This　paper　proposes　a　3-D　sound　field　reproduction　(SFR)　approach　through　the　combination　of　alternating　direction　method　of　multipliers　(ADMM)-based　least-absolute　shrinkage　and　selection　operator　(Lasso)　and　regularized　least　square　(LS).　The　proposed　SFR　method　is　split　into　two　parts　through　the　pressure　matching　optimization　of　loudspeaker　positions　and　the　computation　of　driving　signals.　At　the　first　part,　a　plurality　of　candidate　positions　of　loudspeakers　in　planar　array　is　given　and,　then,　the　active　speaker　selection　method　is　proposed　based　on　ADMM　complex　Lasso　algorithm　for　selecting　the　optimal　loudspeaker　positions.　Afterwards,　regularized　LS　is　adopted　to　calculate　the　selected　loudspeaker　weights　and　control　the　total　power.　The　numerical　simulation　experiments　demonstrate　that　the　proposed　SFR　scheme　outperforms　the　existing　sparse　loudspeakers＇　placement　and　weight　optimization　algorithms　especially　in　under-sampled　sound　fields.　Meanwhile,　the　evaluations　also　confirmed　that　the　proposed　method　could　significantly　reduce　the　computational　complexity　of　the　active　loudspeaker　selection　compared　to　the　state-of-the-art　Lasso-based　SFR.　Effectively,　the　proposed　method　uses　a　relatively　small　number　of　loudspeakers　for　a　satisfying　reproduction　quality.