In this paper we describe a frequency domain data transmission method to be used for digital data transmission over analog telephone lines which exploits recently derived reduced computational complexity algorithms, such as the Winograd Fourier Transform, to achieve a significantly lower computational rate than comparable time domain QAM modems implemented digitally using signal processing techniques. In addition to the lower computational rate, the proposed method also allows for better channel bandwidth utilization by allowing optimal signal power allocation based on the channel's signal to noise versus frequency characteristics. Experimental results on this method are presented, indicating that it may be possible to wnd over 10,000 BPS over an unconditioned telephone line while maintaining a i0 BER.

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Signal processing is a data processing domain that contains a diversity of applications, including speech processing, image processing, radar, sonar, medical imaging, data communications, seismic processing, and many others. Despite the diversity of the applications, this processing domain has a very structured set of characteristics. These include real-time operation. dominance of arithmetic operations, and well-structured data flows. The Real-Time Signal Processor (RSP) is a microprocessor architecture that was created to exploit these characteristics in order to provide an expeditious and economical way to implement signal processing applications. In this paper, the organization and architecture ofthe RSP are described. Features of the RSP, such as the instruction pipeline and the fractionalJixed-point arithmetic, which exploit the characteristics of signal processing to provide additional computational power, are emphasized. Other features, such as the powerful indexing, the saturation arithmetic, the guard bits. and the double-word-width accumulator, which add much to the processor's versatility and programmability. are also highlighted. The performance of the RSP is illustrated through examples.

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