Pulse or digital communications – Spread spectrum – Direct sequence
Reexamination Certificate
1999-06-11
2002-11-12
Vo, Don N. (Department: 2631)
Pulse or digital communications
Spread spectrum
Direct sequence
C375S152000, C375S345000, C375S260000
Reexamination Certificate
active
06480528
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention relates to communications, and more particularly to techniques that provide for improved decoding performance of a multi-carrier signal.
Digital communication is widely used for many applications including digital video, cellular telephones, and other. Examples of digital communications systems for use in cellular phones include time division multiple access (TDMA), frequency division multiple access (FDMA), and code division multiple access (CDMA) communications systems. These multiple access systems support simultaneous transmission of multiple channels, which are allocated to users on demand and as available.
CDMA utilizes spread spectrum techniques that offer significant advantages over other modulation techniques used by other multiple access communication systems. In CDMA systems, data for each communications channel (i.e., assigned to a particular user) is coded and spread across the entire frequency band. The inherent wideband nature of the CDMA signal offers frequency diversity such that selective fading affects only a portion of the CDMA signal bandwidth. Space or path diversity is achieved by providing multiple signal paths through simultaneous transmission from two or more base stations to a mobile unit. Further, path diversity may be obtained by exploiting the multipath environment through spread spectrum processing in which signals arriving with different propagation delays are separately received and processed and later combined.
CDMA systems are typically designed to conform to the “TIA/EIA/IS-95-A Mobile Station-Base Station Compatibility Standard for Dual-Mode Wideband Spread Spectrum Cellular System,” hereinafter referred to has the IS-95-A standard. This standard defines the number of channels available for each CDMA signal and the CDMA signal bandwidth. For example, a CDMA signal conforming to the IS-95-A standard (i.e., a “standard” CDMA signal) includes up to 64 orthogonal Walsh channels and has a bandwidth of 1.2288 MHz.
To achieve greater data transmission capability, a wideband CDMA signal or multiple standard CDMA signals can be used. One such signal is a multi-carrier (MC) signal that is defined by “TR-45 Physical Layer Standard for CDMA 2000 Spread Spectrum Systems,” referred to as the IS-95-C standard and incorporated herein by reference. The multi-carrier signal includes three standard CDMA signals to provide up to three times the data transmission capability of the standard CDMA signal.
The CDMA signal is encoded and modulated for transmission in a noisy transmission environment. In accordance with IS-95-A standard, the modulation includes “covering” each communications channel with a unique Walsh code corresponding to that channel and “spreading” the covered channel with a pseudo-noise (PN) sequence unique to the particular transmitting base station. Walsh covering provides orthogonality between the channels, and PN spreading spreads the covered channels over the entire CDMA signal bandwidth. Thus, each CDMA signal is a combination of many individually covered and spread channels (e.g., up to 64 for IS-95-A systems).
The CDMA signal is received and processed by a receiver. In many receiver designs, the received RF signal is conditioned and filtered by analog circuitry, sampled and quantized by an analog-to-digital converter (ADC). The received RF signal includes the desired signal (e.g., one or more CDMA signals) along with the undesired signals. Typically, one or more stages of filtering are provided to remove the undesired signals. One of the filter stages is typically an analog filter having a bandwidth matched to the bandwidth of the signal being demodulated (e.g., approximately 1.26 MHz for one IS-95-A compliant CDMA signal).
Matched filtering is conventionally performed to remove an optimum (or near optimum) amount of noise from the received signal before sampling and quantizing by the ADC. Typically, the amplitude of the signal provided to the ADC input (i.e., the desired signal plus noise) is maintained such that the ADC introduces a minimum (or near minimum) amount of saturation plus quantization noise. Filtering by a filter having an excessive bandwidth results in the inclusion of more noise than optimal. The additional noise may require a larger dynamic range ADC to reach the same saturation plus quantization noise. Conversely, filtering by a filter having a narrow bandwidth results in the removal of more desired signals than optimal.
There are several reasons why it may not be practical to perform matched filtering before sampling by the ADC. For example, the input signal may contain a number of modulated signals, and it may be desirable to sample all modulated signals using the minimum number of ADCs (i.e., to reduce cost and circuit complexity). As another example, the input signal may have a variable bandwidth (i.e., for a variable data rate system) and it may be more efficient to utilize a filter having a bandwidth matched to the largest bandwidth. For each of these examples, multiple analog matched filters can be used for each signal bandwidth of interest. However, this “brute force” approach increases circuit complexity and cost.
In accordance with the IS-95-A standard, convolutional encoding is used to provide error-correcting capability of the received data bits. At the receiver, after filtering by a matched filter, sampling and quantization by an ADC, and demodulation by a demodulator, the demodulated data samples are provided to a decoding circuitry. Typically, a decoder is used to perform maximum likelihood decoding of the convolutionally encoded data. For optimal performance, the decoder requires that the input signal (or soft decision samples) meet certain conditions. Specifically, it can be shown that the decoder operates at or near optimum when the input signal to the decoder is scaled by the total noise in the signal band. However, when the filter before the ADC is not matched to signal bandwidth, the signal provided to the decoder is less than optimal and the decoding performance degrades.
SUMMARY OF THE INVENTION
The invention provides techniques that can be used for improved decoding performance of a multi-carrier signal. In accordance with the invention, the multi-carrier signal is initially filtered by an analog filter having a bandwidth that is equal to or wider than the bandwidth of the signal or signals being demodulated and decoded. The analog filter may thus be wider than that of a matched filter. The filtered signal is then sampled (i.e., by an ADC). For each signal being processed, the samples are then filtered with a discrete time matched filter, scaled, quantized, and provided to the decoder. An AGC loop is used to maintain a proper signal level into the quantizer. Thus, matched filtering and gain control are performed after the initial sampling stage.
An embodiment of the invention provides a method for processing a desired signal for decoding (i.e., by a decoder). In accordance with the method, an input signal that includes the desired signal and additional signals is received and filtered with a first filter having a bandwidth greater than a bandwidth of the desired signal. The filtered signal is then sampled to generate discrete time samples that are further filtered with a discrete time matched filter to generate filtered samples. The filtered samples are then scaled with a scaling factor and quantized. A quantity related to the amplitude of the quantized samples (i.e., power) is measured, and the scaling factor is adjusted in accordance with the measured quantity. The quantized samples can be further processed (i.e., demodulated) and provided to a decoder. The desired signal can be a quadrature-modulated signal, in which case matched filtering, scaling, quantization are performed on the in-phase and quadrature components of the desired signal.
The adjustment of the scaling factor can be performed by an automatic gain control (AGC) loop that compares the measured quantity (e.g., the signal power of the quantized samples) against a predetermined val
Patel Shimman
Wilborn Thomas
Brown Charles D.
Pappas George C.
Qualcomm Incorporated
Vo Don N.
Wadsworth Philip R.
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