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Spectrum sensing is one key enabler towards opportunistic spectrum access in cognitive radio networks. Such scenarios allow cognitive users (a.k.a. secondary users) to access some licensed spectrum band as long as they do not interfere with the licensed (or primary) users. The main goal is to achieve an efficient and utmost access to the otherwise underutilized spectrum resources while still guaranteeing primary users a non-harmful operation. Spectrum sensing can be then used by secondary users to detect spectrum holes that may be accessed in a non-interfering manner. However, spectrum sensing may be subject to errors in the form of false-alarm and misdetection. False-alarm causes spectrum under-use while misdetection leads to spectrum interference between primary and secondary users. Unfortunately, these two magnitudes pose a trade-off on the sensing mechanism: low misdetection is achieved at the expense of high false alarm and vice versa. Consequently, an adequate operating point of the sensing mechanism should be determined. In this work we evaluate the impact of false-alarm and misdetection errors on the performance of a spectrum sensing scenario. We use a discrete time Markov chain (DTMC) model and we determine the suitable operating point for the sensing mechanism under different traffic load conditions such that some quality of service is attained by both primary and secondary users. Performance results reveal that by effectively choosing the operation point bearing in mind the traffic load levels will lead to enhanced perceived quality of service of both primary and secondary users.