Optimal Site Placement For Cooperative Communications

Cooperative communications, one of the prominent technologies for next generation wireless communications, could significantly improve the system capacity and spectral efficiency by servicing one single user with multiple base stations, which means interference from adjacent cell is used actively from suppressed passively via sharing antennas between different base stations. The deployment of base stations is a classic problem in the field of mobile communication, which would determine the overall performance of the system including several system performance indices such as network delay, interference, synchronization and energy consumption. The modeling and solutions to traditional cellular planning are based on the assumption of non-overlapping hexagonal cell. However, in case of cooperative communications, the coverage of base stations would always overlap with others’ to some degree, which cause the cell selection, calculation of signal to interference and noise ratio and power distribution of base station are different from the traditional cellular planning. Therefore, the paper focuses on the optimal site placement for cooperative communication according to the new characteristics of this scenario.The paper builds two optimization models to determine the optimal location and number of the base stations for cooperative communication and put forward the corresponding algorithms. Numerical simulation shows that the proposed model can effectively reduce the energy consumption and number of base stations with Good convergence, the main work and innovations are as follows.① According to the different cooperation mechanisms between base stations, the clusters of base stations serving the same user are decided by calculating the distance between base stations and users and the corresponding interference model is established, then builds the base station site optimization model with the objective function to minimize the total power consumption of base stations. Output of the site optimization model is used as input variables of the number optimization model of base stations with the objective function to minimize the number of base stations, which is composed to be nest optimization model with the site optimization model.② Mesh adaptive direct search algorithm is used to solve the site optimization model as it is a nonlinear multiple constraints optimization problems. Successive elimination algorithm is used to solve the number optimization model as distance between different base stations is limited in actual situation. A joint optimization algorithm is proposed to solve the established models, in which the methodologies of mesh adaptive direct search and successive elimination have been used as output of the site optimization model is used as input variables of the number optimization model of base stations.③ Two optimization models are solved under the assumption when user distribution follows a uniform, single Gaussian and multiple Gaussian by Monte Carlo method combining with the joint optimization algorithm. As the coverage of base station overlapping degree increases, the number and total transmit power of base stations will be reduced, while the overlap degree is fixed, the number of base stations is inversely proportional to the total transmit power of base stations. Numerical results show that the joint algorithm with good convergence can more effectively reduce the number of base stations or the total transmission power compared with the K-means clustering algorithm, although time complexity of the latter is lower.The research of the study as an exploration to the deployment of the base stations of cooperative communication can be extended to any other user distributions. Related work can provide a reasonable reference for the construction of the next generation mobile communication network.