System and methods for non-orthogonal multiple access

A resource allocation method is provided for a non-orthogonal multiple access distribution of access network users communicatively coupled to a single transport medium. The method includes steps of allocating a first frequency and time domain resource to a first user and a second frequency and time domain resource to a second user of the access network users, obtaining channel information regarding a particular communication channel of the access network for which resources are allocated, grouping the first user with the second user based on an overlap of the first frequency and time domain resource with the second frequency and time domain resource, and assigning the first user to a different power allocation resource than the second user within the frequency and time domain overlap.

BACKGROUND

The field of the disclosure relates generally to communication systems and networks, and more particularly, to communications systems and networks employing non-orthogonal multiple access.

Conventional hybrid fiber-coaxial (HFC) architectures typically deploy fiber strands from an optical hub to a fiber node, and often many short coaxial or fiber strands to cover the shorter distances from the fiber nodes to a plurality of end users. Conventional Multiple Service Operators (MSOs) offer a variety of services, including analog/digital TV, video on demand (VoD), telephony, and high speed data internet, over these HFC networks, which utilize both optical fibers and coaxial cables, and which provide video, voice, and data services to the end user subscribers. HFC networks are known to include a master headend, and the optical fiber strands carry the optical signals between the headend, the hub, and the fiber node. Conventional HFC networks also typically include a plurality of coaxial cables to connect the fiber nodes to the respective end users, and to carry radio frequency (RF) modulated analog electrical signals.

The HFC fiber node converts optical analog signals from the optical fiber into the RF modulated electrical signals that are transported by the coaxial cables to the end users/subscribers. In the conventional HFC network, both the optical and electrical signals are analog, from the hub to the end user subscriber's home. Typically, a modem termination system (MTS) is located at either the headend or the hub, and provides complementary functionality to a modem of the respective end user.

The signal components of the conventional HFC fiber/coaxial cable links experience higher propagation attenuation at higher frequency. The attenuation increases over distance and this attenuation effect is particularly significant in coaxial cables. Thus, different users of the network will experience difference system performance at different distances from the fiber node, at different operation frequencies. Conventional HFC networks, however, implement orthogonal multiple access (OMA) techniques to allocate resources orthogonally in the frequency and time domains.

FIG. 1is a graphical illustration depicting a conventional orthogonal multiple access (OMA) two-dimensional frequency-time-power distribution100of users102. In the exemplary embodiment illustrated inFIG. 1, distribution100is depicted with respect to a conventional HFC network that implements a communication protocol such as the Data Over Cable Service Interface Specification (DOCSIS), or DOCSIS version 3.1 (D3.1). In this example, each of the several different users102are illustrated as occupying different frequency-time slots on (e.g., on a 2-D plane) and do not overlap with other users102.

According to conventional OMA distribution100, the OMA techniques of distribution100do not consider the respective variations experienced by users102according to the distance of a particular user102from the node, or the frequency slot at which that user102is operating. More particularly, the conventional OMA techniques do not optimize resource allocation based on these variations, thereby resulting in low spectral efficiency. Accordingly, it is desirable to provide techniques that consider the channel differences of different users and frequencies to optimize network resource allocation, and in an equitable manner, to increase the spectral efficiency and throughput of the network.

BRIEF SUMMARY

In an embodiment, a resource allocation method is provided for a non-orthogonal multiple access distribution of access network users communicatively coupled to a single transport medium. The method includes steps of allocating a first frequency and time domain resource to a first user and a second frequency and time domain resource to a second user of the access network users, obtaining channel information regarding a particular communication channel of the access network for which resources are allocated, grouping the first user with the second user based on an overlap of the first frequency and time domain resource with the second frequency and time domain resource, and assigning the first user to a different power allocation resource than the second user within the frequency and time domain overlap.

In an embodiment, a resource allocation method is provided for a non-orthogonal multiple access distribution of access network users communicatively coupled to a single transport medium. The method includes steps of allocating a first frequency and time domain resource to a first user and a second frequency and time domain resource to a second user of the access network users, obtaining channel information regarding a particular communication channel of the access network for which resources are allocated, grouping the first user with the second user based on an overlap of the first frequency and time domain resource with the second frequency and time domain resource, and assigning the first user to a different code allocation resource than the second user within the frequency and time domain overlap.

