Some of the new trends emerging in future wireless networks enable a vastly increased fluidity in accessing a wide range of resources, thus supporting flexible network composition and dynamic allocation of resources to virtual network operators (VNOs). In this work we study a new resource allocation opportunity that is enabled by the cloud radio access network architecture. In particular, we investigate the relationship between the cloud-based antennas and spectrum as two important resources in virtualized wireless networks. We analyze the interplay between spectrum and antennas in the context of an auction-based allocation mechanism through which VNOs can bid for a combination of the two types of resources. Our analysis shows that the complementarity and partial substitutability of the two resources significantly impact the results of the allocation of those resources and uncovers the possibility of divergent interests between the spectrum and the infrastructure providers.

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Telecommunication standards have become a reliable mechanism to strengthen collaboration between industry and research institutions to accelerate the evolution of communications systems. Standards are needed to enable cooperation while promoting competition. Within the framework of a standard, the companies involved in the standardization process contribute and agree on appropriate technical specifications to ensure diversity, compatibility and facilitate worldwide commercial deployment and evolution. Those parts of the system that can create competitive advantages are intentionally left open in the specifications. Such specifications are extensive, complex and minimalistic. This makes the telecommunication standards education a difficult endeavor, but it is much demanded by industry and governments to spur economic growth. This paper describes a methodology for teaching wireless communications standards. We define our methodology around six learning stages that assimilate the standardization process and identify key learning objectives for each. Enabled by software-defined radio technology we describe a practical learning environment that facilitates developing many of the needed technical and soft skills without the inherent difficulty and cost associated with radio frequency components and regulation. Using only open-source software and commercial off-the-shelf computers, this environment is portable and can easily be recreated at other educational institutions and adapted to their educational needs and constraints. We discuss our and our students' experiences when employing the proposed methodology to 4 th generation (4G) long-termevolution (LTE) standard education at Barcelona Tech.

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Abstract-CurrentSoftware-Defined Radio applications (waveforms) are tailored to specific hardware. Processor vendors frequently adapt internal OS mechanisms for its specific architecture (e.g. scheduling and synchronization). The Abstraction Layer and Operating Environment (ALOE) is an open source SDR operating environment that isolates platform architecture from the application design. An integrated resource manager is capable of automatically mapping waveform components to a network of heterogeneous processors while meeting the waveform's real-time requirements. This paper analyzes the ALOE performance for x86 and ARM processors. It presents computing histograms of UTRAN transceiver components, the maximum achievable throughput of a simple BPSK modem, interface latencies, and overhead measurements of the ALOE background processes. SDR; middleware; resource overhead; software-defined radio performance; abstraction layer and operating environment (ALOE)

It is widely known that the SDR industry campaigns component-based radio applications, which will enable fast prototyping and deployment of new radio devices and may increase manufacturing profits. Through the JTRS program, the US Dept. of Defence proposed the SCA specification as the standard for military communications. The SDR Forum is now reviewing these specifications and trying to adapt them to the commercial market. The significant differences between military and commercial communications' requirements make this migration a hazardous task. On the other hand, the SCA specification does not consider any method or procedure that enables cognitive functionalities, which would be necessary for future cognitive radio implementations. This paper therefore presents an alternative approach to SCA, introducing a lowprofile operating environment for next generation cognitive radios. We demonstrate its suitability for present and future commercial radios.

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This paper analyzes the computing resource\ud management implications of SDR base stations implemented\ud as SDR clouds. SDR clouds describe distributed\ud antennas that connect to a data center for digital signal\ud processing. The data center employs cloud computing\ud technology, providing a virtualized computing resource\ud pool. The service area of a single SDR cloud may be a\ud metropolitan area with a high user density. Hence, the data\ud center will execute thousands of SDR applications in parallel,\ud providing wireless communications services to several\ud radio cells. Whenever a user initiates or terminates a\ud wireless communications session, computing resources\ud need to be allocated or deallocated in real time. We\ud therefore propose a hierarchical resource management.\ud This paper justifies such an approach and analyzes different\ud resource management strategies. The results indicate the\ud need for strategies that can dynamically adapt to the given\ud user traffic distribution.Peer ReviewedPostprint (published version