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459 results on '"Imran, Muhammad Ali"'

12. Wireless Microwave Signal Transmission for Cryogenic Applications

Author

Rehman Kazim, Jalil ur, primary, Ali, Muhammad Zulfiqar, additional, Al-Moathin, Ali, additional, Nikbakhtnasrabadi, Fatemeh, additional, Khatri, Prince, additional, Powell, Megan, additional, Stanley, Manoj, additional, Ridler, Nick M., additional, Rossi, Alessandro, additional, Weides, Martin, additional, Heidari, Hadi, additional, Imran, Muhammad Ali, additional, Abbasi, Qammer H., additional, and Li, Chong, additional

Published
2023
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18. Characterization of a Compact Wideband Microwave Metasurface Lens for Cryogenic Applications

Author

Al-Moathin, Ali, primary, Zhong, Mingyan, additional, Al-Taai, Qusay, additional, Jiang, Yunan, additional, Farage, Michael, additional, Kazim, Jalil ur Rehman, additional, Ali, Muhammad Zulfiqar, additional, Nikbakhtnasrabadi, Fatemeh, additional, Powell, Megan, additional, Khatri, Prince, additional, Stanley, Manoj, additional, Rossi, Alessandro, additional, Heidari, Hadi, additional, Imran, Muhammad Ali, additional, Abbasi, Qammer H., additional, Ridler, Nick M., additional, Weides, Martin, additional, and Li, Chong, additional

Published
2023
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38. Energy Management in an Agile Workspace using AI-driven Forecasting and Anomaly Detection

Author

Manzoor, Habib Ullah, Khan, Ahsan Raza, Al-Quraan, Mohammad, Mohjazi, Lina, Taha, Ahmad, Abbas, Hasan, Hussain, Sajjad, Imran, Muhammad Ali, and Zoha, Ahmed

Abstract

Smart building technologies transform buildings into agile, sustainable, and health-conscious ecosystems by leveraging IoT platforms. In this regard, we have developed a Persuasive Energy Conscious Network (PECN) at the University of Glasgow to understand the user-centric energy consumption patterns in an agile workspace. PECN consists of desk-level energy monitoring sensors that enable us to develop user-centric models that can be exploited to characterize the normal energy usage behavior of an office occupant. In this study, we make use of staked long short-term memory (LSTM) to forecast future energy demands. Moreover, we employed statistical techniques to automate the detection of anomalous power consumption patterns. Our experimental results indicate that post-anomaly resolution leads to 6.37% improvement in the forecasting accuracy.

Published
2022

39. Cross-Layer Authentication based on Physical-Layer Signatures for Secure Vehicular Communication

Author

Shawky, Mahmoud A., Abbasi, Qammer H., Imran, Muhammad Ali, Ansari, Shuja, and Taha, Ahmad

Abstract

In recent years, research has focused on exploiting the inherent physical (PHY) characteristics of wireless channels to discriminate between different spatially separated network terminals, mitigating the significant costs of signature-based techniques. In this paper, the legitimacy of the corresponding terminal is firstly verified at the protocol stack’s upper layers, and then the re-authentication process is performed at the PHY-layer. In the latter, a unique PHY-layer signature is created for each transmission based on the spatially and temporally correlated channel attributes within the coherence time interval. As part of the verification process, the PHY-layer signature can be used as a message authentication code to prove the packet’s authenticity. Extensive simulation has shown the capability of the proposed scheme to support high detection probability at small signal-to-noise ratios. In addition, security evaluation is conducted against passive and active attacks. Computation and communication comparisons are performed to demonstrate that the proposed scheme provides superior performance compared to conventional cryptographic approaches.

Published
2022

40. NB-IoT Performance Analysis and Evaluation in Indoor Industrial Environment

Author

Dangana, Muhammad, Ansari, Shuja, Hussain, Sajjad, and Imran, Muhammad Ali

Abstract

Narrow Band Internet of Things (NB-IoT) is one of the drivers of industry 4.0 and the study of its wireless behavior in Indoor industrial environments has become important. This is because of the unfavorable conditions poised to wireless propagation as a result of the presence of heavy-duty equipment and the physical structure of industrial buildings. In this paper, an indoor industry was modeled to present some of the reflective characteristics and its effects on wireless propagation, particularly large-scale fading. The results obtained which include propagation paths, path loss, and impulse response showed how the environment affected the wireless transmission of NB-IoT. However, to mitigate this challenge, a collaborative scheme is introduced to improve the transmission among the affected NB-IoT terminals. The proposed scheme resulted in a collective improvement in path loss value by 30.44%.

Published
2022

41. An adaptive diagonal loading technique to improve direction of arrival estimation accuracy for linear antenna array sensors

Author

Muhammad, Murdifi, Li, Minghui, Abbasi, Qammer H., Goh, Cindy, and Imran, Muhammad Ali

Abstract

Diagonal loading is one of the most widely used and effective methods to improve the robustness of both adaptive beamformers and Direction of Arrival (DOA) estimation due to the involvement of the sensor received covariance matrix. In addition, subspace-based DOA estimation techniques rely on multiple snapshots to achieve high estimation accuracies. This paper presents the study of a modified diagonally loaded sample covariance matrix for accurate DOA estimation in adverse scenarios. The proposed and novel technique deciphers poor DOA estimation in a low SNR environment by computationally changing the received sample covariance matrix. Our method is computationally simple as it does not require peak searching and does not depend on the coherency of the signal. The efficacy of the proposed method is examined via computer simulation for various sensor array sizes and the number of snapshot samples. Based on our numerical simulation results, our proposed method generally outperforms most state-of-the-art DOA estimators. In a finite number of snapshots and a single signal source, our proposed method performs 9.5% better than the state-of-the-art DOA estimation technique, 2.8% in multiple signal sources, and 8.5% in a single snapshot, single signal source environment of gained DOA estimation performance.

Published
2022

42. Wireless Resource Management in Intelligent Semantic Communication Networks

Author

Xia, Le, Sun, Yao, Li, Xiaoqian, Feng, Gang, and Imran, Muhammad Ali

Subjects
Networking and Internet Architecture (cs.NI), Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Networking and Internet Architecture, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing
Abstract

The prosperity of artificial intelligence (AI) has laid a promising paradigm of communication system, i.e., intelligent semantic communication (ISC), where semantic contents, instead of traditional bit sequences, are coded by AI models for efficient communication. Due to the unique demand of background knowledge for semantic recovery, wireless resource management faces new challenges in ISC. In this paper, we address the user association (UA) and bandwidth allocation (BA) problems in an ISC-enabled heterogeneous network (ISC-HetNet). We first introduce the auxiliary knowledge base (KB) into the system model, and develop a new performance metric for the ISC-HetNet, named system throughput in message (STM). Joint optimization of UA and BA is then formulated with the aim of STM maximization subject to KB matching and wireless bandwidth constraints. To this end, we propose a two-stage solution, including a stochastic programming method in the first stage to obtain a deterministic objective with semantic confidence, and a heuristic algorithm in the second stage to reach the optimality of UA and BA. Numerical results show great superiority and reliability of our proposed solution on the STM performance when compared with two baseline algorithms., This work has been accepted for publication by 2022 IEEE International Conference on Computer Communications (INFOCOM). Copyright may be transferred without notice, after which this version may no longer be accessible

Published
2022

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