Dynamic Spectrum Reservation for CR Networks in the Presence of Channel Failures: Channel Allocation and Reliability Analysis

(c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this[EN] Providing channel access opportunities for new service requests and guaranteeing continuous connections for ongoing flows until service completion are two challenges for service provisioning in wireless networks. Channel failures, which are typically caused by hardware and software failures or/and by intrinsic instability in radio transmissions, can easily result in network performance degradation. In cognitive radio networks (CRNs), secondary transmissions are inherently vulnerable to connection breaks due to licensed users' arrivals as well as channel failures. To explore the advantages of channel reservation on performance improvement in error-prone channels, we propose and analyze a dynamic channel reservation (DCR) algorithm and a dynamic spectrum access (DSA) scheme with three access privilege variations. The key idea of the DCR algorithm is to reserve a dynamically adjustable number of channels for the interrupted services to maintain service retainability for ongoing users or to enhance channel availability for new users. Furthermore, the DCR algorithm is embedded in the DSA scheme enabling spectrum access of primary and secondary users with different access privileges based on access flexibility for licensed shared access. The performance of such a CRN in the presence of homogeneous and heterogeneous channel failures is investigated considering different channel failure and repair rates.The work of V. Pla was supported by the Spanish Ministry of Economy, Industry and Competitiveness under Grant TIN2013-47272-C2-1-R.Balapuwaduge, IAM.; Li, F.; Pla, V. (2018). Dynamic Spectrum Reservation for CR Networks in the Presence of Channel Failures: Channel Allocation and Reliability Analysis. IEEE Transactions on Wireless Communications. 17(2):882-898. https://doi.org/10.1109/TWC.2017.2772240S88289817

System Times and Channel Availability for Secondary Transmissions in CRNs: A Dependability Theory based Analysis

[EN] Reliability is of fundamental importance for the performance of secondary networks in cognitive radio networks (CRNs). To date, most studies have focused on predicting reliability parameters based on prior statistics of traffic patterns from user behavior. In this paper, we define a few reliability metrics for channel access in multichannel CRNs that are analogous to the concepts of reliability and availability in classical dependability theory. Continuous-time Markov chains are employed to model channel available and unavailable time intervals based on channel occupancy status. The impact on user access opportunities based on channel availability is investigated by analyzing the steady-state channel availability and several system times such as mean channel available time and mean time to first channel unavailability. Moreover, the complementary cumulative distribution function for channel availability is derived by applying the uniformization method, and it is evaluated as a measure of guaranteed availability for channel access by secondary users. The precision and the correctness of the derived analytical models are validated through discrete-event-based simulations. We believe that the reliability metric definitions and the analytical models proposed in this paper have their significance for reliability and availability analysis in CRNs.The work of V. Pla was supported by the Ministry of Economy and Competitiveness of Spain under Grant TIN2013-47272-C2-1-R. The review of this paper was coordinated by Dr. B. Canberk.Balapuwaduge, IAM.; Li, FY.; Pla, V. (2017). System Times and Channel Availability for Secondary Transmissions in CRNs: A Dependability Theory based Analysis. IEEE Transactions on Vehicular Technology. 66(3):2771-2788. https://doi.org/10.1109/TVT.2016.2585200S2771278866

On the Performance of Channel Assembling and Fragmentation in Cognitive Radio Networks

[EN] Flexible channel allocation may be applied to multi-channel cognitive radio networks (CRNs) through either channel assembling (CA) or channel fragmentation (CF). While CA allows one secondary user (SU) occupy multiple channels when primary users (PUs) are absent, CF provides finer granularity for channel occupancy by allocating a portion of one channel to an SU flow. In this paper, we investigate the impact of CF together with CA for SU flows by proposing a channel access strategy which activates both CF and CA and correspondingly evaluating its performance. In addition, we also consider a novel scenario where CA is enabled for PU flows. The performance evaluation is conducted based on continuous time Markov chain (CTMC) modeling and simulations. Through mathematical analyses and simulation results, we demonstrate that higher system capacity can be achieved indeed by jointly employing both CA and CF, in comparison with the CA-only strategies. However, this benefit is obtained only under certain conditions which are pointed out in this paper. Furthermore, the theoretical capacity upper bound for SU flows with both CF and CA enabled is derived when PU activities are relatively static compared with SU flows.This work was supported by the EU Seventh Framework Programme FP7-PEOPLE-IRSES under Grant agreement 247083, project acronym S2EuNet. The work of L. Jiao was supported by the Research Council of Norway through the ECO-boat MOL project under Grant 210426. The work of V. Pla was supported in part by the Ministry of Economy and Competitiveness of Spain under Grant TIN2010-21378-C02-02. The associate editor coordinating the review of this paper and approving it for publication was H. Wymeersch.Jiao, L.; Balapuwaduge, IAM.; Li, FY.; Pla, V. (2014). On the Performance of Channel Assembling and Fragmentation in Cognitive Radio Networks. IEEE Transactions on Wireless Communications. 13(10):5661-5675. https://doi.org/10.1109/TWC.2014.2322057S56615675131

Channel Assembling with Priority-based Queues in Cognitive Radio Networks: Strategies and Performance Evaluation

