  We propose a low complexity antenna selection algorithm for low target rate
users in cloud radio access networks. The algorithm consists of two phases: In
the first phase, each remote radio head (RRH) determines whether to be included
in a candidate set by using a predefined selection threshold. In the second
phase, RRHs are randomly selected within the candidate set made in the first
phase. To analyze the performance of the proposed algorithm, we model RRHs and
users locations by a homogeneous Poisson point process, whereby the
signal-to-interference ratio (SIR) complementary cumulative distribution
function is derived. By approximating the derived expression, an approximate
optimum selection threshold that maximizes the SIR coverage probability is
obtained. Using the obtained threshold, we characterize the performance of the
algorithm in an asymptotic regime where the RRH density goes to infinity. The
obtained threshold is then modified depending on various algorithm options. A
distinguishable feature of the proposed algorithm is that the algorithm
complexity keeps constant independent to the RRH density, so that a user is
able to connect to a network without heavy computation at baseband units.