DETAILED DESCRIPTION

As used herein, the term “database” may refer to either a body of data, a relational database management system (RDBMS), or to both, and may include a collection of data including hierarchical databases, relational databases, flat file databases, object-relational databases, object oriented databases, and/or another structured collection of records or data that is stored in a computer system.

The present embodiments advantageously improve over the conventional OMA techniques, described above, by implementing non-orthogonal multiple access (NOMA) to expand the channel resource space into a third dimension, namely, that of the power domain (i.e., PD-NOMA) and/or the code domain (i.e., CD-NOMA). The present systems and methods are therefore able to take the channel difference between different users and different frequencies into consideration, and then optimize the resource allocation of the network (e.g., an HFC network) in a more equitable manner. According to the techniques described herein, both the spectral efficiency and the throughput of the network are significantly increased, while also advantageously generating more use cases, and including more classes of users, than may be realized according to the conventional techniques.

FIG. 2is a graphical illustration depicting a non-orthogonal multiple access (NOMA) three-dimensional distribution200of resource blocks202for individual users. Distribution200represents an exemplary three-dimensional space of the resources allocated to various users that may occupy the same frequency-time slot in two dimensions, but which may overlap in a third dimension of power (e.g., PD-NOMA) and/or code (e.g., CD-NOMA). In this example, each resource block202indicates a three-dimensional representation of resources allocated to a particular user. In some cases, multiple different resource blocks202may be allocated to the same user. Techniques for allocating resources to users, and to groups of users, may be performed as described below, for various purposes and according to particular constraints, in order to maximize overall capacity, while also ensuring throughput to individual users and user groups. The following examples are described with respect to an HFC network communication system for ease of explanation, but not in a limiting sense. The person of ordinary skill in the art will understand how the principles of the present embodiments are applicable to other types of communication networks and protocols.

FIG. 3is a flow diagram for an exemplary resource allocation process300for NOMA distribution200,FIG. 2. In the exemplary embodiment, process300may allocate channel resources with respect to an HFC system implementing NOMA. Process300is described herein with reference to an exemplary communication system400illustrated inFIG. 4, below. Except where described to the contrary, the particular order of steps in process300are provided for purposes of illustration, and not in a limiting sense.

In exemplary operation, process300begins at step302, in which a frequency-time resource is allocated to a set of users402(FIG. 4, below). In an exemplary embodiment of step302, the two-dimensional frequency-time portion (i.e., the rectangular area on the frequency-time plane) of each three-dimensional resource block is assigned to users402(six, in this example) that are communicatively connected to a same HFC plant (e.g., transport medium408,FIG. 4, below) belonging to the same service group. In step304, process300obtains channel information regarding the particular channel of communication system400for which resources are allocated. In an exemplary embodiment of step304, the channel information includes the frequency response and signal-to-noise-ratio (SNR)/noise level at each user402.

In step306, based on the channel information, the set of users402are divided into groups. In an exemplary embodiment of step306, each user group is formed of users that occupy the same two-dimensional frequency-time resource, but at a different power/code domain level. Accordingly, in some embodiments, each user402may belong to multiple groups at the same time (e.g., users402(4),402(5),402(6)). In this case, different users402are capable of occupying different amounts of frequency-time resources, that is, different users may have different sizes and shapes of resource blocks202. In an embodiment, user grouping may be performed according to criteria such as maximized capacity, system requirements satisfaction, service level agreement fulfillment, and present or dynamic traffic demands. In step308, within each group, process300calculates the optimal power/code allocation among users402.

