User-centric network (UCN) organises a dynamic femto access point group (FAPG) for each user to meet the exponential data demands in 5G. However, there exists spatialcorrelation in the scheduling of femto access poin...
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User-centric network (UCN) organises a dynamic femto access point group (FAPG) for each user to meet the exponential data demands in 5G. However, there exists spatialcorrelation in the scheduling of femto access points (FAPs) due to the overlap of different users' FAPGs, which has not yet been analysed in existing literature. In this study, considering this spatialcorrelation by using Matern-like model, simple yet accurate semi-closed form expressions of rate coverage probability and area average goodput of power control strategy in UCN are derived, respectively, using stochastic geometry tools. In this user-centric power control strategy, each user equipment (UE) determines its FAPG radius considering the distance to the nearest FAP, and FAPs within the FAPG employ power control to mitigate dominant interference for the UE. Further, Matern-like model guarantees that two FAPs in the same FAPG will not transmit at full power simultaneously, and thus whether a FAP performs power control is correlated with other FAPs that belong to the same FAPG. The analytical results demonstrate significant performance gains of power control strategy in UCN compared with the non-coordination baseline, e.g. area average goodput is improved by about 44% when FAP-to-UE density ratio equals 1.
This study presents an analytical method that shows how spatialcorrelation degrades the overall performance of cooperative spectrum sensing. In a cooperative spectrum sensing, where all secondary users (SUs) report t...
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This study presents an analytical method that shows how spatialcorrelation degrades the overall performance of cooperative spectrum sensing. In a cooperative spectrum sensing, where all secondary users (SUs) report their sensing information to the fusion centre (FC), sensing information is correlated for closely located users due to the similar surrounding environment. Considering the soft combining at the FC, this study shows how detection performance of correlated SUs is different from uncorrelated SUs. Furthermore, an algorithm is proposed which selects best uncorrelated SUs among all SUs of the network based on received power to the FC from SUs. The simulation results confirm the performance analysis of cooperative spectrum sensing with spatialcorrelation on the sensing data.
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