This　paper　designs　a　weighted　minimum　mean　square　error　(WMMSE)　based　distortionless　convolution　beamformer　(DCBF)　for　joint　dereverberation　and　denoising.　By　effectively　using　WMMSE　with　the　constraint　of　distortionless,　a　DCBF　is　deduced,　where　the　outputs　of　the　weighted　prediction　error　(WPE)　filter　and　the　WPE-based　minimum　variance　distortionless　response　(MVDR)　beamformer　are　combined　to　initialize　target　signal　for　balancing　signal　distortion,　residual　reverberation　and　residual　noise.　In　addition,　two　optimization　factors　are　introduced　to　reduce　the　reverberation　and　noise　when　the　initialized　target　signal　is　used　for　the　solution　of　beamformer.　As　a　result,　the　designed　beamformer　is　presented　as　a　linear　combination　of　the　WMMSE-based　convolution　beamformer　(CBF)　and　weighted　power　minimization　distortionless　response　(WPD)　filter.　The　experimental　results　demonstrate　the　superior　performance　of　the　designed　beamformer　for　joint　dereverberation　and　denoising　compared　to　the　reference　methods.　©　2024　Elsevier　B.V.