FIG. 4is a partial schematic illustration of a communication system400configured to implement allocation process300,FIG. 3. In the exemplary embodiment, communication system400is an HFC system implementing the present NOMA techniques for users402, and includes a node404(e.g., a fiber node), and a plurality of taps406for connecting respective users402to a signal transport medium408(e.g., a fiber strand, coaxial cable, etc.). In exemplary operation of system400, first user402(1) and second user402(2) are depicted to occupy the same two-dimensional frequency-time slot, and thus may belong to the same group (e.g., step306,FIG. 3). When seen three-dimensionally though, first user402(1) and second user402(2) are separated in the power/code domain according to the power/code allocation determined by the system (e.g., step308,FIG. 3). In an exemplary embodiment, system400is configured to perform the power/code allocation according to, criteria including, without limitation, maximized capacity, system requirements satisfaction, service level agreement fulfillment, and present or dynamic traffic demands, as described above.

FIG. 5is a graphical illustration depicting respective attenuation versus frequency plots500,502for first and second users402(1),402(2),FIG. 4. For ease of explanation, an exemplary description of gain and signaling effects inFIG. 5are limited to only two users402(i.e., plots500,502), but the person of ordinary skill in the art will understand how these principles apply with respect to more than two users on a cable plant. In an exemplary embodiment depicted inFIG. 5, first and second users402(1),402(2) occupy the same frequency-time slot, but are separated in the power domain.

For further ease of explanation, in this example, it is assumed that (1) capacity is the exemplary criterion used to determine the resource allocation in the power domain over a frequency-time slot, (2) the frequency-time slot is fixed by other preconditions or constraints of the overall allocation, (3) the frequency range of the given frequency-time slot is relatively small, (4) the total power for402(1),402(2) over the given frequency-time slot is fixed by other preconditions or constraints of the overall allocation (and is denoted as P), and (5) the channel is time-invariant. The person of ordinary skill in the art though, will understand that these assumptions are provided by way of example, and not in a limiting sense.

In the exemplary embodiment depicted inFIG. 5, first user402(1) and second user402(2) are located at different physical locations within the HFC network of communication system400. In this example, first user402(1) is located nearer in proximity to node404with respect to second user402(2), which is located farther away from node404. Therefore, irrespective of any pre-emphasis, second user402(2) will experience significantly more power variation, that is, attenuation, over a frequency range, as illustrated by the greater slope to plot502(user2) in comparison with the more linear, horizontal slope of plot500(used). This variation difference results in the difference of attenuation (e.g., A1versus A2) exhibited by first user402(1) and second user402(2), respectively, at a given frequency fg.

In the example illustrated inFIG. 5, a two-dimensional cross-section of the resource blocks202(1),202(2) are depicted with respect to a two-dimensional cross-section of the entire distribution200. As may be seen from this exemplary illustration, second user402(2) has a lower attenuation value A2at frequency fg, and the average attenuation values within the frequency slot that includes frequency fgmay be approximated to A1and A2(in dB) for first user402(1) and second user402(2), respectively.

Assuming, for purposes of this description, that the additive white Gaussian noise (AWGN) channels and Gaussian noise have a power of N within the frequency slot fgat a receiver side of system400, the spectral efficiency η of first user402(1) and second user402(2) within the frequency slot fgmay be respectively represented by:

for first user402(1)/user1, and by:

for second user402(2)/user2, where a1=10{circumflex over ( )}(−A1/10), a2=10{circumflex over ( )}(−A2/10), P is the total power budget for both users at the transmitter side, and 0≤x≤1 is the proportion of power for first user402(1). The total spectral efficiency ηtotalmay then be represented as:

Accordingly, in the embodiments described above, including allocation process300, system400is advantageously configured to enable maximization of η1, η2, and/or ηtotalaccording to a desired purpose of the system operator, and/or preconditions or constraints that may be placed on the system and its operation. In some embodiments, resource allocation may be further realized by adjusting value of x.

FIG. 6is a graphical illustration depicting an exemplary derivation technique600for maximizing spectral efficiency of first and second users402(1),402(2),FIG. 4. The exemplary embodiment illustrated inFIG. 6is depicted with respect to a derivation of maximum η1and η2implementing PD-NOMA. The person of ordinary skill in the art though, will appreciate that the principles described herein are applicable to other NOMA techniques, such as CD-NOMA, etc.

