Patent Publication Number: US-11398939-B2

Title: Dimensioning approach for data networks

Description:
BACKGROUND 
     Cable data networks have evolved throughout the years to the current fairly complex system that DOCSIS 3.1 represents. The DOCSIS 3.1 multicarrier system has a variety of sources of overhead that have to be taken into account when estimating capacity. The introduction of profiles has introduced a new layer of complexity as each profile, depending on its traffic characteristics and the channel conditions of its related end-devices, will have its own efficiency estimate. The determination of resources consumed allows cable operators to determine how to best assign spectrum, network device ports and how to configure the network devices to meet desired performance levels for their subscribers. It is also a tool for operators to determine the appropriate time to upgrade and purchase equipment as the demand for capacity continues to grow. 
     SUMMARY OF THE INVENTION 
     A network dimensioning algorithm for networks, such as that included in DOCSIS 3.1, is described. The algorithm combines per profile traffic characteristics, available bandwidth, legacy coexistence and detail overhead contributions of cyclic prefix, pilots, excluded subcarriers, FEC and bit loading, among other parameters. 
     The present dimensioning approach to data network systems and methods may be implemented externally to the cable modem terminal system (CMTS) and the cable modem (CM) for purposes of collecting data therefrom. In addition, the present system and method may also collect data regarding traffic through the CMTS and CM. The collected data is utilized according to the instructions presented here for the calculation of capacity and efficiency, which may then be used to select the appropriate transmission patterns, and thereby the best balance of efficiency and robustness for a given network path. 
     In an embodiment, in addition to the collection of CMTS configuration parameters that rely on the CMTS&#39;s internal algorithms, the present dimensioning system may also externally optimize the CMTS data based on traffic and channel conditions and then communicate the results back to the CMTS. Based at least in part on the results, the upstream algorithm assesses whether greater efficiencies may be gained by utilizing a lower modulation order body minislot and transmitting through the impairment or by skipping over the impairment and beginning the transmission of an edge minislot. 
     In an example of a downstream embodiment, a similar process to that described above in the upstream embodiments may be used. For example, in the case of a wideband interferer, like LTE ingress, carriers are not automatically excluded. Instead, an ingress level and the OFDM signal level per profile assessment is made to determine the use of FEC and frequency interleaving to overcome, rather than avoid, the wideband interference. 
    
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
         FIG. 1  is a block diagram illustrating one exemplary structure of a profile and overall capacity and efficiency calculator, in an embodiment. 
         FIG. 2  is a flowchart illustrating one exemplary method for a dimensioning approach for downstream data in a data network, in an embodiment. 
         FIG. 3  is one example of a Collect PLC information step from the method of  FIG. 2 , in an embodiment. 
         FIG. 4  is one example of a Traffic Data step from the method of  FIG. 2 , in an embodiment. 
         FIG. 5  is a continuation of the method of  FIG. 2 , in an embodiment. 
         FIG. 6  is a flowchart illustrating one exemplary method for a dimensioning approach for upstream data in a data network, in an embodiment. 
         FIG. 7  is one example of a Data Collect step from the method of  FIG. 6 , in an embodiment. 
         FIG. 8  is one example of a Traffic and FEC impact step from the method of  FIG. 6 , in an embodiment. 
         FIG. 9  is a graph illustrating a roll-off window and legacy/OFDM separation optimization, in an embodiment. 
         FIG. 10  shows exemplary upstream Pilot structures in Patterns  1  through  7 , each with body minislots and edge minislots, in an embodiment. 
         FIG. 11  shows exemplary upstream Pilot structures in Patterns  8  through  11 , each with body minislots and edge minislots, in an embodiment. 
         FIG. 12  shows exemplary upstream Pilot structures in Patterns  12  through  14 , each with body minislots and edge minislots, in an embodiment. 
         FIGS. 13-17 , which show an exemplary upstream FEC efficiency Calculator, should be viewed together. 
         FIG. 13  is one exemplary table showing results for an upstream FEC Efficiency Calculator, in an embodiment. 
         FIG. 14  shows formulas utilized in the table of  FIG. 13  for the upstream FEC Efficiency Calculator, in an embodiment. 
