In　the　speech　communication　over　the　internet,　due　to　the　latency　and　jitter　of　the　network,　the　data　packets　may　be　lost　and　result　in　a　degraded　user　experience.　Therefore,　the　packet　loss　concealment　(PLC)　technology　plays　an　important　role　in　recovering　the　lost　information.　In　this　paper,　a　PLC　method　only　using　few　historical　information　is　proposed　based　on　generative　adversarial　network　(GAN).　In　this　method,　the　generator　is　composed　of　the　improved　gated　attention　unit　(IGAU)　and　temporal　convolution　network,　which　can　fully　exploit　the　available　time-domain　information　and　recover　the　lost　speech　signal.　Specially,　a　consistent　mapping　approach　is　devised　to　enhance　the　quality　of　the　generated　speech.　In　addition,　two　additional　loss　functions　are　used　to　assist　in　the　training　of　network.　The　experimental　results　show　that　the　proposed　method　has　better　performance　in　terms　of　both　perceptual　quality　and　speech　intelligibility　at　different　packet　loss　rates.