In an exemplary embodiment, the spectral efficiencies η1and η2are maximized for first user402(1) and second user402(2), respectively. Thus, by traversing the value x over [0, 1], an upper boundary curve602of (η1, η2) may be derived for the PD-NOMA implementation. With respect to the exemplary embodiment depicted inFIG. 6, the area under upper boundary curve602is considered to be achievable.FIG. 6further illustrates, for comparison, a counterpart curve604representing an upper limit achievable through the conventional OMA technique. As can be seen from the comparison, the greater boundary is achievable implementing the present NOMA techniques.

In an exemplary embodiment of technique600, a constraint606of η1=η2is applied, which intersects both curves602,604at points C and D, respectively. Thus, when compared with OMA value (i.e., point D) of counterpart curve604, the spectral efficiency of both η1and η2are improved for the PD-NOMA implementation (i.e., point C).

FIG. 7is a graphical illustration depicting a constellation plot700of superimposed signals702corresponding to first and second users402(1),402(2),FIG. 4. In the exemplary embodiment illustrated inFIG. 7, constellation plot700is depicted with respect to two superimposed QPSK signals implementing PD-NOMA, and using derivation technique600. In this example, the modulation format is designated to approach the maximum spectral efficiency η at point C on upper boundary curve602. Using the respective amplitudes of constellation700, the value for x at point C may be derived.

FIG. 8is a graphical illustration demonstrating a capacity tradeoff effect800between first and second users402(1),402(2),FIG. 4, according to the conventional OMA technique compared with the present NOMA techniques. In the exemplary embodiment illustrated inFIG. 8, trade-off effect800demonstrates the simulation results of a capacity trade-off between user1and user2at a distance of 300 ft from the node (e.g., node404,FIG. 4), for an OMA case802and a NOMA case804.

In this example, the respective resource blocks202of first and second users402(1),402(2) (i.e., user1and user2) are assumed to occupy a total bandwidth of 20 MHz, and at a central frequency of 1 GHz after frequency-time allocation and user grouping. Referring back toFIG. 4, the tap to which user1connects (e.g., tap406(1)) is, in this example, 100 ft away from fiber node404, while the tap to which user2connects (e.g., tap406(2)) is 300 ft away from node404. In this simulation, taps406were communicatively connected to node404by 75-Ohm 0.5-inch hardline cables, and the noise density at the receiver end of simulated system400was 25-dB lower than the transmitted signal power density.

Accordingly, when compared with first user402(2), second user402(2) experiences higher attenuation at 1 GHz due to the fact that second user402(1) is farther away from node404. Thus, because first and second users402(1),402(2) share the same frequency resource (20 MHz, in this example), the relative capacity both users has a tradeoff relationship. As can be seen from the exemplary effect800depicted inFIG. 8, the tradeoff for both of first and second users402(1),402(2) is demonstrated along both an OMA curve806and a PD-NOMA curve808. Additionally, when and equal capacity constraint810is applied as a criterion for effect800, it can be seen that, at point812on NOMA curve808, 7 Mbps (i.e. 10.6%) of higher capacity is realized in comparison with a corresponding equal-capacity point814on OMA curve806.

Accordingly, implementing OMA techniques, trade-off effect800demonstrates, in this simulation example, that 1001.2-1010 MHz is allocated to first user402(1) and 990-1001.2 MHz is allocated to second user402(2). However, in contrast, the implementation of PD-NOMA enables 6.41% of the total transmitted power to be allocated to first user402(1) and 93.59% of the transmitted power to be allocated to second user402(2).

FIG. 9is a graphical illustration demonstrating a capacity tradeoff effect900between first and second users402(1),402(2),FIG. 4, according to the conventional OMA technique compared with the present NOMA techniques. Tradeoff effect900is similar to tradeoff effect800,FIG. 8, except that tradeoff effect900demonstrates simulation results for second user402(2) located 500 ft from node404, for an OMA case902and a NOMA case904, as opposed to the 300 ft distance described above with respect toFIG. 8. Accordingly, a higher improvement may be observed from the implementation of the present NOMA techniques for users402located at even greater distances from node404.