         FIG. 15  is one exemplary table showing results for an upstream FEC Efficiency Calculator, in an embodiment. 
         FIG. 16  shows formulas utilized in the table of  FIG. 15  for the upstream FEC Efficiency Calculator, in an embodiment 
         FIG. 17  is a graph illustrating an Upstream Efficiency vs. Information size in bytes as determined by the upstream FEC efficiency calculator of  FIGS. 13-16 , in an embodiment. 
         FIG. 18  is a graph illustrating an Upstream Efficiency vs. Codeword size in bytes as determined by the upstream FEC efficiency calculator of  FIGS. 13-16 , in an embodiment. 
         FIGS. 19-25E , which show an exemplary DOCSIS 3.1 upstream efficiency calculator, are best viewed together. 
         FIG. 19  shows field data and references used in a DOCSIS 3.1 efficiency calculator, in an embodiment. 
         FIGS. 20A-25E  are aspects of the DOCSIS 3.1 upstream efficiency calculator. 
         FIGS. 26-30  are best viewed together. 
         FIG. 26  shows aspects of the DOCSIS 3.1 upstream efficiency calculator of  FIGS. 19-25E  shown in detail, in an embodiment. 
         FIGS. 27-30  are aspects of the DOCSIS 3.1 upstream efficiency calculator of  FIG. 26  shown in detail. 
         FIGS. 31-35  are best viewed together. 
         FIGS. 31-33C  are a plurality of upstream use cases showing results of the of applied algorithms, in an embodiment. 
         FIG. 33D  shows a mixing calculator, the formulas of which are shown in  FIG. 35 , which calculates transmission rates for each of the  4   a - 6   b + cases for mixing of DOCSIS 3.1 and 3.0 systems at a 5% mixing penalty. 
         FIG. 34  shows use cases  1 ,  4   a  and  4   a + of  FIG. 31  with results replaced by formulas that produce those results, in an embodiment. 
         FIG. 35  shows an aspect of  FIG. 33D  with results replaced by formulas that produce those results, in an embodiment. 
         FIGS. 36A-B  show downstream use cases, with results ( FIG. 36A ) and formulas ( FIG. 36B ) that produce those results. 
         FIGS. 37A-B  show upstream use cases, with results ( FIG. 37A ) and formulas ( FIG. 37B ) that produce those results. 
         FIG. 38  is a portion of a DOCSIS 3.1 downstream efficiency calculator showing results of calculations, in an embodiment. 
         FIG. 38A  shows formulas that produce the results shown in  FIG. 38 . 
         FIG. 38B  is a portion of a DOCSIS 3.1 downstream efficiency calculator showing results of calculations, in an embodiment. 
         FIGS. 38C-D  and  39  show formulas that produce the results shown in  FIG. 38B . 
         FIGS. 39A-J  are best viewed together. 
         FIGS. 39A-G  show aspects of a downstream bit loading, pilots, and exclusions calculator in detail showing formulas and results produced by those formulas. 
         FIG. 39H  is a 4K FFT Diagram at a subcarrier spacing of 50 KHz, in an embodiment. 
         FIG. 39I  is an 8K FFT Diagram at a subcarrier spacing of 25 KHz, in an embodiment. 
         FIG. 39J  is an 8K FFT Diagram at a subcarrier spacing of 25 KHz with alternating pilots, in an embodiment. 
     
    
    
     DETAILED DESCRIPTION OF THE FIGURES 
     Cable data networks have evolved throughout the years to their current level of complexity, as described in the DOCSIS 3.1 implementation. This multicarrier data network system has a plurality of overhead sources that must to be taken into account when calculating system capacity. Adding profiles has introduced an extra layer of complexity due to the fact that efficiency estimates are profile dependent. That is, each profile depends on at least data traffic characteristics and end-device channel conditions. A diagram showing some general dependencies that may be taken into account is shown in  FIG. 1 . 
       FIG. 1  shows some of the general parametric dependencies for dimensioning a DOCSIS 3.1 network. A more detailed description of the network dimensioning process in the downstream and upstream directions may be calculated by modeling, for example, user traffic characteristics and conditions that exist on network channels. These details are expanded on in the following description and associated figures. 
