It is known that the sum of sine waves of equal amplitudes but of fixed phase difference between each member is:
where ΔΦ is the phase difference between the members which can be visualized as vectors. This sum can be formed from the input to a transmitter by adding inputs phase shifted by ΔΦ to the input as shown in
In
If now the ΔΦ's in the branches (paths) are made functions of the frequencies of input signals in the same manner as was done in the transmitter, the paths are independently responsive to the incoming signals according to their frequencies. Thus, an incoming group of signals to the sender is enhanced by the arrangement of
The system consists of a transmit and receive location in each of which there are several branches. Phase shifters 101a . . . 101n are located in each of the transmit station branches. Each of these phase shifts ΔΦ1, ΔΦ2, . . . ΔΦn, varies distinctively with frequency. Switched Inverters 103, 103a . . . 103n are also in the respective branches. These switches are responsive to control signals from coder 100 which supplies different digital control pulse sequences to the individual branches. These switches may invert the phase of the branch signal, as stated above, or simply turn the branch on and off in accordance with the control signal. The timing is controlled by the clock 102. The outputs of all the branches are supplied to an adder 200 which also receives a band of signals from filter 106. This band of signals, Σ1 cos ω1 t, Σ2 cos ω2 t, . . . Σn cos ωn t, may originate from noise or a return path from the receiver.
Filter 114 represents the transmission channel bandpass. A group of frequencies selected by the transmitter process is supplied to adder 205, which sums this input with all of the outputs of the receiver branches. The output of 205 goes to all of the branches. Phase shifters 116, 116a . . . 116n are similar to 101, 101a . . . 101n and provide corresponding phase shifts for the same frequency of the corresponding transmitter branch. Units 140, 140a, . . . 140n limit the build up of signal in the branches. This is done by opening the channel for bit length periods only controlled by clock 102a. Bits are detected by amplitude detectors 130, 130a, . . . 130n when the built-up signals exceed a threshold. As shown in
A simpler oversampled digital spike filter may be employed than the standard FIR. As shown in
En=en sin ωt+en−1(wt+τ0) where τ0 is the delay of unit 355. This signal is fed back to adder 357 where it adds to the incoming signal e. The successive summation after n iterations results in En=(sin n ωto/sin ωto)ejωto, where ω=2πf. When f=fo, 2πfo, π0=2π,the magnitude of En will=n, the maximum value, and the nulls occur at frequencies n±fo2n from fo which defines the bandwidth of the filter. Thus, this system is a narrow pass filter. A filter tuned to the null frequency of 355 provides the noise subtracting signal. This filter is composed of delay 355A and adders 356A and 357A. Subtraction takes place in summation amplifier 358. However, the circuit shown in
The invention described in this patent application is a digital compression technology for increasing the data throughput of telecommunications and broadcasting networks. The invention is applicable to telephone networks, including telephone twisted-pair wiring but not limited to it; coaxial cables for telephony, data transmission and video transmission with or without accompanying sound; microwave, cellular, mobile and personal communications networks; radio and satellite systems. The invention applies to multimedia applications in all of the above components of telecommunications and broadcast networks.
The inventive system compresses bandwidth to allow for minimum energy transmission by reducing the spectrum of the data. Each symbol period contains one sinusoid of a specific amplitude. Sampled inputs, samples of sine or cosine waves, vary in amplitude. The disclosed superresonant filter adds new samples to previous samples. It should be noted that the added samples are parts of sine or cosine waves, not the sum of the waves. While the output signal appears to be a spike, it is actually the summation of the samples. Each sample is slightly different in phase from the previous sample. As each sample is added to the previous sample, the effective bandwidth is lessened and the overall signal amplitude is increased. Each iteration has a slightly different phase except in the case of optimum performance where the phase is zero.
The disclosed superresonant filter has a settling time significantly faster than prior art narrow band filters. Prior art narrow band filters passing approximately 1 Hz require approximately 1 second to settle. For example, the disclosed superresonant filter passing 1 Hz will settle in approximately 1 microsecond.
a and 1b show a phased summing method;
c shows the resulting output of the phase summing method versus vector phase difference ΔΦ for n=60;
a is another embodiment of a superresonant filter;
Bits transferred at a given rate require a channel bandwidth W. The bits are transferred in timed pulses. The required bandwidth W allows the reception of white noise of the same bandwidth. The white noise increases in power directly with the bandwidth W. The information pulse is stronger in power than the received noise power by a multiple to insure error free reception of a prescribed quality. The multiple is actually the signal-to-noise ratio (SN ratio). The prescribed quality is the bit error rate. As is apparent, the power required to transmit information increases with the pulse power and the pulse rate.
