Modeling Of Inter-System Interference In Dynamic Spectrum Sharing Scenario

Spectrum is a scare resource in wireless communication. However, tra-ditional spectrum allocation scheme-fixed allocation-results in a situation that spectrum is not fully utilized. Dynamic spectrum access (DSA) is a promising solution to solve the problem of spectrum shortage. In many countries and ar-eas, part of the spectrum allocated to Digital Television System(DTV) has be and is being opened to share with other wireless communication system in case that cognitive system cause no excessive interference to DTV receivers. This paper models the coexistence interference problem between mobile communi-cation system and DTV system.We focus on resolving the problem of obtaining interference constraints which can be used in the actual network planning. By using those constraints, we can assess the interference level caused by cognitive system to DTV system and it can further support the study of how to avoid interference. Therefore, this paper first lists the interference constraints and system operating parame-ters on the spectrum sharing point of view. Based on theose parameters, we model the coexistence interference and find out the solution to avoid harmful interference caused to DTV system. Then, two coexistence scenarios are given: one consisting of incumbent DTV system and single CR cell, and the other con-sisting of incumbent DTV system and cellular CR system. For both of them, we model the interference constraints of DTV system as a function of feasible network planning parameters. Then interference constraints of the DTV sys-tem can be translated to feasible network planning parameters. Furthermore, simulation method is used to evaluate the impact of those parameters:uplink and downlink transmitted power of cognitive system, the inter-system isola- tion distance, the probability of miss-detection, sensing period. In simulations, both numerical and Monte-Carlo simulation results are given and analyzed to validate feasibility of the theoretical approach. Finally, recommendations to cognitive network planning are given.