       FIG. 1  shows the basic structure of a profile and overall capacity and efficiency calculator  100  in an embodiment. System  100  includes a user population  102 , which influences profiles&#39; services and applications  104 , profiles&#39; packet size distributions  106 , and profiles&#39; channel conditions  108 . Profiles&#39; services and applications  104  and packet size distribution  106  influence profiles&#39; traffic signatures  110 . Profiles&#39; channel conditions  108  influence profiles&#39; configuration parameters  112 . Profiles&#39; traffic signatures  110  and profiles&#39; configuration parameters  112  together are inputs into a capacity estimation function  114 , which in turn outputs a per profile overall capacity and efficiency  116 . 
     The user population  102  is a group of data service users that as an aggregate has specific transmission characteristics. The user population sharing specific network configuration parameters, channel conditions and traffic characteristics is used to estimate the network resources it consumes. 
     The services and applications  104  are defined as follows. A service is defined as a two-way data connection to a subscriber that meets specific levels of performance and is associated to certain traffic characteristics. In this context, an application is a specific purpose program that uses a two-way data connection and is also associated with certain traffic characteristics. 
     The packet size distribution  106  describes the different packet length statistics in bytes or bits of upstream or downstream transmissions. This distribution provides insight on transport efficiency as the overhead of a shorter packet is different than the overhead of a longer packet. 
     The channel conditions  108  indicate the noise, distortion and other unwanted signal characteristics occupying the different portions of the channel spectrum. The channel conditions provide the necessary information to decide how to use the channel and transmit the desired information carrying signals. 
     Traffic signatures  110  describe the transmission characteristics using attributes such as number of packets in transmission, packet duration or length (packet size distribution) and period of time of transmission. Traffic signatures can be defined for individual subscriber transmissions, for transmissions related to specific services or applications or by any selection or grouping of subscribers or traffic. 
     Configuration parameters  112  indicate the operational settings selected by operators or automatically set by the network equipment. 
     The capacity estimation function  114  estimates the effective capacity available from the network under the conditions assumed and configurations selected. It is a collection of algorithms that use a diversity of inputs such as configuration parameters and traffic signatures to provide the effective capacity. 
       FIGS. 2-5  show a downstream network dimensioning method  200  utilized in a data network. The present embodiment is described for use in a DOCSIS 3.1 environment, although it will be understood that the present method may be adapted to other data networks without departing from the scope herein. The methods of  FIGS. 2-8  are represented in one embodiment by the graphs, spread sheets, and algorithms shown in  FIGS. 9-39J . 
     Step  202  starts method  200 , which then moves to step  204 . 
     In step  204 , method  200  identifies the legacy use of spectrum and node capacities to determine the total downstream DOCSIS 3.1 occupied spectrum in nodes. Method  200  then moves to step  206 . 
     In step  206 , method  200  determines both the unused spectrum and unusable spectrum within the total occupied spectrum of the data network. Method  200  then moves to step  208 . 
     In step  208 , method  200  examines the first (or the next) i-th channel, for example, utilizing a downstream FFT function. Method  200  then moves to step  210 . 
     In step  210 , method  200  collects PLC data. Method  200  then moves to step  212  where method  200  collects traffic data. Examples of method steps  210  and  212  are shown in detail in  FIGS. 3 and 4 , respectively. Method  200  then moves to step  214 . 
     In step  214 , method  200  utilizes cyclic prefix data and net symbol period data to determine a time efficiency which may be represented, for example, as a percentage. Method  200  then moves to step  216 . 
     In step  216 , method  200  determines the modulated bandwidth of the system and stores the upper bound for a number of subcarriers in, for example, a temporary storage variable “S”. Method  200  then moves to step  218 . 
     In step  218 , method  200  utilizes the occupied bandwidth and guard band or encompassed bandwidth to determine an upper and a lower active sub-carrier frequency. Method  200  then moves to decision step  220 . 