Also similar to effect800, effect900depicts an OMA curve906and a NOMA curve908, and applies an equal capacity constraint910as a criterion. In this example, it may be seen that, at point912on NOMA curve908, 11.9 Mbps (i.e. 21.8%) of higher capacity is realized in comparison with a corresponding equal-capacity point914on OMA curve906. Additionally, implementing OMA techniques, 1001.2-1010 MHz is again allocated to first user402(1) and 990-1001.2 MHz is again allocated to second user402(2). However, in this example, the implementation of PD-NOMA enables 5% of the total transmitted power to be allocated to first user402(1) and 95% of the transmitted power to be allocated to second user402(2).

FIG. 10is a graphical illustration depicting a distance versus capacity improvement effect1000for second user402(2),FIG. 4. In the exemplary embodiment, improvement effect1000demonstrates, through simulation, the results achieved by implementation of the present NOMA techniques (e.g., in comparison with conventional OMA techniques). More particularly, improvement effect1000depicts a relationship curve1002between the location of second user402(2) and the capacity improvement using NOMA, when first user402(1) is fixed at a location 100 ft away from the node404in these simulations. Relationship curve1002therefore becomes a valuable tool for grouping users (e.g., step306of process300,FIG. 3), based on the respective locations of various users, as well as other chosen criteria of the system.

FIG. 11is a graphical illustration depicting a noise level versus capacity improvement effect1100for second user402(2),FIG. 4, according to the present NOMA techniques compared with the conventional OMA technique. In an exemplary embodiment, the capacity improvement may also be determined based on respective noise level experienced by a particular user at various distances from the node. Improvement effect1100depicts the capacity improvement (i.e., the vertical axis, in %) under different noise levels (i.e., the horizontal axis, in dB) for a first condition1102when second user402(2) is located 300 ft from node404, and for a second condition1104when second user402(2) is located 500 ft away from node404. Under first condition1102(i.e., 300 ft) a first maximal point1106is found when the noise level is approximately −17 dB, while under second condition1104(i.e., 500 ft), a second maximal point1108is found when the noise level is approximately −23 dB. The respective curves of first and second conditions1102,1104therefore also provide valuable tool for grouping users (e.g., step306of process300,FIG. 3), based on the respective noise levels and locations of various users, as well as other chosen criteria of the system.

The present embodiments are described above with respect to HFC networks by way of example, and not in a limiting sense. The person of ordinary skill in the art will appreciate how the systems and methods described herein are also applicable to the optical fiber segments in the HFC network, as well as a passive optical network (PON) architecture that utilizes optical fiber segments in multiple fiber nodes at endpoints, which may be analogous to the various users described with respect to the present embodiments. The NOMA techniques described herein are also provided for illustrative purposes, but are not intended to be limiting. Other NOMA techniques, for example, may also be implemented within the scope of the present embodiments, including without limitation Multi-User Superposition Transmission (MUST), Sparse Code Multiple Access (SCMA), Pattern Division Multiple Access (PDMA), Lattice Partition Multiple Access (LPMA), and/or Multi-User Shared Access (MUSA).

The person of ordinary skill will further appreciate that the present techniques are generally applicable to access systems having a power domain and/or a code domain, and which adopt non-orthogonal signal space in an HFC network. As featured above, the principles of the present systems and methods are described with respect to two users separated in the power/code domain. Nevertheless, the person of ordinary skill in the art will appreciate that these principles apply in the case of more than two users separated in the power/code domains. It will further be appreciated, from the description herein and the accompanying drawings, that the present techniques for optimizing the power/code domains are not exclusive of optimization techniques for the frequency and time domains. That is, the present embodiments may be employed as joint allocation and/or joint optimization techniques for the power/code domain in a complementary and/or simultaneous fashion with allocation/optimization techniques of the frequency and time domains.

Exemplary embodiments of systems and methods for optimizing non-orthogonal multiple access are described above in detail. The systems and methods of this disclosure though, are not limited to only the specific embodiments described herein, but rather, the components and/or steps of their implementation may be utilized independently and separately from other components and/or steps described herein.

Although specific features of various embodiments of the disclosure may be shown in some drawings and not in others, this is for convenience only. In accordance with the principles of the disclosure, a particular feature shown in a drawing may be referenced and/or claimed in combination with features of the other drawings.