For example, a one megabit per second information rate is equivalent to a pulse 1 MHz wide. When multiple amplitude levels are employed, more information can be sent within the same bandwidth W. Thus, it is possible to reduce the power required to transmit information at any given rate by reducing the power in the spectrum needed by the information pulse. When the pulse spectrum is transformed to an equivalent line spectrum, it retains the same time duration as the information pulse.
The sine input from 801 is processed by super-resonant filter (SRF) 805. The SRF employs a locally generated sine generator operating at fo in phase with the incoming sine signal. SRF 806 has a local cosine generator operating in phase with the cosine signal generated at 802. Adder 807 linearly adds the signal generated by each of the super-resonant filters. Amplitude adjustors Gt 803, 804, adjust the amplitude of the signal output by the signal generators and input to the SRFs.
For modeling purposes, a noise signal is added to the combined signal 810. The combined signal 810, output from adder 807, is added to a noise signal 809. The noise signal is, in one embodiment, a constant amplitude signal in the range of 0.5 MHz to 1.5 MHz. This signal is created using a random number generating operating at 100 MS/sec. This signal is then fed to the bandpass filter. The system output signal 810 plus the noise 809. In one embodiment of the invention, the filtered noise source is pre-calculated and stored in a file for a consistent noise time wave formula. Further, for analysis purposes, all nodes are observable with a time/waveform power meter.
As shown in
A receiver, as shown in
The receiver input is the signal and noise as well as a synch signal 1101. This signal is input into SRFs 1102 and 1103. If there are additional data streams, additional SRFs can be added. Each SRF has a local oscillator operating at the frequency necessary to decode the data stream. The output of the SRF is then input into detector 1104. The output of detector 1104 is the desired data stream.
The super-resonant filter has advantages over prior art spike filters. One such advantage is the fast settling time of the super-resonant filter. The prior art spike filters take a long time to settle. For example, a 1 hertz narrow pass filter requires one second before its operation is complete. The SRF transmits only a single frequency at a specific phase of a sinusoidal input. The inputs may include noise which is itself a compilation of signals. The input may also include functions of sine waves such as the integral of a sine or cosine wave.
The system operates on samples of the input signal. The sample intervals are much smaller than the period of the complete operation. The process therefore operates over one symbol period or less so there is no coherent relationship between successive symbol periods. Each symbol period starts afresh, although within the symbol period there may be several frequencies which may be recoverable by separate filters.
As shown in
In circuit 1004, the x2 operation provides sinusoids whose angle has doubled, i.e., x=a sin a becomes x2=a2 sin2 a or a2(sin 2a−1). When this signal is multiplied by the output of the local oscillator 1005 outputting a signal of sine a, the result is a2 sine a. This signal is exactly in phase with the input signal.
It should be noted that the sample of the signal is also in phase with the local oscillator f0. When the sample is delayed by one sample period (1/n), it adds to the newly received sample period. However, before this addition takes place, the square root of a2(sin 2a-1)sine a which results in a sin a. Because the square root process removes the sign, it is necessary to ensure that the output of the square root process has the input sign restored.
When the local oscillator frequency is not exactly equal to the incoming frequency and phase, the operation is different. When the local frequency angle is a+Φ, the output angle is 2a−a−Φ which equals a−Φ and when the local frequency angle is a−Φ, the output angle is a+Φ so whether the incoming signal frequency is above or below the desired locally selected frequency, the feedback delayed signal is out of phase with the input signal and does not add.
The addition of the samples amounts to an integration of the selected sinusoidal wave resulting in a peak signal of n/2π. The sample amplitudes are large over a 30° interval. Thus, the integration is most intense near the peaks of the input signal.
The integration of sequential sampling pulses requires that the spectrum of each overlap the other at the information channel frequency. Only this spectrum is needed to develop and transfer the information across the channel. Thus, the entire spectrum of the sampling pulse is not required. A Z-transformation analysis leads to the same results.
a shows an alternate embodiment of an SRF to reduce the third harmonic from the output signal. As shown, in place of a third harmonic generator 1008 the absolute value (1032) of the local oscillator is multiplied at multiplier 1020 with the output of adder 1003. The output of multiplier 1020 is then reintroduced using adders 1026 and 1028 to reduce the third harmonic in the output signal. Components 1022 and 1024 are used to apply the output of multiplier 1020 to adders 1026 and 1028 respectively and terminals 1034 and 1030 are output terminals for multiplier 1020 and adder 1028.