     In decision step  220 , method  200  determines if the occupied bandwidth and guard band are available. If step  220  determines that the occupied bandwidth and guard band are available, then method  200  moves to step  222 , where method  200  utilizes the occupied BW and guard band or the encompassed bandwidth to determine upper and lower active subcarriers frequencies. Method  200  then moves to the first step of  FIG. 5 . If it is determined in step  220  that no occupied bandwidth and guard bands are available, then step  220  moves to step  224 , where method  200  updates the potential subcarriers variable “S” from the encompassed bandwidth. One example of updating the “S” variable is by performing the calculation:
 
[((Upper edge active subcarrier frequency)−(lower edge active subcarrier frequency))/subcarrier spacing]
 
     Method  200  then moves to the first step of  FIG. 5 . 
       FIG. 3  shows method  300 , which is one example of step  210  of  FIG. 2 , shown in detail. Step  210  is a step of collecting PHY Link Channel (PLC) information. In step  302 , method  300  first determines the subcarrier spacing of the i-th channel from PLC acquisition. 
     In step  304 , method  300  retrieves the cyclic prefix of the i-th channel. 
     In step  306 , method  300  determines the roll-off window of the i-th channel. 
     In step  308 , method  300  determines lower and upper edges of the i-th channel. 
     In step  310 , method  300  determines the number of excluded subcarriers of the i-th channel. 
     In step  312 , method  300  calculates the aggregate bandwidth of the excluded sub-bands for the i-th channel. 
     In step  314 , method  300  determines all of the “M” profile&#39;s bit-loading vs. frequency for the i-th channel. 
     In step  316 , method  300  retrieves the number of continuous pilots outside of the PLC in the i-th channel. 
     In step  318 , method  300  adds eight (8) to the outside PLC continuous pilots to generate a total number of continuous pilots. 
     In step  320 , method  300  calculates the number of staggered pilots in the i-th channel. 
     In step  322 , method  300  determines the number of PLC subcarriers. The number of PLC subcarriers is 8 for a subcarrier spacing of 50 KHz and is equal to 16 for a subcarrier spacing of 25 KHz. 
     Method  300  then moves to step  212  of method  200 ,  FIG. 2 . 
       FIG. 4  shows method  400 , which is one example of step  212  of  FIG. 2 , shown in detail. Step  212  is a step of collecting network traffic data. In step  402 , method  400  estimates a profile cycling period for each of the M profiles in i-th channels. 
     In step  404 , method  400  determines the number of users for each of the M profiles in i-th channels. 
     In step  406 , method  400  measures the volumes in bytes for each of the M profiles in i-th channels. 
     In step  408 , method  400  measures the average number of packets for each of the M profiles in i-th channels. Method  400  then moves to step  214  of method  200 ,  FIG. 2 . 
       FIG. 5  is a continuation of the method of  FIG. 2 , in an embodiment. Steps  222  or  224  of method  300  move to step  502  of  FIG. 5 , starting method  500 . 
     In step  502 , method  500  subtracts the excluded subcarrier to update the “S” variable. 
     In step  504 , method  500  converts the excluded bands to subcarriers and subtracts them from the “S” variable to further update it. 
     In step  506 , method  500  subtracts the continuous pilots that are not in the 6 MHz PLC from the “S” variable to further update it. 
     In step  508 , method  500  subtracts the 8 continuous pilots that are in the 6 MHz PLC from the “S” variable to further update it. 
     In step  510 , method  500  subtracts the staggered/scattered pilots that are in the 6 MHz PLC from the “S” variable to further update it. 
     In step  512 , method  500  determines the number of PLC subcarriers. The number of PLC subcarriers is 8 for a subcarrier spacing of 50 KHz and is equal to 16 for a subcarrier spacing of 25 KHz. 
     In step  514 , method  500  determines the frequency efficiency by dividing the value stored in the “S” variable by the occupied bandwidth, which results in the frequency efficiency which may be represented, for example, as a percentage. 
     In step  516 , method  500  utilizes the profile bit loading to determine the available raw bits for each profile/symbol. 
     In step  518 , method  500  utilizes the Forward Error Correction (FEC), for example, using LDPC &amp; BCH parity bits: 1968 bits, Info bits=14323 bits, Full Length CW bits=16200, to determine a 1st pass at an estimated effective number of bits available for each profile/symbol. 
     In step  520 , method  500  utilizes the number of profiles, volume traffic consumption per profile, and profile cycle duration to determine the average number of symbols per profile cycle to estimate the number of full and shortened codewords for each profile. 
