Abstract:
A receiver with orthogonal beam forming technique is achieved that is capable of differentiating different signal components within the received composite signal. An adaptive processor is used to eliminate the signal component whose phase information is known or can be calculated. The phase information of the major component of a signal can be easily acquired by using a limiter. The phase information of other signal components can be acquired by their direction information and other characteristics, such as modulation scheme, etc. Multiple orthogonal beams can be formed by eliminating one unwanted signal component each time by the adaptive processor until all unwanted signal is eliminated. Thus, a composite signal from multiple sources can be broken down into their component signals.

Description:
RELATED APPLICATION DATA 
       [0001]    This application is a continuation of application Ser. No. 12/951,995, filed on Nov. 22, 2010, now pending, which claims the benefit of U.S. provisional application Ser. No. 61/381,381, filed Sep. 9, 2010. 
     
    
     BACKGROUND OF THE INVENTION 
       [0002]    1. Field of the Invention 
         [0003]    The present invention relates to the fields of wireless communications and antenna architecture and design, and, in particular, to adaptive smart antenna system architectures and designs. More specifically, but without limitation thereto, the present invention aims to create an antenna receiver system that is capable of forming multiple orthogonal beams and differentiating multiple received signals by eliminating signal components whose phase information or other characteristics are known or can be acquired. 
         [0004]    2. Description of Related Art 
         [0005]    In the field of wireless communications, antennas are widely used to transmit or receive data in the form of radio frequency signals from one place to another. Antennas are used in fields such as satellite, radio, television broadcasting, and cellular phone communications, among other things. These antennas can come in all shapes and sizes, ranging from traditional dish antennas, to antenna arrays that utilize multiple elements. 
         [0006]    The performance of an antenna is degraded by the presence of an interfering signal, which can be defined as a signal originating from a source external to the desired signal path that produces undesired artifacts in the signal. This can be intentional interference, such as a jamming signal, or unintentional interference, such as receiving signals from a nearby satellite that is being broadcast on the same frequency. Additionally, when the strength of the interfering signal is too strong the communication quality becomes too low to maintain proper service. 
         [0007]    Interference due to signal transmission on same frequencies can pose a problem for ground terminals attempting to transmit or receive signals from a desired source, such as a satellite. Several schemes have been designed to distinguish between signals. For example, digital and analog filters which may be easily implemented to differentiate received signals with different frequencies are widely used today. However, these systems do not present an adequate solution when the frequency of interfering signals are the same or very close to the desired signal. 
         [0008]    One possible solution to overlapping frequency use is to use smart antennas equipped with digital beam forming (DBF) techniques to distinguish between signals originating from different directions by forming an orthogonal beam in the direction of the desired signal, while simultaneously forming a null at the direction of interfering sources. This provides an adequate solution to frequency use overlap as the antenna only picks up signals from the desired direction. While DBF techniques solve the issue of multi-directional, multi-signal interference, these smart antennas do not adequately solve the issue of multiple signal, differing strength signals being broadcast from relatively close directions 
         [0009]    The present invention takes advantage of the difference of signal strengths, corresponding directional information and other signal characteristics to calculate the phase information of unwanted signals and eliminate them using an adaptive algorithm. Different from other smart antennas utilizing beam-forming techniques, this invention focuses on eliminating unwanted signal components by adaptively minimizing the correlation between a desired signal and any unwanted components. 
       REFERENCES 
       [0000]    
       
         1. Donald C. D. Chang et al, “Multiple Basestation Communication System Having Adaptive Antennas,” Mar. 6, 2007, U.S. Pat. No. 7,187,949 
         2. Ying Feria et al, “Stratospheric-Based Communication System Having Interference Cancellation,” May 18, 2010, U.S. Pat. No. 7,720,472 
       
     
       SUMMARY OF THE INVENTION 
       [0012]    The present invention provides a dynamic communication system suitable for dynamically receiving incoming signals from multiple satellites to a receiver. More specifically, the present invention pertains to an adaptive signal differentiation scheme which is capable of distinguishing between signals by their strength difference and directional information. 
         [0013]    An embodiment of the present invention comprises an antenna receiver system and a signal processing unit. With no limitation thereto, the antenna receiver for the current embodiment is an antenna array. Generally, a plurality of signals are received by the antenna system and then transmitted to the signal processing unit. There the processing unit coherently separates the signals using a system of weighting components and iterative loops, thus creating usable, separate signals. 
