| 1. |
- Lundberg, Hampus, et al.
(författare)
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Experimental Analysis of Trustworthy In-Vehicle Intrusion Detection System Using eXplainable Artificial Intelligence (XAI)
- 2022
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Ingår i: IEEE Access. - : Institute of Electrical and Electronics Engineers Inc.. - 2169-3536. ; 10, s. 102831-102841
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Tidskriftsartikel (refereegranskat)abstract
- Anomaly-based In-Vehicle Intrusion Detection System (IV-IDS) is one of the protection mechanisms to detect cyber attacks on automotive vehicles. Using artificial intelligence (AI) for anomaly detection to thwart cyber attacks is promising but suffers from generating false alarms and making decisions that are hard to interpret. Consequently, this issue leads to uncertainty and distrust towards such IDS design unless it can explain its behavior, e.g., by using eXplainable AI (XAI). In this paper, we consider the XAI-powered design of such an IV-IDS using CAN bus data from a public dataset, named 'Survival'. Novel features are engineered, and a Deep Neural Network (DNN) is trained over the dataset. A visualization-based explanation, 'VisExp', is created to explain the behavior of the AI-based IV-IDS, which is evaluated by experts in a survey, in relation to a rule-based explanation. Our results show that experts' trust in the AI-based IV-IDS is significantly increased when they are provided with VisExp (more so than the rule-based explanation). These findings confirm the effect, and by extension the need, of explainability in automated systems, and VisExp, being a source of increased explainability, shows promise in helping involved parties gain trust in such systems.
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| 2. |
- Salehi, Fateme, et al.
(författare)
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Reliable Interference Prediction and Management with Time-Correlated Traffic for URLLC
- 2023
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Ingår i: GLOBECOM 2023 - 2023 IEEE Global Communications Conference. - : IEEE conference proceedings. - 9798350310900 ; , s. 6699-6704
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Konferensbidrag (refereegranskat)abstract
- In designing ultra-reliable low-latency communication (URLLC) services in 5G-and-beyond systems, link adaptation (LA) plays a vital role in adjusting transmission parameters under channel and interference dynamics. Without capturing such dynamics (e.g., relying on average estimates), the LA algorithms fail to simultaneously meet the strict reliability and latency bounds of mission-critical applications. To this end, this paper focuses on interference prediction-based adaptive resource allocation of one-shot URLLC transmission, wherein our solution deviates from the conventional average-based interference estimation schemes. We predict the next interference value based on the interference distribution estimation using a discrete-time Markov chain (DTMC). Further, to exploit the time correlation of each interference source, we model the correlated interference variations as a second-order DTMC to achieve higher prediction accuracy. While accounting for the risk sensitivity of interference estimates, the prediction outcome is then used for appropriate resource allocation of a URLLC transmission under link outage constraints. We evaluate the complete solution, given in the form of an algorithm, using Monte-Carlo simulations, and compare it with the first-order baseline counterpart. The analysis shows that the second-order interference estimate can fulfill the target outage as low as 10-7and improve the outage probability more than ten times in some scenarios compared to the baseline scheme while keeping the same amount of resource usage.
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| 3. |
- Akhtar, Muhammad Waseem, et al.
(författare)
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Exploiting NOMA for Radio Resource Efficient Traffic Steering Use-case in O-RAN
- 2022
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Ingår i: 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings. - : IEEE conference proceedings. - 9781665435406 ; , s. 5771-5776
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Konferensbidrag (refereegranskat)abstract
- In this work, we consider the design of a radio resource management (RRM) solution for traffic steering (TS) use-case in the open radio access network (O-RAN). The O-RAN TS deals with the quality-of-service (QoS)-aware steering of the traffic by connectivity management (e.g., device-to-cell association, radio spectrum, and power allocation) for emerging heterogeneous networks (HetNets) in 5G-and-beyond systems. However, TS in HetNets is a complex problem in terms of efficiently assigning/utilizing the radio resources while satisfying the diverse QoS requirements of especially the cell-edge users due to their poor signal-to-interference-plus-noise ratio (SINR). In this respect, we propose an intelligent non-orthogonal multiple access (NOMA)-based RRM technique for a small cell base station (SBS) within a macro gNB. A Q-learning-assisted algorithm is designed to allocate the transmit power and frequency sub-bands at the O-RAN control layer such that interference from macro gNB to SBS devices is minimized while ensuring the QoS of the maximum number of devices. The numerical results show that the proposed method enhances the overall spectral efficiency of the NOMA-based TS use case without adding to the system's complexity or cost compared to traditional HetNet topologies such as co-channel deployments and dedicated channel deployments.
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| 4. |
- Akhtar, Muhammad Waseem, et al.