     In step  522 , method  500 , based on number of full and shortened codewords, the number of NCP messages, and the number of subcarriers used for NCP Messages, adjust, in a second pass, the estimated effective number of bits available for each profile/symbol after including NCP Overhead. 
     In step  524 , method  500  utilizes the number of effective bits in a profile, multiplied by the time efficiency and divided by the product of occupied bandwidth and symbols/profile, to obtain the effective efficiency in b/s/Hz in each of the profiles. 
     In step  526 , method  500  multiplies the efficiency in each profile by the occupied bandwidth to determine a profile throughput in b/s. 
     In step  528 , method  500  (and  200 ) determines if method  500  has completed its process of all i-th channels. If method  500  determines it has not completed the process, method  500  moves to step  208  of  FIG. 2 , otherwise, method  500  ends. 
       FIGS. 6-8  show an Upstream Network Dimensioning method in a DOCSIS 3.1 embodiment. The method of  FIGS. 6-8  is represented in one embodiment by the spread sheets, graphs, and algorithms of  FIGS. 9-37B . 
     Step  602  starts method  600 . 
     In step  604 , method  600  determines total upstream DOCSIS 3.1 occupied spectrum in a node based on legacy use of spectrum and node capacities. 
     In step  606 , method  600  determines what portion of the total occupied spectrum is the unused spectrum and the unusable spectrum. 
     In step  608 , method  600  examines the first i-th channel, if this is the first pass through the method; otherwise method  600  examines the next i-th channel. This examination process may be performed, for example, using an upstream FFT Block. 
     In step  610 , method  600  collects data. One exemplary data collection step  610  is shown in detail in  FIG. 7  as data collection  700 . 
     In step  612 , method  600  utilizes cyclic prefix and net symbol period to determine time efficiency, for example, as a percentage. 
     In step  614 , method  600  determines traffic and FEC impact. One exemplary step  614  is shown in detail in  FIG. 8  as data collection  800 . 
     In step  616 , method  600  calculates a total # of body and edge minislots in each M profile from the number of grants per profile plus the number of additional edge minislots. 
     In step  618 , method  600  calculates raw bit capacity for each M profile from profile modulation and pilot pattern versus frequency information. 
     In step  620 , method  600  utilizes an effective code rate calculation for each of the profiles to calculate an effective bit capacity after FEC overhead. 
     In step  622 , method  600  determines efficiency in b/s/Hz for each of the M profiles utilizing time efficiency and occupied bandwidth metrics. 
     In step  624 , method  600  determines a profile throughput in bits/sec by multiplying efficiency in each profile by the occupied bandwidth. 
     In decision step  626 , method  600  determines if it is done with all i-th channels. If in step  626  it is determined that method  600  is not done with all i-th channels, it moves to step  610 , and otherwise method  600  ends. 
       FIG. 7  is a method  700 , which is one example of step  610  of  FIG. 6 , shown in detail. In step  702 , method  700  determines the subcarrier spacing of an i-th channel. 
     In step  704 , method  700  determines the i-th channel&#39;s cyclic prefix. 
     In step  706 , method  700  determines the i-th channel&#39;s roll-off window. 
     In step  708 , method  700  determines the i-th channel&#39;s lower and upper edges. 
     In step  710 , method  700  calculates potential # of subcarriers and stores it in temp variable “S” based on the retrieved i-th channel&#39;s lower and upper edges. 
     In step  712 , method  700  determines minislot parameters, for example, the number of subcarriers, the number of symbols, etc. 
     In step  714 , method  700  calculates the frame duration from “K”, the symbols per frame. 
     In step  716 , method  700  determines a list of intelligent occupancy of upstream spectrum by legacy systems on the network, including center frequency, bandwidth, and expected modulation order. 
     In step  718 , method  700  calculates the minimum gaps required for legacy systems on the network and determines the position and width of excluded sub-bands. 
     In step  720 , method  700  determines the position of excluded subcarriers based on signal-to-noise-ratio (SNR). 
     In step  722 , method  700  determines the guard band(s) required. 
