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See detailTowards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions
Sharma, Shree Krishna UL; Wang, Xianbin

in IEEE Communications Surveys and Tutorials (2019)

The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense ... [more ▼]

The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as enhanced Mobile Broadband (eMBB), massive Machine Type Communications (mMTC) and Ultra-Reliable and Low Latency Communications (URLLC), the mMTC brings the unique technical challenge of supporting a huge number of MTC devices in cellular networks, which is the main focus of this paper. The related challenges include Quality of Service (QoS) provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and Narrowband IoT (NB-IoT). Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenario along with the recent advances towards enhancing its learning performance and convergence. Finally, we discuss some open research challenges and promising future research directions. [less ▲]

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See detailCollaborative Distributed Q-Learning for RACH Congestion Minimization in Cellular IoT Networks
Sharma, Shree Krishna UL; Wang, Xianbin

in IEEE Communications Letters (2019), 23(4), 600-603

Due to infrequent and massive concurrent access requests from the ever-increasing number of machine-type communication (MTC) devices, the existing contention-based random access (RA) protocols, such as ... [more ▼]

Due to infrequent and massive concurrent access requests from the ever-increasing number of machine-type communication (MTC) devices, the existing contention-based random access (RA) protocols, such as slotted ALOHA, suffer from the severe problem of random access channel (RACH) congestion in emerging cellular IoT networks. To address this issue, we propose a novel collaborative distributed Q-learning mechanism for the resource-constrained MTC devices in order to enable them to find unique RA slots for their transmissions so that the number of possible collisions can be significantly reduced. In contrast to the independent Q-learning scheme, the proposed approach utilizes the congestion level of RA slots as the global cost during the learning process and thus can notably lower the learning time for the low-end MTC devices. Our results show that the proposed learning scheme can significantly minimize the RACH congestion in cellular IoT networks. [less ▲]

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See detailQuantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future
Nawaz, Sayed Junaid; Sharma, Shree Krishna UL; Wyne, Shurjeel et al

in IEEE Access (2019)

The upcoming 5th Generation (5G) of wireless networks is expected to lay a foundation of intelligent networks with the provision of some isolated Artificial Intelligence (AI) operations. However, fully ... [more ▼]

The upcoming 5th Generation (5G) of wireless networks is expected to lay a foundation of intelligent networks with the provision of some isolated Artificial Intelligence (AI) operations. However, fully-intelligent network orchestration and management for providing innovative services will only be realized in Beyond 5G (B5G) networks. To this end, we envisage that the 6th Generation (6G) of wireless networks will be driven by on-demand self-reconfiguration to ensure a many-fold increase in the network performanceandservicetypes.Theincreasinglystringentperformancerequirementsofemergingnetworks may finally trigger the deployment of some interesting new technologies such as large intelligent surfaces, electromagnetic-orbital angular momentum, visible light communications and cell-free communications – tonameafew.Ourvisionfor6Gis–amassivelyconnectedcomplexnetworkcapableofrapidlyresponding to the users’ service calls through real-time learning of the network state as described by the network-edge (e.g., base-station locations, cache contents, etc.), air interface (e.g., radio spectrum, propagation channel, etc.), and the user-side (e.g., battery-life, locations, etc.). The multi-state, multi-dimensional nature of the network state, requiring real-time knowledge, can be viewed as a quantum uncertainty problem. In this regard, the emerging paradigms of Machine Learning (ML), Quantum Computing (QC), and Quantum ML (QML) and their synergies with communication networks can be considered as core 6G enablers. Considering these potentials, starting with the 5G target services and enabling technologies, we provide a comprehensivereviewoftherelatedstate-of-the-artinthedomainsofML(includingdeeplearning),QCand QML, and identify their potential benefits, issues and use cases for their applications in the B5G networks. Subsequently,weproposeanovelQC-assistedandQML-basedframeworkfor6Gcommunicationnetworks whilearticulatingitschallengesandpotentialenablingtechnologiesatthenetwork-infrastructure,networkedge, air interface and user-end. Finally, some promising future research directions for the quantum- and QML-assisted B5G networks are identified and discussed. [less ▲]

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See detailEmerging Edge Computing Technologies for Distributed IoT Systems
Alnoman, Ali; Sharma, Shree Krishna UL; Ejaz, Waleed et al

in IEEE Network (2019)

The ever-increasing growth of connected smart devices and Internet of Things (IoT) verticals is leading to the crucial challenges of handling the massive amount of raw data generated by distributed IoT ... [more ▼]

