| 1. |
- Azari, Amin, et al.
(författare)
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Energy-Efficient and Reliable IoT Access Without Radio Resource Reservation
- 2021
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Ingår i: IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING. - : Institute of Electrical and Electronics Engineers (IEEE). - 2473-2400. ; 5:2, s. 908-920
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Tidskriftsartikel (refereegranskat)abstract
- One of the major challenges for Internet-of-Things applications is that the existing cellular technologies do not support the uplink IoT traffic in an energy-efficient manner. There are two principal ways for serving the uplink IoT traffic: grant-based (i.e., scheduled) and grant-free (i.e., random access). Grant-based access provides fine-grained control of reliability and latency at the cost of energy consumption required for signaling. Grant-free access removes the signaling overhead at the cost of looser control of performance in terms of reliability and latency. However, a precise analysis of reliability, latency and energy performance of grant-free access (GFA) is largely missing. This article focuses on a GFA-type protocol, in which a device transmits several packet replicas, asynchronously with respect to the other devices. Using stochastic geometry, we derive closed-form expressions for reliability, delay, and energy consumption, which can be used to identify the tradeoffs among these performance parameters. In order to improve the performance of the protocol, we develop a receiver that leverages the random timing and frequency offsets among the devices in order to facilitate resolution of collisions. This is complemented by a per-device adaptive scheme that controls the number of transmitted replicas. The evaluation confirms the validity of the analysis and the potential of the proposed solution, identifying operating regions in which GFA outperforms the grant-based access.
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| 2. |
- Azari, Amin, 1988-, et al.
(författare)
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Reliable and Energy-Efficient IoT Systems : Design Considerations in Coexistence Deployments
- 2023
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Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537. ; 20:3, s. 2412-2427
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Tidskriftsartikel (refereegranskat)abstract
- Currently, there is a plethora of low-power wide-area IoT networking solutions available, each targeting a specific niche of use-cases and deployment scenarios. Existing studies on reliability evaluations of IoT solutions rely on the assumption that a single technology is deployed in the service area, or different IoT technologies operate over dedicated spectrum bands. Here, we investigate the reliability performance of IoT communications in coexisting scenarios, where multiple competing radio-access technologies share spectrum resources. Our focus is on solutions exploiting grant-free communications, which are gaining traction due to their potential to lower the energy consumption, and have been adopted in recent IoT technologies like SigFox and LoRa. We first derive an analytical model of the interference, comprising both inter- and intra-technology interference sources. We then leverage the Poisson Cluster Process for modeling distribution of devices in the service area, and derive expressions for the communication reliability, energy consumption, and battery lifetime of IoT devices. Exploiting these expressions, we study the energy-reliability trade-offs and investigate strategies to maintain or improve communication reliability, while minimizing energy consumption in coexisting scenarios by proper adjustment of communications parameters at the device side and provisioning resources at the network side. We verify the analytical results via numerical evaluations, confirming their accuracy and performing optimization in some example networking setups.
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| 3. |
- Farag, Hossam, et al.
(författare)
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A Deep Reinforcement Learning Approach for Improving Age of Information in Mission-Critical IoT
- 2021
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Ingår i: The 2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT) - 2021 IEEE GCAIoT. - : IEEE. ; , s. 14-18
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Konferensbidrag (refereegranskat)abstract
- The emerging mission-critical Internet of Things (IoT) play a vital role in remote healthcare, haptic interaction, and industrial automation, where timely delivery of status updates is crucial. The Age of Information (AoI) metric is introduced as an effective criterion for evaluating the freshness of information received at the destination. A system design based solely on the optimization of the average AoI might not be adequate to capture the requirements of mission-critical applications, since averaging eliminates the effects of extreme events. In this paper, we introduce a Deep Reinforcement Learning (DRL)-based algorithm to improve AoI in mission-critical IoT applications. The objective is to minimize an AoI-based metric consisting of the weighted sum of the average AoI and the probability of exceeding an AoI threshold. We utilize the actor-critic method to train the algorithm to achieve optimized scheduling policy to solve the formulated problem. The performance of our proposed method is evaluated in a simulated setup and the results show a significant improvement in terms of the average AoI and the AoI violation probability compared to the related-work.
