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  • 1.
    Alabbasi, Abdulrahman
    et al.
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
    Cavdar, Cicek
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
    Delay-Aware Green Hybrid CRAN2017In: 2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 201727 June 2017, IEEE conference proceedings, 2017, 7959942Conference paper (Refereed)
    Abstract [en]

    As a potential candidate architecture for 5G systems,cloud radio access network (CRAN) enhances the system’s capacityby centralizing the processing and coordination at the centralcloud. However, this centralization imposes stringent bandwidthand delay requirements on the fronthaul segment of the networkthat connects the centralized baseband processing units (BBUs)to the radio units (RUs). Hence, hybrid CRAN is proposed toalleviate the fronthaul bandwidth requirement. The concept ofhybrid CRAN supports the proposal of splitting/virtualizing theBBU functions processing between the central cloud (centraloffice that has large processing capacity and efficiency) and theedge cloud (an aggregation node which is closer to the user,but usually has less efficiency in processing). In our previouswork, we have studied the impact of different split points onthe system’s energy and fronthaul bandwidth consumption. Inthis study, we analyze the delay performance of the end user’srequest. We propose an end-to-end (from the central cloud tothe end user) delay model (per user’s request) for differentfunction split points. In this model, different delay requirementsenforce different function splits, hence affect the system’s energyconsumption. Therefore, we propose several research directionsto incorporate the proposed delay model in the problem ofminimizing energy and bandwidth consumption in the network.We found that the required function split decision, to achieveminimum delay, is significantly affected by the processing powerefficiency ratio between processing units of edge cloud and centralcloud. High processing efficiency ratio ( 1) leads to significantdelay improvement when processing more base band functionsat the edge cloud.

  • 2.
    Alabbasi, Abdulrahman
    et al.
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS. King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
    Rezki, Zouheir
    Shihada, Basem
    Outage Analysis of Spectrum Sharing Over M-Block Fading With Sensing Information2017In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 66, no 4, 3071-3087 p.Article in journal (Refereed)
    Abstract [en]

    Future wireless technologies, such as fifth-generation (5G), are expected to support real-time applications with high data throughput, e.g., holographic meetings. From a bandwidth perspective, cognitive radio (CR) is a promising technology to enhance the system's throughput via sharing the licensed spectrum. From a delay perspective, it is well known that increasing the number of decoding blocks will improve system robustness against errors while increasing delay. Therefore, optimally allocating the resources to determine the tradeoff of tuning the length of the decoding blocks while sharing the spectrum is a critical challenge for future wireless systems. In this paper, we minimize the targeted outage probability over the block-fading channels while utilizing the spectrum-sharing concept. The secondary user's outage region and the corresponding optimal power are derived, over two-block and M-block fading channels. We propose two suboptimal power strategies and derive the associated asymptotic lower and upper bounds on the outage probability with tractable expressions. These bounds allow us to derive the exact diversity order of the secondary user's outage probability. To further enhance the system's performance, we also investigate the impact of including the sensing information on the outage problem. The outage problem is then solved via proposing an alternating optimization algorithm, which utilizes the verified strict quasi-convex structure of the problem. Selected numerical results are presented to characterize the system's behavior and show the improvements of several sharing concepts.

  • 3.
    Alabbasi, Abdulrahman
    et al.
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
    Shihada, Basem
    Optimal Cross-Layer Design for Energy Efficient D2D Sharing Systems2017In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 16, no 2, 839-855 p.Article in journal (Refereed)
    Abstract [en]

    In this paper, we propose a cross-layer design, which optimizes the energy efficiency of a potential future 5G spectrum-sharing environment, in two sharing scenarios. In the first scenario, underlying sharing is considered. We propose and minimize a modified energy per good bit (MEPG) metric, with respect to the spectrum sharing user's transmission power and media access frame length. The cellular users, legacy users, are protected by an outage probability constraint. To optimize the non-convex targeted problem, we utilize the generalized convexity theory and verify the problem's strictly pseudoconvex structure. We also derive analytical expressions of the optimal resources. In the second scenario, we minimize a generalized MEPG function while considering a probabilistic activity of cellular users and its impact on the MEPG performance of the spectrum sharing users. Finally, we derive the associated optimal resource allocation of this problem. Selected numerical results show the improvement of the proposed system compared with other systems.