The ever-increasing growth of connected smart devices and Internet of Things (IoT) verticals is leading to the crucial challenges of handling the massive amount of raw data generated by distributed IoT systems and providing timely feedback to the end-users. Although existing cloud computing paradigm has an enormous amount of virtual computing power and storage capacity, it might not be able to satisfy delaysensitive applications since computing tasks are usually processed at the distant cloud-servers. To this end, edge/fog computing has recently emerged as a new computing paradigm that helps to extend cloud functionalities to the network edge. Despite several benefits of edge computing including geo-distribution, mobility support and location awareness, various communication and computing related challenges need to be addressed for future IoT systems. In this regard, this paper provides a comprehensive view on the current issues encountered in distributed IoT systems and effective solutions by classifying them into three main categories, namely, radio and computing resource management, intelligent edge-IoT systems, and flexible infrastructure management. Furthermore, an optimization framework for edge-IoT systems is proposed by considering the key performance metrics including throughput, delay, resource utilization and energy consumption. Finally, a Machine Learning (ML) based case study is presented along with some numerical results to illustrate the significance of ML in edge-IoT computing. [less ▲]

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See detailMargin-based Active Online Learning Techniques for Cooperative Spectrum Sharing in CR Networks
Korrai, Praveenkumar UL; Lagunas, Eva UL; Sharma, Shree Krishna UL et al

in International Conference on Cognitive Radio Oriented Wireless Networks (CROWNCOM), Poznan, Poland, June 2019 (2019)

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See detailDistributed Caching Enabled Peak Traffic Reduction in Ultra-Dense IoT Networks
Sharma, Shree Krishna UL; Wang, Xianbin

in IEEE Communications Letters (2018), 22(6), 1252-1255

The proliferation of massive machine-type communications devices and their random and intermittent transmissions have brought the new challenge of sporadic access-network congestion in ultra-dense ... [more ▼]

The proliferation of massive machine-type communications devices and their random and intermittent transmissions have brought the new challenge of sporadic access-network congestion in ultra-dense Internet of Things (IoT) networks. To address this issue, we propose an innovative approach of peak traffic reduction within the access network by utilizing distributed cache of IoT devices to coordinate their sporadic transmissions. The proposed technique is realized by employing a novel uplink transmission scheduling based on delay adaptation, in which distributed IoT devices adjust their transmission timings by utilizing embedded caching. An optimization problem is formulated for the minimization of peak data rate demand subject to delay tolerance levels, and is solved for the 3GPP-based traffic models by employing a gradient descent-based algorithm. Our results show that the proposed scheme can significantly reduce the peak data traffic in ultra-dense IoT networks. [less ▲]

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See detailSimultaneous Wireless Information and Power Transfer (SWIPT): Recent Advances and Future Challenges
Perera, T. D. Ponnimbaduge; Jayakody, Dushantha Nalin; Sharma, Shree Krishna UL et al

in IEEE Communications Surveys and Tutorials (2018), 20(1), 264-302

Initial efforts on wireless power transfer (WPT) have concentrated toward long-distance transmission and high power applications. Nonetheless, the lower achievable transmission efficiency and potential ... [more ▼]

Initial efforts on wireless power transfer (WPT) have concentrated toward long-distance transmission and high power applications. Nonetheless, the lower achievable transmission efficiency and potential health concerns arising due to high power applications, have caused limitations in their further developments. Due to tremendous energy consumption growth with ever-increasing connected devices, alternative wireless information and power transfer techniques have been important not only for theoretical research but also for the operational costs saving and for the sustainable growth of wireless communications. In this regard, radio frequency energy harvesting (RF-EH) for a wireless communications system presents a new paradigm that allows wireless nodes to recharge their batteries from the RF signals instead of fixed power grids and the traditional energy sources. In this approach, the RF energy is harvested from ambient electromagnetic sources or from the sources that directionally transmit RF energy for EH purposes. Notable research activities and major advances have occurred over the last decade in this direction. Thus, this paper provides a comprehensive survey of the state-of-art techniques, based on advances and open issues presented by simultaneous wireless information and power transfer (SWIPT) and WPT assisted technologies. More specifically, in contrast to the existing works, this paper identifies and provides a detailed description of various potential emerging technologies for the fifth generation communications with SWIPT/WPT. Moreover, we provide some interesting research challenges and recommendations with the objective of stimulating future research in this emerging domain. [less ▲]

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See detailSatellite Communications in the 5G Era
Sharma, Shree Krishna UL; Chatzinotas, Symeon UL; Arapoglou, Pantelis-Daniel

Book published by IET (2018)

