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Opportunistic spectrum access in cognitive radio network is proposed for remediation of spectrum under-utilization caused by exclusive licensing for service providers that are intermittently utilizing spectrum at any given geolocation and time. The unlicensed secondary users (SUs) rely on opportunistic spectrum access to maximize spectrum utilization by sensing/identifying the idle bands without causing harmful interference to licensed primary users (PUs). In this thesis, Real-time Opportunistic Spectrum Access in Cloud-based Cognitive Radio Networks (ROAR) architecture is presented where cloud computing is used for processing and storage of idle channels. Software-defined radios (SDRs) are used as SUs and PUs that identify, report, analyze and utilize the available idle channels. The SUs in ROAR architecture query the spectrum geolocation database for idle channels and use them opportunistically. The testbed for ROAR architecture is designed, analyzed, implemented and evaluated for efficient and plausible opportunistic communication between SUs.