[EN] With the implementation of channel assembling (CA) techniques, higher data rate can be achieved for secondary users in multi-channel cognitive radio networks. Recent studies which are based on loss systems show that maximal capacity can be achieved using dynamic CA strategies. However the channel allocation schemes suffer from high blocking and forced termination when primary users become active. In this paper, we propose to introduce queues for secondary users so that those flows that would otherwise be blocked or forcibly terminated could be buffered and possibly served later. More specifically, in a multi-channel network with heterogeneous traffic, two queues are separately allocated to real-time and elastic users and channel access opportunities are distributed between these two queues in a way that real-time services receive higher priority. Two queuing schemes are introduced based on the delay tolerance of interrupted elastic services. Furthermore, continuous time Markov chain models are developed to evaluate the performance of the proposed CA strategy with queues, and the correctness as well as the preciseness of the derived theoretical models are verified through extensive simulations. Numerical results demonstrate that the integration of queues can further increase the capacity of the secondary network and spectrum utilization while decreasing blocking probability and forced termination probability. © 2002-2012 IEEE.The authors would like to acknowledge the support from the EU FP7-PEOPLE-IRSES program, project acronym S2EuNet (Grant no. 247083). The work of V. Pla was partly supported by the Ministerio de Ciencia e Innovacion of Spain under Grant TIN2010-21378-C02-02.Balapuwaduge, IAM.; Jiao, L.; Pla, V.; Li, FY. (2014). Channel Assembling with Priority-based Queues in Cognitive Radio Networks: Strategies and Performance Evaluation. IEEE Transactions on Wireless Communications. 13(2):630-645. https://doi.org/10.1109/TWC.2013.120713.121948S63064513

Preamble Transmission Prediction for mMTC Bursty Traffic : A Machine Learning based Approach

Author's accepted manuscript.© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.acceptedVersio

Hidden Markov Model Based Machine Learning for mMTC Device Cell Association in 5G Networks

Massive machine-type communication (mMTC) is expected to play a pivotal role in emerging 5G networks. Considering the dense deployment of small cells and the existence of heterogeneous cells, an MTC device can discover multiple cells for association. Under traditional cell association mechanisms, MTC devices are typically associated with an eNodeB with highest signal strength. However, the selected eNodeB may not be able to handle mMTC requests due to network congestion and overload. Therefore, reliable cell association would provide a smarter solution to facilitate mMTC connections. To enable such a solution, a hidden Markov model (HMM) based machine learning (ML) technique is proposed in this paper to perform optimal cell association

Preamble Reservation Based Access for Grouped mMTC Devices with URLLC Requirements

Ultra-reliable low latency communication (URLLC) and massive machine type communications (mMTC) are two of the three major technological pillars in 5G. For medium access in mMTC scenarios, e.g., smart cities, a major bottleneck for achieving reliable access is channel congestion due to LTE-A based random access. Hence, priority-based access schemes are preferred in order to provide reliable and low latency access for mMTC devices in 5G networks. In this paper, we categorize the devices covered inside a cell into grouped and non-grouped sets and propose a preamble reservation based 2-step access scheme where grouped devices gain network access via a designated group leader using reserved preambles. Through analysis and simulations, we demonstrate that the proposed scheme enables ultra-reliable and low latency access for grouped devices while improving the performance of non-grouped devices through proper configuration of parameters

Optimal Utilization of Charging Resources of Fast Charging Station with Opportunistic Electric Vehicle Users

The key challenge with the rapid proliferation of electric vehicles (EVs) is to optimally manage the available energy charging resources at EV fast-charging stations (FCSs). Furthermore, the rapid deployment of fast-charging stations provides a viable solution to the potential driving range anxiety and charging autonomy. Costly grid reinforcements due to extra load caused by fast charging can be omitted using a dedicated energy storage and/or renewable energy system at the FCS. The energy supply and fixed number of EV supply equipment (EVSE) are considered as the limited charging resources of FCS. Amidst various uncertainties associated with the EV charging process, how to optimally utilize limited charging resources with opportunistic ultra-fast charging EV users (UEVs) is studied in this work. This work proposes resource allocation and charging coordination strategies that facilitate UEVs to dynamically exploit these limited charging resources with defined liabilities when pre-scheduled users (SEVs) do not occupy them to utilize limited charging resources maximally. Moreover, the proposed dynamic charging coordination strategies are analyzed with a Monte Carlo simulation (MCS). The presented numerical results reveal that the major drawbacks of under-utilization of limited charging resources by SEVs can be significantly improved through dynamic charging resource allocation and coordination along with UEVs. With the proposed charging coordination strategies in this study, the maximum charging resource utilization of considered FCS with 10 EVSE has been improved to 90%, which bounds to 78% only with SEVs

MEC-RHA:demonstration of novel service request handling algorithm for MEC

Abstract Multi-Access Edge Computing (MEC) is a cloud computing evolution that delivers end-user services at the mobile network’s edge. As a result, MEC guarantees that users will benefit from ultra-low latency and increased bandwidth when using the services. The orchestration process is the holistic management and control of the edge computing platforms. Handling of service requests forwarded by the MEC subscribers is an inceptive function that requires the intervention of the orchestrator. This paper demonstrates how an advanced service request handler algorithm (MEC-RHA) works on MEC orchestration, considering factors of service priority levels, feasibility, and resource availability when launching a service; while an optimal MEC server selection process is formed based on those factors