Deployment and management of SDR cloud computing resources: problem definition and fundamental limits
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RESEARCH
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Deployment and management of SDR cloud computing resources: problem definition and fundamental limits Ismael Gomez-Miguelez* , Vuk Marojevic and Antoni Gelonch
Abstract Software-defined radio (SDR) describes radio transceivers implemented in software that executes on general-purpose hardware. SDR combined with cloud computing technology will reshape the wireless access infrastructure, enabling computing resource sharing and centralized digital-signal processing (DSP). SDR clouds have different constraints than general-purpose grids or clouds: real-time response to user session requests and real-time execution of the corresponding DSP chains. This article addresses the SDR cloud computing resource management problem. We show that the maximum traffic load that a single resource allocator (RA) can handle is limited. It is a function of the RA complexity and the call setup delay and user blocking probability constraints. We derive the RA capacity analytically and provide numerical examples. The analysis demonstrates the fundamental tradeoffs between short call setup delays (few processors) and low blocking probability (many processors). The simulation results demonstrate the feasibility of a distributed resource management and the necessity of adapting the processor assignment to RAs according to the given traffic load distribution. These results provide new insights and guidelines for designing data centers and distributed resource management methods for SDR clouds. 1 Introduction Wireless communications technology continuously improves and already facilitates the provisioning of a wide variety of advanced communications services at competitive prices. Whereas current systems provide data rates of a few mega-bits per second (Mbps), 4G systems will offer up to 100 Mbps per user. A few seconds may be necessary today before a connection is established between the user equipment and the network. Long term evolution (LTE) and LTE-Advanced (LTE-A) promise connection establishment times of less than 50 and 10 ms, respectively, [1,2]. Base stations are the wireless access points of cellular communications systems. They comprise antennas and analog and digital signal processing resources for implementing radio transmitters and receivers. The network operator deploys base station resources, that is, wireless transceivers, as a function of the expected peak load. The *Correspondence: [email protected] Department of Signal Theory and Communications, Universitat Politecnica de Catalunya, Barcelona, Spain
goal is guaranteeing a certain quality figure, for example, the probability of granting a user service request. Providing resources for the worst case scenario however leads to long idle times and resource inefficiencies because of the sporadic use of wireless communications services [3]. Deploying fewer resources would increase the mean resource utilization while increasing the user rejection probability. Base stations may be shared between radio operators, but temporarily unused resources can still hardly be
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