Overloaded array processing in wireless airborne communication systems

In mobile cellular communications, one of the major challenges that a system designer and a DSP engineer are faced with is severe co-channel interference (CCI). This is especially true for wireless networks that employ airborne repeaters, such as the “base station in the sky” repeater proposed by SkyStation International, Incorporated. The receiver faces the challenge of demodulating the signal of interest (SOI) in the presence of excessive amounts of CCI from a large number of sources. This results in the overloaded environment where the number of near-equal power co-channel interferers, d, exceeds the number of antenna array elements, m. In this paper we first analyze a generic overloaded interference environment experienced by a wireless airborne communication receiver flying at altitudes on the order of miles above the Earth surface. A two-ray propagation model analysis shows that the antenna array mounted on an airborne receiver has to be able to recover the SOI out of hundreds of co-channel interfering signals. Due to the limitations of the array size on the surface of the aircraft, linear signal processing techniques such as space-time beamforming are not be able to perform well in such scenarios. For this reason, we show that signal extraction in overloaded environments can be achieved by employing a non-linear maximum-likelihood (ML) detector. This technique, called least squares with enumeration (LSE), is a ML joint detection approach that provides an optimum solution for overloaded antenna array scenarios in the presence of synchronous co-channel users in an AWGN channel