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See detailDynamic Spectrum Sharing in 5G Wireless Networks With Full-Duplex Technology: Recent Advances and Research Challenges
Sharma, Shree Krishna UL; Bogale, Tadilo Endeshaw; le, Long Bao et al

in IEEE Communications Surveys and Tutorials (2018), 20(1), 674-707

Full-duplex (FD) wireless technology enables a radio to transmit and receive on the same frequency band at the same time, and it is considered to be one of the candidate technologies for the fifth ... [more ▼]

Full-duplex (FD) wireless technology enables a radio to transmit and receive on the same frequency band at the same time, and it is considered to be one of the candidate technologies for the fifth generation (5G) and beyond wireless communication systems due to its advantages, including potential doubling of the capacity and increased spectrum utilization efficiency. However, one of the main challenges of FD technology is the mitigation of strong self-interference (SI). Recent advances in different SI cancellation techniques, such as antenna cancellation, analog cancellation, and digital cancellation methods, have led to the feasibility of using FD technology in different wireless applications. Among potential applications, one important application area is dynamic spectrum sharing (DSS) in wireless systems particularly 5G networks, where FD can provide several benefits and possibilities such as concurrent sensing and transmission (CST), concurrent transmission and reception, improved sensing efficiency and secondary throughput, and the mitigation of the hidden terminal problem. In this direction, first, starting with a detailed overview of FD-enabled DSS, we provide a comprehensive survey of recent advances in this domain. We then highlight several potential techniques for enabling FD operation in DSS wireless systems. Subsequently, we propose a novel communication framework to enable CST in DSS systems by employing a power control-based SI mitigation scheme and carry out the throughput performance analysis of this proposed framework. Finally, we discuss some open research issues and future directions with the objective of stimulating future research efforts in the emerging FD-enabled DSS wireless systems. [less ▲]

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See detailAnalysis of Power Quality Signals Using An Adaptive Time-Frequency Distribution
Khan, Nabeel A.; Baig, F.; Nawaz, S.J. et al

in Energies (2016)

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See detailUniversal Intelligent Small Cell for Next Generation Cellular Networks
Patwary, M.; Sharma, Shree Krishna UL; Chatzinotas, Symeon UL et al

in Digital Communications and Networks (2016), 2(4), 167174

Exploring innovative cellular architectures to achieve enhanced system capacity and good coverage has become a critical issue towards realizing the next generation of wireless communications. In this ... [more ▼]

Exploring innovative cellular architectures to achieve enhanced system capacity and good coverage has become a critical issue towards realizing the next generation of wireless communications. In this context, this paper proposes a novel concept of Universal Intelligent Small Cell (UnISCell) for enabling the densification of the next generation of cellular networks. The proposed novel concept envisions an integrated platform of providing a strong linkage between different stakeholders such as street lighting networks, landline telephone networks and future wireless networks, and is universal in nature being independent of the operating frequency bands and traffic types. The main motivating factors for the proposed small cell concept are the need of public infrastructure re-engineering, and the recent advances in several enabling technologies. First, we highlight the main concepts of the proposed UnISCell platform. Subsequently, we present two deployment scenarios for the proposed UnISCell concept considering infrastructure sharing and service sharing as important aspects. We then describe the key future technologies for enabling the proposed UnISCell concept and present a use case example with the help of numerical results. Finally, we conclude this article by providing some interesting future recommendations. [less ▲]

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See detailTerminal-side interference mitigation for spectral coexistence of satellite and terrestrial systems in non-exclusive Ka-band
Sharma, Shree Krishna UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in 34th AIAA International Communications Satellite Systems Conference (2016, October)

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See detailCompressed Sensing of Sparse Multipath MIMO Channels with Superimposed Training Sequence
Amin, B.; Mansoor, B.; Junaid Nawaz, S. et al

in Wireless Personal Communications (2016)

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See detailCognitive Interference Management Techniques for the Spectral Co-existence of GSO and NGSO Satellites
Pourmoghaddaslangroudi, Ameneh UL; Sharma, Shree Krishna UL; Chatzinotas, Symeon UL et al

in International Conference on Wireless and Satellite Systems (WiSATS, formerly PSATS), Cardiff, UK, Sep 2016 (2016, September 19)

One of the main challenges in the co-existence of geostationary satellite orbit (GSO) and non-geostationary satellite orbit (NGSO) satellite networks is to mitigate the in-line interference caused by an ... [more ▼]

