This article presents a novel method to measure the transmitted radiation pattern by using orthogonal encoded signals during the process of hybrid analog-digital (HAD) beamformer development. One of the most important indicators in evaluating the performance of HAD beamforming systems is the measurement of the sub-array radiation patterns. However, as the number of elements increases, the number of combinations that can create sub-arrays increases significantly, and the conventional radiation pattern measurement process becomes exhaustive. However, when an orthogonal coded signal is used for the HAD beamforming system measurement, the magnitude and phase information of each element of the HAD beamforming system, including mutual coupling, can be simultaneously obtained from a single scan. Hence, it is possible to measure all feasible sub-array patterns very efficiently. Therefore, we propose an orthogonal code-based time-domain measurement technique and validate it with full-wave time-domain simulations. The results show that it is possible to receive element pattern information independently and that any sub-array pattern can be reconstructed with an accuracy greater than 99.99%.

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’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.

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.