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| 4. |
- Farag, Hossam, et al.
(författare)
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Distributed Backlog-Aware Protocol for Heterogeneous D2D Communication-Assisted Wireless Sensor Networks
- 2024
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Ingår i: IEEE Transactions on Mobile Computing. - : IEEE. - 1536-1233 .- 1558-0660. ; 23:5, s. 3981-3992
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Tidskriftsartikel (refereegranskat)abstract
- Age of Information (AoI) and delay are crucial performance metrics for Industrial Internet of Things (IIoT) applications not only to perform seamless actuation and control actions but also to enable self-organized and re-configurable manufacturing systems. A challenging task in heterogeneous IIoT networks is to minimize the AoI while maintaining a predefined delay constraint. In this work, we consider a Device-to-Device (D2D)-based heterogeneous IIoT network that supports two types of traffic flows, namely AoI-sensitive flow and delay-sensitive flow. First, we introduce a distributed backlog-aware random access protocol that allows the AoI-sensitive nodes to opportunistically access the channel based on the queue occupancy of the delay-sensitive node. Then, we develop an analytical framework to evaluate the average delay and the average AoI, and formulate an optimization problem to minimize the AoI under a given delay constraint. Finally, we provide numerical results to demonstrate the impact of different network parameters on the performance in terms of the average delay and the average AoI. We also give numerical solutions of the optimal parameters that minimize the AoI subject to a defined delay constraint.
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| 5. |
- Graell I Amat, Alexandre, 1976, et al.
(författare)
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Coded Slotted Aloha with Stopping Set Resolution: A Group Testing Approach
- 2022
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Ingår i: Conference Record - Asilomar Conference on Signals, Systems and Computers. - 1058-6393. ; 2022-October, s. 677-681
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Konferensbidrag (refereegranskat)abstract
- In this work, we explore the use of group testing techniques to steer a collision resolution phase in the context of coded slotted Aloha protocols. The problem can be defined as the discovery of stopping sets based on the residual collision pattern after successive interference cancellation decoding. We show how the application of the simple combinatorial orthogonal matching pursuit algorithm is sufficient to resolve a large number of the collisions that hinder the success of the iterative interference cancellation process. We highlight the design choices that have to be addressed to benefit from the proposed approach. Finally, we outline a few interesting directions for future developments.
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| 6. |
- Khodakhah, Farnaz, et al.
(författare)
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NOMA or Puncturing for Uplink eMBB-URLLC Coexistence from an AoI Perspective?
- 2023
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Ingår i: GLOBECOM 2023 - 2023 IEEE Global Communications Conference. - : IEEE. - 9798350310900 ; , s. 4301-4306
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Konferensbidrag (refereegranskat)abstract
- Through the lens of the age-of-information (AoI) metric, this paper takes a fresh look into the performance of coexisting enhanced mobile broadband (eMBB) and ultra-reliable low-latency (URLLC) services in the uplink scenario. To reduce AoI, a URLLC user with stochastic packet arrivals has two options: orthogonal multiple access (OMA) with the preemption of the eMBB user (labeled as puncturing) or non-orthogonal multiple access (NOMA) with the ongoing eMBB transmission. Puncturing leads to lower average AoI at the expense of the decrease in the eMBB user's rate, as well as in signaling complexity. On the other hand, NOMA can provide a higher eMBB rate at the expense of URLLC packet loss due to interference and, thus, the degradation in AoI performance. We study under which conditions NOMA could provide an average AoI performance that is close to the one of the puncturing, while maintaining the gain in the data rate. To this end, we derive a closed-form expression for the average AoI and investigate conditions on the eMBB and URLLC distances from the base station at which the difference between the average AoI in NOMA and in puncturing is within some small gap β. Our results show that with β as small as 0.1 minislot, the eMBB rate in NOMA can be roughly 5 times higher than that of puncturing. Thus, by choosing an appropriate access scheme, both the favorable average AoI for URLLC users and the high data rate for eMBB users can be achieved.
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