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In a joint transmission (JT) system using orthogonal frequency-division modulation (OFDM), performance degradation due to asynchronous interference resulting from the time difference of arrival is unavoidable. We propose an affinity propagation clustering (APC) algorithm for radio remote heads clustering for downlink JT in an asynchronous OFDM system. In particular, by closely connecting the principles of APC and JT with synchronization mismatch, we newly design pairwise similarities and preferences of the APC algorithm. The proposed algorithm provides 1.5 times higher 5-percentile user spectral efficiency than the APC algorithm with a conventional similarity matrix, and it has the same time complexity in term of big O notation.

Affinity propagation (AP) clustering with low complexity and high performance is suitable for radio remote head (RRH) clustering for real-time joint transmission in the cloud radio access network. The existing AP algorithms for joint transmission have the limitation of high computational complexities owing to re-sweeping preferences (diagonal components of the similarity matrix) to determine the optimal number of clusters as system parameters such as network topology. To overcome this limitation, we propose a new approach in which preferences are fixed, where the threshold changes in response to the variations in system parameters. In AP clustering, each diagonal value of a final converged matrix is mapped to the position (x,y coordinates) of a corresponding RRH to form two-dimensional image. Furthermore, an environment-adaptive threshold value is determined by adopting Otsu&rsquo, s method, which uses the gray-scale histogram of the image to make a statistical decision. Additionally, a simple greedy merging algorithm is proposed to resolve the problem of inter-cluster interference owing to the adjacent RRHs selected as exemplars (cluster centers). For a realistic performance assessment, both grid and uniform network topologies are considered, including exterior interference and various transmitting power levels of an RRH. It is demonstrated that with similar normalized execution times, the proposed algorithm provides better spectral and energy efficiencies than those of the existing algorithms.