         [0014]    Additionally, an embodiment of the present signal differentiation scheme further comprises a limiter, an adaptive processor and a phase alignment module. A limiter is an electronic device which simply converts a data sample greater or equal to zero into 1, and others into −1. Since the phase of a signal is determined mostly by the largest signal component of the signal, the output of the limiter approximately reflects the signal component with the strongest signal strength, and ignores all the amplitude information of input signals. The phase information is transmitted to the adaptive processor where a closed adaptive loop is used to iteratively eliminate the signal component which has the same phase as the strongest signal component, thus eliminating the strongest signal component of the signal. Similarly, other signal components can be eliminated if their phase information is known, or can be calculated, i.e. by their direction of arrival. 
         [0015]    The present invention is not limited to one interfering source. In the case of multiple interfering sources, the present signal differentiation scheme may be applied to elimination of one interfering signal component at a time until all the interference is eliminated or differentiated into their component signals. 
         [0016]    Additionally, other characteristics of a signal component, such as its modulation scheme can also provide useful information to generate an approximation of the signal component which can be used to eliminate the signal component in the adaptive processing. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0017]      FIG. 1  illustrates an embodiment of the structure of the signal differentiation system. 
           [0018]      FIG. 2  shows a general structure of the signal receiver module. 
           [0019]      FIG. 3  illustrates a schematic view of the present signal differentiation system. 
           [0020]      FIG. 4  presents several graphs showing the results of the adaptive signal differentiation algorithm, showing the original signal, suppression of the stronger signal, and suppression of the weaker signal 
           [0021]      FIG. 5  depicts the suppression process of the signal with stronger signal strength 
           [0022]      FIG. 6  illustrates the suppression process of the signal with smaller signal strength. 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
       [0023]    The present invention relates to the field of communications systems and adaptive antenna design. More specifically, but without limitation thereto, the present invention provides an adaptive scheme which is capable of receiving and distinguishing between two or more radio frequency signals with differing signal strengths regardless of transmission directions. 
         [0024]    As shown in  FIG. 1 , in an embodiment of the present invention, radio frequency (RF) signals  103 ,  104  transmitted from satellites  101 ,  102  are received by multiple-element antenna array  105 . The signals from each satellite interfere with each other at the receiver side which means the composite signal received by each antenna element includes signals from both satellites. To distinguish these signals  103 ,  104  from each other, the received composite signal from each antenna element is first down-converted to base band and converted to digital signal  107  by the receiver module  106 , and then transmitted to the digital signal processor  108  which utilizes an adaptive identification scheme to identify both signals  109 ,  110  individually based on their power difference and direction information. 
         [0025]      FIG. 2  shows the general structure of receiver module in the present invention. The high frequency, analog signal  201  from each channel are treated by low noise amplifiers  202 , and then down-converted to baseband by signal down-converters  203 . The baseband analog signals are then converted to digital signals  205  by analog-to-digital (A/D) converters  204  and transmitted to signal identification module  108  as shown in  FIG. 1 . 
         [0026]      FIG. 3  gives the schematic view of our present signal identification scheme utilized by the digital signal processor  108 . Input signals  331  coming from the multiple-element antenna array are routed through two adaptive processes  310 ,  320  which output the signal component with lower power  337 , and the signal component with stronger power  338 , respectively. In the first adaptive process  310 , the composite signal is split, with a portion going to limiter  311 , which converts a positive or zero signal sample into 1 and a negative signal sample into −1, and another portion going to the element weighting processor  313 . 
         [0027]    This invention focuses on eliminating unwanted signal components by adaptively minimizing the correlation between a desired signal and any unwanted components. Limiter  311  is used to generate four approximations  332  of the larger one of two signal components  331  in each channel as one input (the total number of inputs equaling the number of elements in the antenna array) to the adaptive processor  314  adaptively performing minimizing the correlation between a feedback signal  333 , i.e. the above-mentioned desired signal, and approximation  332  of the larger one of the signal components  331 . i.e the above-mentioned unwanted components. The other input  333  from the beam output  337  is generated by applying complex weight  313   a  which is a set of complex number to change the amplitude and phasea to each channel of input signals  331 . The input signals  331  are then processed within iterative loop  312  until certain criteria are reached. In each iteration, the adaptive processor  314  updates the complex weight  313  to generate a new output signal  337 . which also returns to the adaptive processor as feedback via the path  333 . The loop stops either when the correlation of returned signal in the path  333  and approximation  332  of the larger one of the signal components  331  becomes smaller than a preset signal strength threshold, or the number of iterations reaches a predefined number. Since the phase of a signal  331  is determined mostly by the largest signal component of the signal  331 . the output of the limiter  311  approximately reflects the signal component  332  with the strongest signal strength, and ignores all the amplitude information of input signals  331 . The phase information is transmitted to the adaptive processor  314  where a closed adaptive loop  312  is used to iteratively eliminate the signal component which has the same phase as the strongest signal component  332 , thus eliminating the strongest signal component of the signal  331 . Similarly, other signal components can be eliminated if their phase information is known, or can be calculated, i.e. by their direction of arrival. As a result of the iterative processes. the process  310  identifies the smaller signal component in the smaller strength signal  337  output to the second loop to trigger the process  320  which is to identify the large signal component in the signal  338  with the stronger signal strength. 