     In step  724 , method  700  determines a list of usable body and gap-related-edge minislots (a.k.a. additional edge minislots) in the i-th channel, from the guard band, excluded subcarriers and excluded sub-bands, such that a minislot generation efficiency is determined. 
     In step  726 , method  700  calculates, for each of the profiles, the effective bit capacity after FEC overhead utilizing the effective code rate. 
     In step  728 , method  700  determines the per profile effective code rate. 
     Method  700  then moves to step  612  of  FIG. 6 . 
       FIG. 8  is a method  800 , which is one example of step  614  of  FIG. 6 , shown in detail. In step  802 , method  800  measures a packet size distribution and a volume of traffic in the profiles. 
     In step  804 , method  800  calculates the number of minislots required for each burst size biased on packet size distribution and configuration. 
     In step  806 , method  800  calculates the number of minislots required for each burst size based on the traffic generated in each profile. 
     In step  808 , method  800  calculates the aggregate number of minislots consumed per profile. 
     In step  810 , method  800  calculates the number of simultaneous grants per profile based on traffic characteristics and configuration. 
     In step  812 , method  800  calculates the per packet size effective code rate. 
     In step  814 , method  800  determines the per profile effective code rate. 
     Method  800  then moves to step  616  of  FIG. 6 . 
       FIG. 9  shows one exemplary relationship between legacy and OFDM systems such that they may coexistence on the same network. For example, where the location and modulation order of legacy channels are known or determined, the present system determines an optimization. The separation of legacy and OFDM systems is based on the CNR required by the legacy channel, the amount of adjacent OFDM/OFDMA noise that a particular roll-off window configuration implies, and a separation  902  of the legacy signal to the closest active OFDM/OFDMA subcarrier. The roll-off window requires additional samples that are added to the symbol and have the effect of lowering the energy adjacent to the signal by rolling-off and decreasing the adjacent energy in amplitude at a higher rate than the traditional configured scenario without the additional roll-off samples. This reduces the total amount of energy in the adjacent channel and allows the adjacent portion of the spectrum be occupied by another signal such as a legacy DOC SIS signal. Graph  900  of  FIG. 9  shows one example of such a scenario in an up-stream embodiment having a roll-off window and legacy/OFDM separation  902  optimization. In this example, a 64 QAM DOCSIS legacy system that requires 27 dB CNR coexists with an OFDMA system, which operates at a specific power level/bandwidth that is located at a specific frequency separation from the edge of the legacy signal. The time overhead needed in the form of Cyclic Prefix is calculated using an adjacency optimization algorithm plus the delay spread that is obtained from the channel conditions. 
       FIGS. 10-12  show upstream patterns  1 - 14  each having specific pilot structures, minislot configurations, etc. as known in the art. The present systems and methods may select the appropriate pattern based on network characteristics. 
       FIGS. 13 and 14  show the same spread sheet, although  FIG. 14  shows the functions that produce the results shown in  FIG. 13 . Both  FIGS. 13 and 14  show the Transmission Payload Range in Bytes, the Codeword types and associated information bits, the transmission payload range in bits, and the Codeword types.  FIGS. 13 and 14  also show the codeword bits, parity bits, payload bits, efficiency, payload bytes and parity bytes associated with the long, medium and short Codeword types. 
       FIGS. 15 and 16  show the same spread sheet, although  FIG. 16  shows the functions that produce the results shown in  FIG. 15 .  FIGS. 15 and 16  show the spread sheet which correlates the calculated efficiencies with calculated code word bytes, information bits, information bytes, and codeword type (short, medium and long). 
       FIG. 17  is a graph of Efficiency vs. Information Size (in bytes) as calculated by the spreadsheet of  FIGS. 13-14 . 
       FIG. 18  is a graph of Efficiency vs. Codeword Size (in bytes) as calculated by the spread sheet of  FIGS. 15-16 . 
       FIG. 19  shows field data and references used in a DOCSIS 3.1 efficiency calculator.  FIGS. 20A-25E  are aspects of the DOCSIS 3.1 upstream efficiency calculator. 
       FIGS. 20A and 20B  show the same spread sheet, although  FIG. 20B  shows the functions that produce the results shown in  FIG. 20A . 