One of the main challenges in the co-existence of geostationary satellite orbit (GSO) and non-geostationary satellite orbit (NGSO) satellite networks is to mitigate the in-line interference caused by an NGSO satellite to the GSO earth terminal, while the NGSO satellite is crossing the GSO satellite's illumination zone. The method recommended in ITU-R S.1325-3 involves utilizing a range-based power control on the NGSO satellite for downlink communication to the NGSO earth terminals. In this paper, we investigate a cognitive range-based power control algorithm while taking into account the imposed interference level to the GSO fixed satellite service (FSS) system. Results show that the proposed cognitive power control algorithm can mitigate the harmful in-line interference on the GSO terminal receiver, while also providing the desired link quality for the NGSO system. More importantly, we formulate and solve an optimization problem with the objective of minimizing the inter-site distance (ISD) of the GSO-NGSO earth user-terminals. Finally, we develop an analytical method to calculate the ISD between GSO and NGSO earth terminals and validate this with the help of simulation results. [less ▲]

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See detailOn the Performance Analysis of Underlay Cognitive Radio Systems: A Deployment Perspective
Kaushik, A.; Sharma, Shree Krishna UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Cognitive Communications and Networking (2016), 2(3), 273-287

We study the performance of a cognitive underlay system (US) that employs a power control mechanism at the secondary transmitter (ST) from a deployment perspective. Existing baseline models considered for ... [more ▼]

We study the performance of a cognitive underlay system (US) that employs a power control mechanism at the secondary transmitter (ST) from a deployment perspective. Existing baseline models considered for performance analysis either assume the knowledge of involved channels at the ST or retrieve this information by means of a band manager or a feedback channel; however, such situations rarely exist in practice. Motivated by this fact, we propose a novel approach that incorporates estimation of the involved channels at the ST in order to characterize the performance of the US in terms of interference power received at the primary receiver and throughput at the secondary receiver (or secondary throughput). Moreover, we apply an outage constraint that captures the impact of imperfect channel knowledge, particularly on the uncertain interference. Besides this, we employ a transmit power constraint at the ST to classify the operation of the US in terms of an interference-limited regime and a power-limited regime. In addition, we characterize the expressions of the uncertain interference and the secondary throughput for the case where the involved channels encounter Nakagami-m fading. Finally, we investigate a fundamental tradeoff between the estimation time and the secondary throughput depicting an optimized performance of the US. [less ▲]

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See detailPerformance Analysis of Interweave Cognitive Radio Systems with Imperfect Channel Knowledge over Nakagami Fading Channels
Kaushik, A.; Sharma, Shree Krishna UL; Chatzinotas, Symeon UL et al

in 2016 IEEE 84th Vehicular Technology Conference: VTC2016-Fall (2016, September)

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See detailPhysical Layer Aspects of Wireless IoT
Sharma, Shree Krishna UL; Bogale, Tadilo E.; Chatzinotas, Symeon UL et al

in 13th International Symposium on Wireless Communication Systems (2016, September)

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See detailSquare-Law Selector and Square-Law Combiner for Cognitive Radio Systems: An Experimental Study
Rodes, L.; Kaushik, A.; Sharma, Shree Krishna UL et al

in IEEE 84th Vehicular Technology Conference: VTC2016-Fall (2016, September)

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See detailCompressive Sensing Based Energy Detector
Lagunas, Eva UL; Sharma, Shree Krishna UL; Chatzinotas, Symeon UL et al

in European Signal Processing Conference (EUSIPCO) (2016, August)

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See detailPerformance analysis of hybrid cognitive radio systems with imperfect channel knowledge
Kaushik, A.; Sharma, Shree Krishna UL; Chatzinotas, Symeon UL et al

in Communications (ICC), 2016 IEEE International Conference on (2016, July)

In this paper, we study the performance of hybrid cognitive radio systems that combine the benefits of interweave and underlay systems by employing a spectrum sensing and a power control mechanism at the ... [more ▼]

In this paper, we study the performance of hybrid cognitive radio systems that combine the benefits of interweave and underlay systems by employing a spectrum sensing and a power control mechanism at the Secondary Transmitter (ST). Existing baseline models considered for performance analysis assume perfect knowledge of the involved channels at the ST, however, such situations hardly exist in practical deployments. Motivated by this fact, we propose a novel approach that incorporates channel estimation at the ST, and consequently characterizes the performance of Hybrid Systems (HSs) under realistic scenarios. To capture the impact of imperfect channel knowledge, we propose outage constraints on the detection probability at the ST and on the interference power received at the primary receiver. Our analysis reveals that the baseline model overestimates the performance of the HS in terms of achievable secondary user throughput. Finally, based on the proposed estimation-sensing-throughput tradeoff, we determine suitable estimation and sensing durations that effectively capture the effect of imperfect channel knowledge and subsequently enhance the achievable secondary user throughput. [less ▲]

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