| 1. |
- Al-Hraishawi, Hayder, et al.
(författare)
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Energy Harvesting from Jamming Attacks in Multi-User Massive MIMO Networks
- 2023
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Ingår i: IEEE Transactions on Green Communications and Networking. - : Institute of Electrical and Electronics Engineers (IEEE). - 2473-2400. ; 7:3, s. 1181-1191
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Tidskriftsartikel (refereegranskat)abstract
- Fifth-generation (5G) and beyond communication systems offer new functionalities and significant performance improvements but that comes at the cost of tougher energy requirements on user devices. Addressing this issue while reducing the environmental impact of the substantial increase in energy consumption can be achieved through energy-neutral systems that operate using energy harvested from radio frequency (RF) transmissions. In this direction, this work examines the concept of utilizing an unconventional source for RF energy harvesting. Specifically, the performance of an RF energy harvesting scheme for multi-user massive multiple-input multiple-output (MIMO) is investigated in the presence of multiple active jammers. The key idea is to exploit the jamming transmissions as an energy source to be harvested by the legitimate users. To this end, the feasibility of this concept is studied via system performance analysis for a training-based massive MIMO encompasses imperfectly estimated channel state information (CSI) at the base-station and employing the time-switching protocol. In particular, the achievable uplink sum rate expressions are derived in closed-form for two different antenna configurations at the base-station. Two optimal time-switching schemes are also proposed based on maximum sum rate and user-fairness criteria. The essential trade-off between the harvested energy and achievable sum rate in time-switching protocol are quantified in closed-form as well. Our analysis reveals that the proposed energy harvesting scheme from jamming signals is viable and can boost massive MIMO uplink performance by exploiting the surrounding RF signals of the jamming attacks for increasing the amount of harvested energy at the served users. Finally, numerical results validate the theoretical analyses and the effectiveness of the derived closed-form expressions through simulations.
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| 2. |
- Alabbasi, Abdulrahman, et al.
(författare)
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Optimal Processing Allocation to Minimize Energy and Bandwidth Consumption in Hybrid CRAN
- 2018
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Ingår i: IEEE Transactions on Green Communications and Networking. - : Institute of Electrical and Electronics Engineers (IEEE). - 2473-2400. ; 2:2, s. 545-555
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Tidskriftsartikel (refereegranskat)abstract
- Cloud radio access network (CRAN) architecture is proposed to save energy, facilitate coordination between radio units, and achieve scalable solutions to improve radio network's performance. However, stringent delay and bandwidth constraints are incurred by fronthaul in CRAN [the network segment connecting RUs and digital units (DUs)]. Therefore, we propose a hybrid cloud radio access network architecture, where a DU's functionalities can be virtualized and split at several conceivable points. Each split option results in two-level deployment of the processing functions (central site level and remote site level) connected by a transport network, called midhaul. We study the interplay of energy efficiency and midhaul bandwidth consumption under optimal processing allocation. We jointly minimize the power and midhaul bandwidth consumption in H-CRAN, while satisfying network constraints, i.e., processing and midhaul bandwidth capacity. We enable power saving functionalities by shutting down different network components. The proposed model is formulated as a constraint programming problem. The proposed solution shows that 42 percentile of midhaul bandwidth savings can be achieved compared to the fully centralized CRAN; and 35 percentile of power consumption saving can be achieved compared to the case where all the network functions are distributed at the edge.
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| 3. |
- Allipuram, Sujatha, et al.
(författare)
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Performance Analysis of a MIMO System With Bursty Traffic in the Presence of Energy Harvesting Jammer
- 2022
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Ingår i: IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2473-2400. ; 6:2, s. 1157-1172
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Tidskriftsartikel (refereegranskat)abstract
- This paper explores the role of multiple antennas in mitigating jamming attacks for the Rayleigh fading environment with exogenous random traffic arrival. The jammer is assumed to have energy harvesting ability where energy arrives according to Bernoulli process. The outage probabilities are derived with different assumptions on the number of antennas at the transmitter and receiver. The outage probability for the Alamouti space-time code is also derived. The work characterizes the average service rate for different antenna configurations taking into account of random arrival of data and energy at the transmitter and jammer, respectively. In many practical applications, latency and timely updates are of importance, thus, delay and Average Age of Information (AAoI) are the meaningful metrics to be considered. The work characterizes these metrics under jamming attack. The impact of finite and infinite energy battery size at the jammer on various performance metrics is also explored. Two optimization problems are considered to explore the interplay between AAoI and delay under jamming attack. Furthermore, our results show that Alamouti code can significantly improve the performance of the system even under jamming attack, with less power budget. The paper also demonstrates how the developed results can be useful for multiuser scenarios.
