGB cameras deployed at the base stations.
no code implementations • 18 Feb 2021 • Yu Zhang, Muhammad Alrabeiah, Ahmed Alkhateeb
Employing large antenna arrays is a key characteristic of millimeter wave (mmWave) and terahertz communication systems.
no code implementations • 11 Feb 2021 • Abdelrahman Taha, Qi Qu, Sam Alex, Ping Wang, William L. Abbott, Ahmed Alkhateeb
Accounting for the constraints on these systems, we develop a comprehensive framework for constructing accurate and high-resolution depth maps using mmWave systems.
no code implementations • 19 Jan 2021 • Weihua Xu, Feifei Gao, Jianhua Zhang, Xiaoming Tao, Ahmed Alkhateeb
Channel covariance matrix (CCM) is one critical parameter for designing the communications systems.
no code implementations • 18 Jan 2021 • Bo Lin, Feifei Gao, Shun Zhang, Ting Zhou, Ahmed Alkhateeb
A critical bottleneck of massive multiple-input multiple-output (MIMO) system is the huge training overhead caused by downlink transmission, like channel estimation, downlink beamforming and covariance observation.
no code implementations • 18 Jan 2021 • Shunyao Wu, Muhammad Alrabeiah, Andrew Hredzak, Chaitali Chakrabarti, Ahmed Alkhateeb
To evaluate our proposed approach, we build a mmWave communication setup with a moving blockage and collect a dataset of received power sequences.
no code implementations • 18 Jul 2020 • Yuwen Yang, Feifei Gao, Chengwen Xing, Jianping An, Ahmed Alkhateeb
However, the research on MSI aided intelligent communications has not yet explored how to integrate and fuse the multimodal sensory data, which motivates us to develop a systematic framework for wireless communications based on deep multimodal learning (DML).
1 code implementation • 25 Jun 2020 • Muhammad Alrabeiah, Yu Zhang, Ahmed Alkhateeb
To overcome these limitations, this paper develops an efficient online machine learning framework that learns how to adapt the codebook beam patterns to the specific deployment, surrounding environment, user distribution, and hardware characteristics.
no code implementations • 17 Jun 2020 • Gouranga Charan, Muhammad Alrabeiah, Ahmed Alkhateeb
Unlocking the full potential of millimeter-wave and sub-terahertz wireless communication networks hinges on realizing unprecedented low-latency and high-reliability requirements.
1 code implementation • 25 Feb 2020 • Yu Zhang, Muhammad Alrabeiah, Ahmed Alkhateeb
This leads to high beam training overhead and loss in the achievable beamforming gains.
Information Theory Signal Processing Information Theory
1 code implementation • 6 Feb 2020 • Muhammad Alrabeiah, Jayden Booth, Andrew Hredzak, Ahmed Alkhateeb
These capabilities have the potential of reliably supporting highly-mobile applications such as vehicular/drone communications and wireless virtual/augmented reality in mmWave and terahertz systems.
1 code implementation • 27 Dec 2019 • Yuwen Yang, Feifei Gao, Zhimeng Zhong, Bo Ai, Ahmed Alkhateeb
Specifically, we develop the direct-transfer algorithm based on the fully-connected neural network architecture, where the network is trained on the data from all previous environments in the manner of classical deep learning and is then fine-tuned for new environments.
no code implementations • 19 Nov 2019 • Weihua Xu, Feifei Gao, Shi Jin, Ahmed Alkhateeb
In this paper, we present a novel framework of 3D scene based beam selection for mmWave communications that relies only on the environmental data and deep learning techniques.
1 code implementation • 14 Nov 2019 • Muhammad Alrabeiah, Andrew Hredzak, Ahmed Alkhateeb
This paper investigates a novel research direction that leverages vision to help overcome the critical wireless communication challenges.
Information Theory Signal Processing Information Theory
no code implementations • 14 Nov 2019 • Muhammad Alrabeiah, Andrew Hredzak, Zhenhao Liu, Ahmed Alkhateeb
It is developed to be a parametric, systematic, and scalable data generation framework.
1 code implementation • 15 Oct 2019 • Yu Zhang, Muhammad Alrabeiah, Ahmed Alkhateeb
This leads to the interesting, and \textit{counter-intuitive}, observation that when more antennas are employed by the massive MIMO base station, our proposed deep learning approach achieves better channel estimation performance, for the same pilot sequence length.
Information Theory Signal Processing Information Theory
2 code implementations • 7 Oct 2019 • Muhammad Alrabeiah, Ahmed Alkhateeb
Prior work, however, has focused on extracting spatial channel characteristics at the sub-6GHz band first and then use them to reduce the mmWave beam training overhead.
Information Theory Signal Processing Information Theory
1 code implementation • 2 Oct 2019 • Faris B. Mismar, Ahmad AlAmmouri, Ahmed Alkhateeb, Jeffrey G. Andrews, Brian L. Evans
Our proposed classifier-based band switching policy instead exploits spatial and spectral correlation between radio frequency signals in different bands based on knowledge of the UE location.
2 code implementations • 30 May 2019 • Xiaofeng Li, Ahmed Alkhateeb
For example, for a system of 64 transmit and 64 receive antennas, with 3 RF chains at both sides, the proposed solution needs only 8 or 16 channel training pilots to directly predict the RF beamforming/combining vectors of the hybrid architectures and achieve near-optimal achievable rates.
Information Theory Signal Processing Information Theory
1 code implementation • 23 Apr 2019 • Abdelrahman Taha, Muhammad Alrabeiah, Ahmed Alkhateeb
We show that the achievable rates of the proposed compressive sensing and deep learning solutions approach the upper bound, that assumes perfect channel knowledge, with negligible training overhead and with less than 1% of the elements being active.
Information Theory Signal Processing Information Theory
3 code implementations • 18 Feb 2019 • Ahmed Alkhateeb
Second, the DeepMIMO dataset is generic/parameterized as the researcher can adjust a set of system and channel parameters to tailor the generated DeepMIMO dataset for the target machine learning application.
Information Theory Signal Processing Information Theory
no code implementations • 7 Aug 2018 • Xiaofeng Li, Ahmed Alkhateeb, Cihan Tepedelenlioğlu
Enabling highly-mobile millimeter wave (mmWave) systems is challenging because of the huge training overhead associated with acquiring the channel knowledge or designing the narrow beams.
Information Theory Information Theory