Noise-independent loss characterization of networks

Abstract

An S-parameter of a reference impedance is determined and converted to a desired mode of operation. Example modes of operation include a single-ended input output mode, a differential input output mode, and a common input output mode. The complex values of the impedance at each port as a function of frequency can be computed using the novel closed-form quadratic S-parameter equation which utilizes the concept of matched networks by setting the reflections and re-reflections to zero through S-parameter renormalization. Using the S-parameter renormalization, the insertion loss corresponding to zero reflections and re-reflections is calculated. Based on the determination of the matching impedance used to reduce the reflections and re-reflections to zero, a parameter of a circuit comprising the network may be modified to reduce noise.

What is claimed is: 
     
         1 . A method comprising:
 accessing, by one or more processors, an S-parameter for a network that comprises a load;   determining, based on the S-parameter, a first possible load reflection coefficient for the network and a second possible load reflection coefficient for the network, the first possible load reflection coefficient having a first magnitude greater than one, the second possible load reflection coefficient having a second magnitude less than or equal to one;   selecting, by the one or more processors, the second possible load reflection coefficient as a load reflection coefficient based on the second magnitude being less than or equal to one; and   based on the load reflection coefficient, modifying a circuit parameter.   
     
     
         2 . The method of  claim 1 , further comprising:
 based on the load reflection coefficient, determining a load characteristic impedance;   renormalizing the S-parameter based on the load characteristic impedance; and   determining, based on the renormalized S-parameter, an effective insertion loss of the network as a function of frequency.   
     
     
         3 . The method of  claim 2 , further comprising:
 determining, based on an insertion loss of the network and the effective insertion loss of the network, an effective insertion loss noise of the network.   
     
     
         4 . The method of  claim 1 , wherein:
 the accessing of the S-parameter comprises accessing the S-parameter from a vector network analyzer.   
     
     
         5 . The method of  claim 1 , wherein:
 the modifying of the circuit parameter of the network based on the load reflection coefficient comprises adjusting an impedance of a component of the network based on the load reflection coefficient.   
     
     
         6 . The method of  claim 1 , wherein:
 the modifying of the circuit parameter of the network based on the load reflection coefficient comprises adjusting an operating frequency of the network based on the load reflection coefficient.   
     
     
         7 . The method of  claim 1 , wherein:
 the modifying of the circuit parameter of the network based on the load reflection coefficient comprises modifying a transceiver of the network based on the load reflection coefficient.   
     
     
         8 . A system comprising:
 a memory that stores instructions; and   one or more processors configured by the instructions to perform operations comprising:
 accessing, by one or more processors, an S-parameter for a network that comprises a load; 
 determining, based on the S-parameter, a first possible load reflection coefficient for the network and a second possible load reflection coefficient for the network, the first possible load reflection coefficient having a first magnitude greater than one, the second possible load reflection coefficient having a second magnitude less than or equal to one; 
 selecting, by the one or more processors, the second possible load reflection coefficient as a load reflection coefficient based on the second magnitude being less than or equal to one; and 
 based on the load reflection coefficient, modifying a circuit parameter. 
   
     
     
         9 . The system of  claim 8 , wherein the operations further comprise:
 based on the load reflection coefficient, determining a load characteristic impedance;   renormalizing the S-parameter based on the load characteristic impedance; and   determining, based on the renormalized S-parameter, an effective insertion loss of the network as a function of frequency.   
     
     
         10 . The system of  claim 9 , wherein the operations further comprise:
 determining, based on an insertion loss of the network and the effective insertion loss of the network, an effective insertion loss noise of the network.   
     
     
         11 . The system of  claim 8 , wherein the operations further comprise:
 the accessing of the S-parameter comprises accessing the S-parameter from a vector network analyzer.   
     
     
         12 . The system of  claim 8 , wherein the operations further comprise:
 the modifying of the circuit parameter of the network based on the load reflection coefficient comprises adjusting an impedance of a component of the network based on the load reflection coefficient.   
     
     
         13 . The system of  claim 8 , wherein the operations further comprise:
 the modifying of the circuit parameter of the network based on the load reflection coefficient comprises adjusting an operating frequency of the network based on the load reflection coefficient.   
     
     
         14 . The system of  claim 8 , wherein the operations further comprise:
 the modifying of the circuit parameter of the network based on the load reflection coefficient comprises modifying a transceiver of the network based on the load reflection coefficient.   
     
     
         15 . A non-transitory machine-readable storage medium containing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
 accessing, by one or more processors, an S-parameter for a network that comprises a load;   determining, based on the S-parameter, a first possible load reflection coefficient for the network and a second possible load reflection coefficient for the network, the first possible load reflection coefficient having a first magnitude greater than one, the second possible load reflection coefficient having a second magnitude less than or equal to one;   selecting, by the one or more processors, the second possible load reflection coefficient as a load reflection coefficient based on the second magnitude being less than or equal to one; and   based on the load reflection coefficient, modifying a circuit parameter.   
     
     
         16 . The non-transitory machine-readable storage medium of  claim 15 , wherein the operations further comprise:
 based on the load reflection coefficient, determining a load characteristic impedance;   renormalizing the S-parameter based on the load characteristic impedance; and   determining, based on the renormalized S-parameter, an effective insertion loss of the network as a function of frequency.   
     
     
         17 . The non-transitory machine-readable storage medium of  claim 16 , wherein the operations further comprise:
 determining, based on an insertion loss of the network and the effective insertion loss of the network, an effective insertion loss noise of the network.   
     
     
         18 . The non-transitory machine-readable storage medium of  claim 15 , wherein the operations further comprise:
 the accessing of the S-parameter comprises accessing the S-parameter from a vector network analyzer.   
     
     
         19 . The non-transitory machine-readable storage medium of  claim 15 , wherein the operations further comprise:
 the modifying of the circuit parameter of the network based on the load reflection coefficient comprises adjusting an impedance of a component of the network based on the load reflection coefficient.   
     
     
         20 . The non-transitory machine-readable storage medium of  claim 15 , wherein the operations further comprise:
 the modifying of the circuit parameter of the network based on the load reflection coefficient comprises adjusting an operating frequency of the network based on the load reflection coefficient.