(författare)
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Partial NOMA for Semi-Integrated Sensing and Communication
- 2023
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Ingår i: 2023 IEEE Globecom Workshops (GC Wkshps). - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350370218 ; , s. 1129-1134
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Konferensbidrag (refereegranskat)abstract
- This paper proposes a novel partial non-orthogonal multiple access (P-NOMA)-based semi-integrated sensing and communication (ISaC) system design. As an example ISaC scenario, we consider a vehicle simultaneously receiving the communication signal from infrastructure-to-vehicle (I2V) and sensing signal from vehicle-to-vehicle (V2V). P-NOMA allows exploiting both the orthogonal multiple access (OMA) and NOMA schemes for interference reduction and spectral efficiency (SE) enhancement while providing the flexibility of controlling the overlap of the sensing and communication signals according to the channel conditions and priority of the sensing and communication tasks. In this respect, we derive the closed-form expressions for communication outage probability and sensing probability of detection in Nakagami-m fading by considering the interference from the composite sensing channel. Our extensive analysis allows capturing the performance trade-offs of the communication and the sensing tasks with respect to various system parameters such as overlapping partial NOMA parameter, target range, radar cross section (RCS), and parameter m of the Nakagami-m fading channel. Our results show that the proposed P-NOMA-based semi-ISaC system outperforms the benchmark OMA-and NOMA-based systems in terms of communication spectral efficiency and probability of detection for the sensing target.
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| 5. |
- Akhtar, M. W., et al.
(författare)
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Q2A-NOMA : A Q-Learning-based QoS-Aware NOMA System Design for Diverse Data Rate Requirements
- 2022
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Ingår i: IEEE Transactions on Industrial Informatics. - 1551-3203 .- 1941-0050. ; 18:11, s. 7549-7559
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Tidskriftsartikel (refereegranskat)abstract
- Wireless use cases in industrial internet-of-thing (IIoT) networks often require guaranteed data rates ranging from a few kilobits per second to a few gigabits per second. Supporting such a requirement in a single radio access technique is difficult, especially when bandwidth is limited. Although non-orthogonal multiple access (NOMA) can improve the system capacity by simultaneously serving multiple devices, its performance suffers from strong user interference. In this paper, we propose a Q-learning-based algorithm for handling many-to-many matching problems such as bandwidth partitioning, device assignment to sub-bands, interference-aware access mode selection (orthogonal multiple access (OMA), or NOMA), and power allocation to each device. The learning technique maximizes system throughput and spectral efficiency (SE) while maintaining quality-of-service (QoS) for a maximum number of devices. The simulation results show that the proposed technique can significantly increase overall system throughput and SE while meeting heterogeneous QoS criteria.
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| 6. |
- Anjum, M., et al.
(författare)
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A Multi-Level ML-Based Optimization Framework for IIoT Networks with Distributed IRS Assisted UAVs
- 2023
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Ingår i: 2023 IEEE Globecom Workshops (GC Wkshps). - : IEEE conference proceedings. - 9798350370218 ; , s. 1338-1343
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Konferensbidrag (refereegranskat)abstract
- The development of the fifth generation (5G) of cellular systems enables the realization of densely connected, seamlessly integrated, and heterogeneous device networks. While 5G systems were developed to support the Internet of Everything (IoE) paradigm of communication, their mass-scale implementations have excessive capital deployment costs and severely detrimental environmental impacts. Hence, these systems are not feasibly scalable for the envisioned real-time, high-rate, high-reliability, and low-latency requirements of connected consumer, commercial, industrial, healthcare, and environmental processes of the IoE network. The IoE vision is expected to support 30 billion devices by 2030, hence, green communication architectures are critical for the development of next-generation wireless systems. In this context, intelligent reflecting surfaces (IRS) have emerged as a promising disruptive technological advancement that can adjust wireless environments in an energy-efficient manner. This work utilizes and analyzes a multi-node distributed IRS-assisted system in variable channel conditions and resource availability. We then employ machine learning and optimization algorithms for efficient resource allocation and system design of a distributed IRS-enabled industrial Internet of Things (IoT) network. The results show that the proposed data-driven solution is a promising optimization architecture for high-rate, next-generation IoE applications.
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| 7. |
- Anjum, Mahnoor, et al.
(författare)
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Analysis of RSSI Fingerprinting in LoRa Networks
- 2019
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Ingår i: 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC). - : IEEE. - 9781538677476 ; , s. 1178-1183
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Konferensbidrag (refereegranskat)abstract
- Localization has gained great attention in recent years, where different technologies have been utilized to achieve high positioning accuracy. Fingerprinting is a common technique for indoor positioning using short-range radio frequency (RF) technologies such as Bluetooth Low Energy (BLE). In this paper, we investigate the suitability of LoRa (Long Range) technology to implement a positioning system using received signal strength indicator (RSSI) fingerprinting. We test in real line-of-sight (LOS) and non-LOS (NLOS) environments to determine appropriate LoRa packet specifications for an accurate RSSI-to-distance mapping function. To further improve the positioning accuracy, we consider the environmental context. Extensive experiments are conducted to examine the performance of LoRa at different spreading factors. We analyze the path loss exponent and the standard deviation of shadowing in each environment
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| 8. |
- Ansari, Rafay Iqbal, et al.