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| 4. |
- Azari, Amin, 1988-, et al.
(författare)
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Energy and Resource Efficiency by User Traffic Prediction and Classification in Cellular Networks
- 2022
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Ingår i: IEEE Transactions on Green Communications and Networking. - : Institute of Electrical and Electronics Engineers (IEEE). - 2473-2400. ; 6:2, s. 1082-1095
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Tidskriftsartikel (refereegranskat)abstract
- There is a lack of research on the analysis of peruser traffic in cellular networks, for deriving and following traffic-aware network management. In fact, the legacy design approach, in which resource provisioning and operation control are performed based on the cell-aggregated traffic scenarios, are not so energy- and cost-efficient and need to be substituted with user-centric predictive analysis of mobile network traffic and proactive network resource management. Here, we shed light on this problem by designing traffic prediction tools that utilize standard machine learning (ML) tools, including long shortterm memory (LSTM) and autoregressive integrated moving average (ARIMA) on top of per-user data. We present an expansive empirical evaluation of the designed solutions over a real network traffic dataset. Within this analysis, the impact of different parameters, such as the time granularity, the length of future predictions, and feature selection are investigated. As a potential application of these solutions, we present an ML-powered Discontinuous reception (DRX) scheme for energy saving. Towards this end, we leverage the derived ML models for dynamic DRX parameter adaptation to user traffic. The performance evaluation results demonstrate the superiority of LSTM over ARIMA in general, especially when the length of the training time series is high enough, and it is augmented by a wisely-selected set of features. Furthermore, the results show that adaptation of DRX parameters by online prediction of future traffic provides much more energy-saving at low latency cost in comparison with the legacy cell-wide DRX parameter adaptation.
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| 5. |
- 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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| 6. |
- Azari, Amin, 1988-, et al.
(författare)
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On the Latency-Energy Performance of NB-IoT Systems in Providing Wide-Area IoT Connectivity
- 2019
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Ingår i: IEEE Transactions on Green Communications and Networking. - 2473-2400.
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Tidskriftsartikel (refereegranskat)abstract
- Narrowband Internet-of-Things (NB-IoT) offers a significant link budget improvement in comparison with the legacy networks by introducing different coverage classes, allowing repeated transmissions, and tuning the repetition order based on the path-loss in communications. However, those repetitions necessarily increase energy consumption and latency in the whole NB-IoT system. The extent to which the whole system is affected depends on the scheduling of the uplink and downlink channels. We address this question, not treated previously, by developing a tractable model of NB-IoT connectivity, comprising message exchanges in random-access, control, and data channels. The model is then used to analyze the impact of channel scheduling and interaction of coverage classes on the performance of IoT devices through the derivation of the expected latency and battery lifetime. These results are subsequently employed in determining the optimized operation points, i.e., (i) scheduling of data and control channels for a given set of users and respective coverage classes, or (ii) determining the optimal set of coverage classes and served users per coverage class for a given scheduling strategy. Simulations results show the validity of the analysis and confirm that channel scheduling and coexistence of coverage classes significantly affect latency and battery lifetime performance of NB-IoT devices.
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| 7. |
- Bashar, Manijeh, et al.
(författare)
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Energy Efficiency of the Cell-Free Massive MIMO Uplink with Optimal Uniform Quantization
- 2019
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Ingår i: IEEE Transactions on Green Communications and Networking. - : IEEE. - 2473-2400. ; 3:4, s. 971-987
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Tidskriftsartikel (refereegranskat)abstract
- A cell-free Massive multiple-input multiple-output (MIMO) uplink is considered, where the access points (APs) are connected to a central processing unit (CPU) through limited-capacity wireless microwave links. The quantized version of the weighted signals are available at the CPU, by exploiting the Bussgang decomposition to model the effect of quantization. A closed-form expression for spectral efficiency is derived taking into account the effects of channel estimation error and quantization distortion. The energy efficiency maximization problem is considered with per-user power, backhaul capacity and throughput requirement constraints. To solve this non-convex problem, we decouple the original problem into two sub-problems, namely, receiver filter coefficient design, and power allocation. The receiver filter coefficient design is formulated as a generalized eigenvalue problem whereas a successive convex approximation (SCA) and a heuristic sub-optimal scheme are exploited to convert the power allocation problem into a standard geometric programming (GP) problem. An iterative algorithm is proposed to alternately solve each sub-problem. Complexity analysis and convergence of the proposed schemes are investigated. Numerical results indicate the superiority of the proposed algorithms over the case of equal power allocation.
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| 8. |
- Biswas, Sinchan, 1988-, et al.