       FIGS. 21A and 21B  show the same spread sheet, although  FIG. 21B  shows the functions that produce the results shown in  FIG. 21A . 
       FIGS. 22A and 22B  show the same spread sheet, although  FIG. 22B  shows the functions that produce the results shown in  FIG. 22A . 
       FIGS. 23A and 23B  show the same spread sheet, although  FIG. 23B  shows the functions that produce the results shown in  FIG. 23A . 
       FIGS. 24A and 24B  show the same spread sheet, although  FIG. 24B  shows the functions that produce the results shown in  FIG. 24A . 
       FIGS. 25 and 25A-25E  show the same spread sheet, although  FIGS. 25A-E  show the functions that produce the results shown in  FIG. 25 . 
       FIG. 26  is a spreadsheet for determining DOCSIS 3.1 upstream minislot and exclusions. For sake of clarity, portions of the spread sheet of  FIG. 26  are represented in  FIGS. 27-30 .  FIG. 26  shows results produced by the formulas shown in  FIGS. 27-30 .  FIG. 26  also shows excluded subcarrier frequencies  2602 . 
       FIG. 31  shows upstream use cases  1 ,  4   a , and  4   a +. The formulas that produce the results for use cases  1 ,  4   a , and  4   a + are shown in  FIG. 34 .  FIG. 32  shows use cases  4   b ,  4   b +, and  5   a .  FIG. 33A  shows uses cases  5   a +,  5   b  and  5   b +.  FIG. 33B  shows use cases  6   a  and  6   a +.  FIG. 33C  shows use cases  6   b , and  6   b +. In addition,  FIG. 33D  also shows a mixing calculator, the formulas of which are shown in  FIG. 35 , which calculates transmission rates for each of the  4   a - 6   b + cases for mixing of DOCSIS 3.1 and 3.0 systems at a 5% mixing penalty. 
       FIGS. 36A  and B show 1-3 downstream use cases for ANGA and A-C downstream uses cases for Comcast.  FIG. 36B  shows the formulas that produce the results presented in  FIG. 36A .  FIG. 36A  also shows a DOCSIS 3.1 uses case B-Poor, with a graphical representation for the time, guardband, Pilot &amp; PLC, NCP, FEC, MAC, and Payload data. For sake of clarity, this graph has been removed from  FIG. 36B . 
       FIGS. 37A and 37B  show upstream use cases  1 - 3  with graphical representation of tie overhead data, legacy, exclusion band, and guardband data, pilot structure overhead, FEC, and PHY payload data.  FIGS. 37A  and B also show graphical representations of downstream time overhead, guardband, Pilot &amp; PLC, NCP, FEC, excluded subcarriers, and PHY payload for ANGA use cases  1 - 3 . 
       FIGS. 38 and 38A  are portions of a DOCSIS 3.1 downstream efficiency calculator. The formulas that produce the results of  FIGS. 38 and 38A  are shown in  FIGS. 38B-D  and  39 . 
       FIGS. 39A-G  show aspects of a downstream bit loading, pilots, and exclusions calculator, in an embodiment.  FIG. 39B  shows the formulas that produce the results of  FIG. 39A .  FIG. 39D  shows the formulas the produce the results shown in  FIG. 39C .  FIG. 39F  shows the formulas that produce the results of  FIG. 39E .  FIG. 39G  shows continuous pilots in PLC data.  FIG. 39H  shows a 4K FFT Diagram having a subcarrier spacing of 50 KHz, in an embodiment.  FIG. 39I  shows an 8K FFT Diagram having a subcarrier spacing of 25 KHz, in an embodiment.  FIG. 39J  shows an 8K FFT Diagram having a subcarrier spacing of 25 KHz with alternating pilots, in an embodiment. 
     Those skilled in the art will appreciate the use of legacy and DOCSIS 3.1 systems, methods and data in its application to the present dimensioning approach to data networks. 
     Changes may be made in the above methods and systems without departing from the scope hereof. It should thus be noted that the matter contained in the above description or shown in the accompanying drawings should be interpreted as illustrative and not in a limiting sense. The following claims are intended to cover all generic and specific features described herein, as well as all statements of the scope of the present method and system, which, as a matter of language, might be said to fall there between.