Turbo SpaceTime Processing to Improve Wireless Channel Capacity

Abstract

By deriving a generalized Shannon capacity formula for multiple-input, multiple-output Rayleigh fading channels, and by suggesting a layered space-time architecture concept that attains a tight lower bound on the capacity achievable, Foschini has shown a potential enormous increase in the information capacity of a wireless system employing multiple-element antenna arrays at both the transmitter and receiver. The layered space-time architecture allows signal processing complexity to grow linearly, rather than exponentially, with the promised capacity increase. This paper includes two important contributions: First, we show that Foschini's lower bound is, in fact, the Shannon bound when the output signal-to-noise ratio (SNR) of the space-time processing in each layer is represented by the corresponding ?>matched filter ?> bound. This proves the optimality of the layered space-time concept. Second, we present an embodiment of this concept for a coded system operating at a low average SNR and in the presence of possible intersymbol interference. This embodiment utilizes the already advanced space-time filtering, coding and turbo processing techniques to provide yet a practical solution to the processing needed. Performance results are provided for quasi-static Rayleigh fading channels with no channel estimation errors. We see for the first time that the Shannon capacity for wireless communications can be both increased by N times (where N is the number of the antenna elements at the transmitter and receiver) and achieved within about 3 dB in average SNR, about 2 dB of which is a loss due to the practical coding scheme we assume - the layered space-time processing itself is nearly information-lossless!