The dissertation is about distributed algorithms for cooperative processing among collaborated nodes within a network (In-Network Processing (INP)). The main content is mainly focused on novel INP algorithms development for the distributed signal processing that are applied to cooperative networks like the wireless sensor networks or mobile communications networks. For the distributed applications, the INP can generally provide solutions to distributed inference problems based on measurements of physical, medical, biological chemical sensors in wireless sensor networks, what is more, it can also facilitate distributed signals estimation and transmission for the distributed radio access networks in 5G/6G communications system. In this dissertation, a variety of distributed algorithms under the framework of INP have been developed. These INP algorithms are designed for some application scenarios where joint processing tasks are able to be achieved by cooperated entities in wireless communications networks through a distributed and parallel fashion. In particular, two main applications the distributed consensus-based joint estimation for uplink signal detection and distributed joint precoding for downlink signal transmission in communications networks are highly focused on. Overall, this work not only presents a variety of concrete INP algorithms for distributed processing in communication networks, it also provides novel ideas and deep analysis of the INP techniques and numerical approaches that can be applied to achieve distributed implementation of joint processing for a wide range of applications in cooperative networks.weiterlesen