In　heterogeneous　cellular　network　(HCN),　the　cell　is　usually　divided　into　tracking　areas　(TA)　for　better　management　of　users’　locations.　The　trade-off　between　location　update　signaling　and　system　paging　signaling　is　a　core　issue　in　TA　planning.　However,　the　existing　TA　planning　solution　aiming　at　large-scale　deployment　of　small　cell　has　the　problems　of　uneven　location　updating　signaling,　ping-pong　effect　and　so　on.　Against　the　above　problems,　this　paper　presents　NCD-TAP,　a　novel　TA　planning　method　based　on　Newman　fast　community　detection　algorithm.　Firstly,　the　TA　planning　problem　is　modeled　as　a　complex　network　community　detection　problem　and　the　Newman　algorithm　in　the　community　detection　is　used　to　propose　the　TA　planning　scheme.　Then,　the　modularity　concept　of　community　partition　is　introduced　to　measure　the　performance　of　TA　planning　scheme.　Finally,　the　experimental　simulation　results　show　that　the　scheme　proposed　in　this　paper　has　obvious　advantages　in　the　case　of　large　scale　of　small　cell　and　high　expectation　of　small　cell　Poisson　distribution,　and　is　suitable　for　massive　cellular　deployment　environment.　©　2019,　North　Atlantic　University　Union.　All　rights　reserved.