         [0028]    The second process  320  also includes an adaptive loop  322  which is very similar to the adaptive loop  312  in the first process  310 . The difference is that the input signal to the second loop  335  is an approximation of the signal with smaller signal strength, comparative to one with the larger signal strength  332 . A limiter  321  is used to generate an approximation  334  of the smaller strength signal  333  that is reconstituted at the output by the first adaptive process  310 . A phase alignment module  325  is applied to align the phase of approximation signal  334  with the phase of smaller signal component in each channel of the original input signal  331  by applying four different complex weights to signal  334  according to their phase difference. The phase information of the smaller component of original input signal  331  can be calculated according to the directional or modulation information of the satellites. Similar to the first adaptive loop  312 , the second loop terminates and outputs the stronger signal  338  when the correlation between the feedback  336  and input signal  335  become smaller than a preset threshold. 
         [0029]      FIG. 4  demonstrates the result of our adaptive orthogonal beam forming scheme. Graph  410  shows the spectrum output of the original input signal  331 . Graph  420  illustrates the spectrum output of the first adaptive process  337 , showing how the stronger signal has been reduced to the level of background noise. Graph  430  shows the spectrum output of the second adaptive process  338 , illustrating how the weaker strength signal has been reduced to the level of background noise as well. The frequency axis  416  spans from 0 to 50 MHz (megahertz). The vertical axis  415  which represents the signal strength ranges from 10 dB to 110 dB (decibels). As shown in spectrum graph  410 , the original input signal includes two signal components  411 ,  412  which come from two satellites  101  and  102  as shown in  FIG. 1 . In the present simulation, the signal component  411  has stronger signal strength of more than 90 dB and a lower frequency. Using signals with different frequencies is for demonstration purposes. The present signal differentiation scheme can be adapted for other applications as well, such as differentiating two signals on the same frequencies if directional information of the satellites is known. Spectrums  420 ,  430  show the output of first and second adaptive process, respectively. In comparison with spectrum  410 , only the smaller signal component  422  is left in spectrum  420 , while only the large signal component  431  is shown in spectrum  430 . 
         [0030]      FIG. 5  is a 3-dimensional plot which illustrates the process of eliminating the signal with stronger signal strength in the first adaptive process  310 . Frequency is represented on the x-axis  510 , which ranges from 0 to 50 MHz. Signal strength is represented on the z-axis  520  ranges from 0 dB to 100 dB. The y-axis  530  represents the number of iterations performed to differentiate the signal, ranging from 0 to 8. Before the adaptive process begins (num of iteration=0), the signal component  501  has a larger signal strength than signal component  502 . When the adaptive processing begins, the strength of signal  501  drops significantly with each iteration, eventually stabilizing as signal  503 . At this point, signal  503  is roughly the same strength as the background noise. In comparison to signal  502 , processed signal  503  is not in the same strength range. At the end of the adaptive processing (num of iteration=8), the remainder of the larger signal  503  is close to the noise level, whereas the strength smaller signal  504  has little to no change of signal strength taking place. 
         [0031]      FIG. 6  illustrates the output of each loop of the second adaptive process. Frequency is again represented on the x-axis  610  in megahertz, the number of iterations is represented by the y-axis  630 , and the signal strength in decibels is represented on the z-axis. Contrary to the first adaptive process shown in  FIG. 5 , the signal strength of the larger signal  602  remains relatively unchanged through each iteration. After 8 iterations signal  604  has the same signal strength as when the adaptive process began. However, signal strength of signal  601  dropped dramatically after 8 iterations to signal  603 . Here, signal  603  has roughly the same signal strength as the background noise.