(författare)
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Control-Data Separation Architecture for Dual-Band mmWave Networks : A New Dimension to Spectrum Management
- 2019
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Ingår i: IEEE Access. - 2169-3536. ; 7, s. 34925-34937
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Tidskriftsartikel (refereegranskat)abstract
- The exponential growth in global mobile data traffic, especially with regards to the massive deployment of devices envisioned for the fifth generation (5G) mobile networks, has given impetus to exploring new spectrum opportunities to support the new traffic demands. The millimeter wave (mmWave) frequency band is considered as a potential candidate for alleviating the spectrum scarcity. Moreover, the concept of multi-tier networks has gained popularity, especially for dense network environments. In this article, we deviate from the conventional multi-tier networks and employ the concept of control-data separation architecture (CDSA), which comprises of a control base station (CBS) overlaying the data base station (DBS). We assume that the CBS operates on the sub-6 GHz single band, while the DBS possesses a dual-band mmWave capability, i.e., 26 GHz unlicensed band and 60 GHz licensed band. We formulate a multi-objective optimization (MOO) problem, which jointly optimizes conflicting objectives: the spectral efficiency (SE) and the energy efficiency (EE). The unique aspect of this work includes the analysis of a joint radio resource allocation algorithm based on Lagrangian Dual Decomposition (LDD) and we compare the proposed algorithm with the maximal-rate (maxRx), dynamic sub-carrier allocation (DSA) and joint power and rate adaptation (JPRA) algorithms to show the performance gains achieved by the proposed algorithm.
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| 9. |
- Aslam, Muhammad Shehryar, et al.
(författare)
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Exploring Multi-Hop LoRa for Green Smart Cities
- 2020
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Ingår i: IEEE Network. - : IEEE Communications Society. - 0890-8044 .- 1558-156X. ; 34:2, s. 225-231
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Tidskriftsartikel (refereegranskat)abstract
- With the growing popularity of Internet-of-Things (IoT)-based smart city applications, various long-range and low-power wireless connectivity solutions are under rigorous research. LoRa is one such solution that works in the sub-GHz unlicensed spectrum and promises to provide long-range communication with minimal energy consumption. However, the conventional LoRa networks are single-hop, with the end devices connected to a central gateway through a direct link, which may be subject to large path loss and hence render low connectivity and coverage. This article motivates the use of multi-hop LoRa topologies to enable energy-efficient connectivity in smart city applications. We present a case study that experimentally evaluates and compares single-hop and multi-hop LoRa topologies in terms of range extension and energy efficiency by evaluating packet reception ratio (PRR) for various source to destination distances, spreading factors (SFs), and transmission powers. The results highlight that a multi-hop LoRa network configuration can save significant energy and enhance coverage. For instance, it is shown that to achieve a 90% PRR, a two-hop network provides 50% energy savings as compared to a single-hop network while increasing 35% coverage at a particular SF. In the end, we discuss open challenges in multi-hop LoRa deployment and optimization.
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| 10. |
- Basharat, Sarah, et al.
(författare)
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Effective Capacity Analysis of Delay-Constrained STAR-RIS Assisted BAC-NOMA Systems
- 2023
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Ingår i: IEEE International Conference on Communications. - : IEEE conference proceedings. - 9781538674628 ; , s. 5793-5798
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Konferensbidrag (refereegranskat)abstract
- Targeting the delay-constrained Internet-of-Things (IoT) applications in sixth-generation (6G) networks, in this paper, we study the integration of simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) and non-orthogonal multiple access-based backscatter communication (BAC-NOMA) under statistical delay quality-of-service (QoS) requirements. In particular, we derive the closed-form expressions for the effective capacity of the STAR-RIS assisted BAC-NOMA system under Nakagami-m fading channels and energy-splitting protocol of STAR-RIS. Our simulation results demonstrate the effectiveness of STAR-RIS over the conventional RIS (C-RIS) and show an excellent correlation with analytical results, validating our analysis. The results reveal that the stringent QoS constraint degrades the effective capacity; however, the system performance can be improved by increasing the STAR-RIS elements and adjusting the energy-splitting coefficients. Finally, we determine the optimal pair of power reflection coefficients subject to the per-BSN effective capacity requirements.
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