Input-Output Clustering Criterion (IOCC) for Optimizing Distributed Antenna Locations

In this paper, we propose an input-output space clustering criterion (IOCC) to optimize the locations of the remote antenna units (RAUs) of generalized Distributed Antenna Systems (DASs) under sum power constraint. In IOCC, the input space refers to RAU location space and output space refers to location specific ergodic capacity space for noise-limited environments. Given a location-specific arbitrary desired ergodic capacity function over a geographical area, we define the error as the difference between actual and desired ergodic capacity. Our investigations show that i) the IOCC provides an upper bound to the cell averaged ergodic capacity error; and ii) the derived upper bound is equal to a weighted quantization error function in location-capacity space (input-output space) and iii) the upper bound can be made arbitrarily small by a clustering process increasing the number of RAUs for a feasible DAS. IOCC converts the RAU location problem into a codebook design problem in vector quantization in input-output space, and thus includes the Squared Distance Criterion (SDC) for DAS in [15] (and other related papers) as a special case, which takes only the input space into account. Computer simulations confirm the theoretical findings and show that the IOCC outperforms the SDC for DAS in terms of the defined cell averaged "effective" ergodic capacity.
Comment: totally 13 plots in Fig.1 to Fig.11, 32 pages, submitted to IEEE Trans. Information Theory