(författare)
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On Optimal Quantized Non-Bayesian Quickest Change Detection with Energy Harvesting
- 2020
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Ingår i: IEEE Transactions on Green Communications and Networking. - : Institute of Electrical and Electronics Engineers (IEEE). - 2473-2400. ; 4:2, s. 433-447
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- In this paper, we consider a problem of decentralized non-Bayesian quickest change detection using a wireless sensor network where the sensor nodes are powered by harvested energy from the environment. The underlying random process being monitored by the sensors is subject to change in its distribution at an unknown but deterministic time point and the sensors take samples (sensing) periodically, compute the likelihood ratio based on the distributions before and after the change, quantize it and send it to a remote fusion centre (FC) over fading channels for performing a sequential test to detect the change. Due to the unpredictable and intermittent nature of harvested energy arrivals, the sensors need to decide whether they want to sense, and at what rate they want to quantize their information before sending them to the FC, since higher quantization rates result in higher accuracy and better detection performance, at the cost of higher energy consumption. We formulate an optimal sensing and quantization rate allocation problem (in order to minimize the expected detection delay subject to false alarm rate constraint) based on the availability (at the FC) of non-causal and causal information of sensors’ energy state information, and channel state information between the sensors and the FC. Motivated by the asymptotically inverse relationship between the expected detection delay (under a vanishingly small probability of false alarm) and the Kullback-Leibler (KL) divergence measure at the FC, we maximize an expected sum of the KL divergence measure over a finite horizon to obtain the optimal sensing and quantization rate allocation policy, subject to energy causality constraints at each sensor. The optimal solution is obtained using a typical dynamic programming based technique, and based on the optimal quantization rate, the optimal quantization thresholds are found by maximizing the KL information measure per slot. We also provide suboptimal threshold design policies using uniform quantization and an asymptotically optimal quantization policy for higher number of quantization bits. We provide an asymptotic approximation for the loss due to quantization of the KL measure, and also consider an alternative optimization problem with minimizing the expected sum of the inverse the KL divergence measure as the cost per time slot. Numerical results are provided comparing the various optimal and suboptimal quantization strategies for both optimization problem formulations, illustrating the comparative performance of these strategies at different regimes of quantization rates.
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| 9. |
- Chang, Z., et al.
(författare)
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Energy-Efficient and Secure Resource Allocation for Multiple-Antenna NOMA With Wireless Power Transfer
- 2018
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Ingår i: IEEE Transactions on Green Communications and Networking. - 2473-2400. ; 2:4, s. 1059-1071
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Tidskriftsartikel (refereegranskat)abstract
- Non-orthogonal multiple access (NOMA) is considered as one of the promising techniques for providing high data rates in the fifth generation mobile communication. By applying successive interference cancellation schemes and superposition coding at the NOMA receiver, multiple users can be multiplexed on the same subchannel. In this paper, we investigate resource allocation algorithm design for an OFDM-based NOMA system empowered by wireless power transfer (WPT). In the considered system, users who need to transmit data can only be powered by the WPT. With the consideration of an existing eavesdropper, the objective is to obtain secure and energy efficient transmission among multiple users by optimizing time, power and subchannel allocation. Moreover, we also take into consideration for the practical case that the statistics of the channel state information of the eavesdropper is not available. In order to address the optimization problem and its high computational complexity, we propose an iterative algorithm with guaranteed convergence to deliver an upper bound and a suboptimal solution in more general cases. For some special cases, we identify the optimality condition that ensures the global optimum in our algorithm. Extensive simulation studies demonstrate the competitiveness and effectiveness of the proposed algorithmic solution over conventional OFDMA systems as well as over other existing NOMA resource allocation schemes.
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| 10. |
- Chen, Zheng, et al.
(författare)
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Dynamic Resource Allocation in Co-Located and Cell-Free Massive MIMO
- 2020
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Ingår i: IEEE Transactions on Green Communications and Networking. - : IEEE. - 2473-2400. ; 4:1, s. 209-220
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we study joint power control and scheduling in uplink massive multiple-input-multiple-output (MIMO) systems with randomly arriving data traffic. We consider both co-located and Cell-Free (CF) Massive MIMO, where the difference lies in whether the antennas are co-located at the base station or spread over a wide network area. The data is generated at each user according to an individual stochastic process. Using Lyapunov optimization techniques, we develop a dynamic scheduling algorithm (DSA), which decides at each time slot the amount of data to admit to the transmission queues and the transmission rates over the wireless channel. The proposed algorithm optimizes the long-term user throughput under various fairness policies while keeping the transmission queues stable. Simulation results show that the state-of-the-art power control schemes developed for Massive MIMO with infinite backlogs can fail to stabilize the system even when the data arrival rates are within the network capacity region. Our proposed DSA shows advantage in providing finite delay with performance optimization whenever the network can be stabilized. © 2017 IEEE.
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