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OFDM Relay Cognitive Radio Multiple Antennas Resource Allocation Full Duplex Spectrum Sensing Synchronization Spectrum Sharing Interference Cancellation Channel Estimation Feedback Heterogeneous Networks Bi-directional Energy Harvesting Stochastic Geometry HetNet relay networks FBMC Equalization channel capacity TVWS CDMA interference in-band full-duplex system Duplex MIMO Ultra Low Power C-V2V 5G Reliability SC-FDMA interference suppression D-TDD CLI indoor positioning reinforcement learning RSRP weighting - Computation offloading smart factory Cell-free multi-access edge computing estimated position overlapping —Device-to-device (D2D) estimated position updating mMIMO control overhead hybrid NR positioning Femtocell Rat-dependent positioning frame structure Zigbee body area networks channel estimation error Handoff CoMP User grouping power uncertainty ultra-dense small cell network mode selection antenna arrays 5G mobile communication UFMC resource block management inter user interference WVAN health care partial overlap GFDM Dynamic TDD Multi-user Receiver Number of training blocks Uplink SCMA system V2X Vehicular communication cross-link interference LTE-TDD FS-NOMA Location-based user fairness Mode 3 QR Factorization Metaheuristics P-NOMA non-orthogonal multiple access dynamic HetNet spectrum partitioning and 5G networks. massive connectivity non-orthogonal multiple access (NOMA) overloading DQN OTDOA distributed mode Communication range resource selection maximum likelihood method Resource sharing Power allocation packet delay
|Title :||Effects of Channel Estimation Errors on Ultra-Dense Small Cell Networks|
|Authors :||Yosub Park, Jihaeng Heo, Jintae Kim, Sooyong Choi, and Daesik Hong|
|Abstract :||In this paper, we investigate the effect of channel estimation (CE) error on the performances for the ultra-dense small cell networks. Specifically, we examine its effect on the distribution of signal to interference and noise ratio (SINR) and trend of spectral efficiency (SE), and outage probability.
From these, we found out that the SINR degradation due to the CE errors becomes larger, as the density ratio of small base station (BS) to UE increases. We derived the theoretical lower bound of the outage probability, which is the function of CE correlation coefficient. Finally, numerical results demonstrate that the CE errors diminish the increasing scaling of SE, as the small BS density increases.