In another embodiment of the invention, an exploded suppressed carrier SRF (ESC-SRF) shown in
The ESC-SRF eliminates the need for the square root function. In one embodiment, the ESC-SRF uses a lower clock rate digital circuitry than the previous SRF architecture and the number of daisy chain stages can be lower than the number of per-symbol iterations in the SRF. Additionally, the ESC-SRF can be used in the receiver side thereby eliminating the need for transmit side additional circuitry including another SRF or ESC-SRF. As shown in
In one embodiment of the circuit shown in
The equations below derive the open-loop behavior, and without the square root function referring to FIG. 12.
IN=cos(ωnΔt) (1)
LO=cos(ω0nΔt) (2)
A=IN(feedback loop is open) (3)
B=A2=cos2 (ωnΔt) (4)
Using the identity below, substitute into eq. (4)
cos2 (a)=(½)+(½)cos(2a)
B=(½)+(½)cos(2ωnΔt) (5)
C=B*LO={(½)+(½)cos(2ωnΔt)}*cos(ω0nΔt) (6)
C=(½)cos(ω0nΔt)+(½)cos(2ωnΔt)*cos(ω0nΔt) (7)
Substituting the following into eq. (7)
ω=ω0+Δω
C=(½)cos(ω0nΔt)+(½)cos(2(ω0+Δω)nΔt)*cos(ω0nΔt) (8)
Using the identity below, substitute for the second term of eq. (8)
cos(a)*cos(b)=(½){cos(a+b)+cos(a−b)}
where a=2(ω0+Δω)nΔt
and b=ω0nΔt, we get
C=(½)cos(ω0nΔt)+(½)(½){cos(2(ω0+Δω)nΔt+ω0nΔt)+cos(2(ω0+Δω)nΔt−ω0nΔt) (9)
Simplifying the above, we get
C=(½)cos(ω0nΔt)+(¼)cos(3ω0nΔt+2ΔωnΔt)+(¼)cos (ω0nΔt+2ΔωnΔt) (10)
Finally, and assuming that we subtracted o.5*LO amplitude at this stage, then
D=C−(½)icos(ω0nΔt) (11)
The exponent “i” determining the LO-subtraction is removed blow, as we are analyzing a single stage. The value of that exponent is fixed for each stage. Refer to
Substituting eq. (11) into eq. (10), and simplifying, we get
D=(¼)cos(3ω0nΔt+2ΔωnΔt)+(¼)cos(ω0nΔt+2ΔωnΔt) (12)
Since we are not using the square root block, then the output and D are the same.
Equation (12) shows that for an input ω0+Δω, the output results into two frequency components, one at a very high frequency of (3 ω0+2Δω) and the other “baseband” component (ω0+2Δω).
One of the fundamental operations of the G function in the ESC-SRF is to take-in an “off-center” frequency, and to shift that frequency further away from the center; hence the input (ω0+Δω) becomes a (ω0+2Δω) component, having been shifted in frequency by an additional (Δω) in the first stage. The amount of frequency shift is equal to (2iΔω) for i-stages. Additionally, the amplitude of the continuously-shifted result of an off-center input is attenuated by a factor about 2i, although this attenuation is also the same for center-frequency case. Hence, the operation of the ESC-SRF is different from the SRF also in that the amplitude of the center-frequency does not build-up, but rather that the off-center frequency is shifted into higher frequencies. This allows a conventional low pass filter to reduce its amplitude drastically.
For the case where the input is at the center frequency, we have Δω=0, ω=ω0. In this case, equation (12) reduces to:
D=(¼)cos(3ω0nΔt)+(¼)cos(ω0nΔt) (13)
First, a generalized 2-sinusoid (called J and K) equation when squared for node B is derived.
A=IN=cos(J)+cos(K) (20)
B=(cos(J)+cos(K) )2 (21)
B=cos2(J)+2cos(J)*cos(K)+cos2(K) (22)
Using the identity cos2(X)=½*(1+cos 2X), we get
B=½+½ cos(2J)+2 cos(J)*cos(K)+½+½ cos(2K) (23)
Using the identity cos(X)*cos(Y)=½(cos(X+Y) ), and simplifying, we get
B=1+½ cos(2J)+½ cos(2K)+cos(J+K)+cos(J−K) (24)
It should be noted that these are fixed factors.
The above equation is used in the graphical representation to show the spectrum of node B for the second iteration. Note that the first time is DC, then next 2 terms are the double-frequency cases, the next term is a high frequency case, and finally, the last term represents a component that generally falls within the band of interest.
The LO subtractor module now subtracts an amount of 1.25 time the input baseband amplitude (or, in absolute terms, 0.3125). The determination of the LO reduction in each stage has not yet been fully derived. It appears to have the form of
LO-reduction=0.25+0.25n
Focusing on the “baseband” output of the second stage, the relative amplitude of the two cases are substantially equal, but the off-center input's offset is shifted by another factor of 2 to its new frequency of ω0+4Δω. This trend continues follows:
ω(n)=ω0+2Δω
Note that the output amplitude is now smaller, but substantially equal for both “baseband” frequency components.