  • 4.
    Alabbasi, Abdulrahman
    et al.
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
    Shihada, Basem
    Cavdar, Cicek
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    On Energy Efficiency of Prioritized IoT Systems2017Conference paper (Other academic)
    Abstract [en]

    The inevitable deployment of 5G and the Internetof-Things (IoT) sheds the light on the importance of the energy efficiency(EE) performance of Device-to-Device (DD) communicationsystems. In this work, we address a potential IoT application,where different prioritized DD system, i.e., Low-Priority (LP) andHigh-Priority (HP) systems, co-exist and share the spectrum. Wemaximize the EE of each system by proposing two schemes. Thefirst scheme optimizes the individual transmission power andthe spatial density of each system. The second scheme optimizesthe transmission power ratio of both systems and the spatialdensity of each one. We also construct and analytically solve amulti-objective optimization problem that combines and jointlymaximizes both HP and LP EE performance. Unique structuresof the addressed problems are verified. Via numerical results weshow that the system which dominates the overall EE (combinedEEs of both HP and LP) is the system corresponding to the lowestpower for low/high power ratio (between HP and LP systems).However, if the power ratio is close to one, the dominating EEcorresponds to the system with higher weight.

    The full text will be freely available from 2017-12-11 22:29
  • 5.
    Lisi, Shari Sofia
    et al.
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
    Alabbasi, Abdulrahman
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
    Tornatore, Massimo
    Cavdar, Cicek
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
    Cost-Effective Migration towards C-RAN with Optimal Fronthaul Design2017In: 2017 IEEE International Conference on Communications, ICC 2017, IEEE conference proceedings, 2017, 7996772Conference paper (Refereed)
    Abstract [en]

    Centralized Radio Access Network (C-RAN) hasbeen recently proposed to increase network capacity, reduceenergy consumption, and improve scalability. However, C-RANrequires an extensive modification to the current infrastructure,which results in a considerable deployment cost. In this paper,we conduct a techno-economic study to evaluate the migrationcost of C-RAN, and we propose a methodology for cost andenergy efficient C-RAN deployment. We exploit the conceptof total cost of ownership, defined as the sum of capital andoperational expenditures. We formulate a Digital Unit (DU) poolplacement optimization problem as Mixed Integer Linear Programming(MILP), which minimizes the total cost of ownership.We compare the total cost of ownership of C-RAN to that ofthe existing infrastructure, under different deployment scenariossuch as greenfield and brownfield deployment of fiber and DUpool, and different cell sizes. The results show that the opticalinfrastructure plays a determinant role in the migration cost ofC-RAN. If greenfield fiber is assumed, the migration cost cannotbe compensated in a reasonable amount of time. If brownfieldfiber is assumed, the migration cost is considerably reduced, anda more feasible C-RAN deployment is achieved.

  • 6. Wang, Xinbo
    et al.
    Alabbasi, Abdulrahman
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
    Cavdar, Cicek
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
    Interplay of Energy and Bandwidth Consumption in CRAN with Optimal Function Split2017In: Communications (ICC), 2017 IEEE International Conference on, IEEE conference proceedings, 2017Conference paper (Other academic)
    Abstract [en]

    Cloud radio access network (CRAN) has been proposedas a potential energy saving architecture and a scalablesolution to increase the capacity and performance of radio networks.The original CRAN decouples the digital unit (DU) fromradio unit (RU) and centralizes the DUs. However, stringent delayand bandwidth constraints are incurred by fronthaul in CRAN,i.e. the network segment connecting RUs and DUs. In this study,we propose a modified CRAN architecture, namely hybrid cloudRAN (H-CRAN), where a DU’s functionalities can be virtualizedand split at several conceivable points. Each split option resultsin two-level deployment of the processing functions, i.e., centralcloud level and edge cloud level, connected by a transport layercalled “midhaul”. We study the interplay of energy efficiencyand midhaul bandwidth consumption when baseband functionsare centralized at the edge cloud vs central cloud. We jointlyminimize the power and midhaul bandwidth consumption in HCRAN,while satisfying the network constraints. The addressedproblem with the associated constrains are modeled as a mixedinteger constraint optimization problem. Numerical results showthe compromise between energy and bandwidth consumption,with the optimal placement of baseband processing functions inH-CRAN architecture.

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