This third stage analysis of the ESC-SRF is somewhat more complex, given that its input now has either 4 or 5 sinusoidal elements. The main ones being the desired baseband signal and others no lower than 3ω0. If the higher frequency elements are eliminated, although such an intermediate LPF is not shown in the block diagram, then the resulting output for the center frequency case would be a yet-lower amplitude ω0 components along with its attendant high frequency elements, and the off-center frequency case would yield a baseband term of ω0+8Δω.
After a sufficient number of stages, the xΔω component itself becomes a high-frequency term that the LPF eliminates.
It should be noted that in operation, the bit error rate of the SRF does not improve significantly as n increases even though the output signal amplitude does increase with n because the noise level at the operating frequency increases correspondingly. Therefore, the output signal-to-noise ratio does not improve.
The signal-to-noise ratio performance can be improved at the receiver using a canceller circuit. Signals that are received but not processed by an SRF unit at the transmit point are essentially sinusoid signals. Use of a canceller in the receiver can provide outputs that are free of interfering channels, i.e., other data streams that don't operate at the specific frequency chosen for the desired data stream. However, such an output is not free of noise signals occurring at the desired stream frequency.
The noise signal can be greatly reduced by the use of an SRF unit operating at the desired frequency. Such a unit discriminates on a time or phase basis between signal and noise. The noise signal, though at the same frequency as the signal, is very infrequently at the same phase as the signal. In fact, it is likely to be at the same phase 1 out of 1000 times or less. The effectively increases the signal-to-noise ratio by a corresponding amount approximately 20-30 dB. The noise improvement can also augment the improvement obtained from the transmit SRF.
The SRF is useful in the receiver shown in
Using the same wave, the disclosed invention transforms that pulse and changes the spectrum to almost a line. Thus, approximately 16 Mbits can be processed in 1 microsecond. When each bit is spaced at 10 hertz, each sample of a vector acts as the whole vector. The signal appears as a spike but it is a result of the integration of many samples.
The inventive digital system is a transfer function that causes a possible differential phase shift for various input frequencies. Each frequency is processed independently. The transfer function is repeated numerous times within each sample period. The result is an output where each input frequency is discriminated from one another. The repetition is performed in a closed loop, i.e., the SRF, a sequential series of circuits, i.e., ESC-SRF, or another implementation of a forward transfer function with a cumulative property.
The circuit implementation for the various embodiments can be done using single or multiple physical circuits. Design choices will dictate the use of feedback looping, daisy-chaining, pipelining, or other methods where circuit complexity and operating frequency are considered. Additionally, DSP chips or FPGAs can be used to do the processing which would include the accumulation of differential phase. Further, a processor programmed to perform the apparatus algorithm can be used to implement the disclosed system.
Although the present invention has been described in relation to particular embodiments thereof, many other variations and other uses will be apparent to those skilled in the art. It is preferred, therefore, that the present invention be limited not by the specific disclosure herein, but only by the scope of the claims.
This application is based on and incorporates herein by reference, provisional patent application Nos. 60/440,952, filed Jan. 17, 2003; 60/440,951, filed Jan. 17, 2003; 60/440,954, filed Jan. 17, 2003; and 60/440,955, filed Jan. 17, 2003.
Number | Name | Date | Kind |
---|---|---|---|
4534257 | Mitarai | Aug 1985 | A |
4601046 | Halpern et al. | Jul 1986 | A |
4857928 | Gailus et al. | Aug 1989 | A |
4937868 | Taguchi | Jun 1990 | A |
4985683 | O'Neill | Jan 1991 | A |
5162812 | Aman et al. | Nov 1992 | A |
5777909 | Leung et al. | Jul 1998 | A |
5822370 | Graupe | Oct 1998 | A |
5956372 | Vaman et al. | Sep 1999 | A |
6226356 | Brown | May 2001 | B1 |
6333763 | Tanaka | Dec 2001 | B1 |
6493409 | Lin et al. | Dec 2002 | B1 |
6665338 | Midya et al. | Dec 2003 | B1 |
20030219085 | Endres et al. | Nov 2003 | A1 |
Number | Date | Country | |
---|---|---|---|
20040208271 A1 | Oct 2004 | US |
Number | Date | Country | |
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60440952 | Jan 2003 | US | |
60440951 | Jan 2003 | US | |
60440954 | Jan 2003 | US | |
60440955 | Jan 2003 | US |