Patent Application
20190238263
This specification is directed, in general, to wired and wireless communications, and, more specifically, to systems and methods for relaying, integrated access and backhaul, and latency reduction for communication networks.
Historically, wireless networks have been used as a last-hop connection technology, where the wireless device communicates with another device that is connected to a high-rate wired connection. This wired-to-wireless interface is commonly found in cellular and wireless local area network (WLAN) applications. Despite the enormous amount of research focused on multi-hop wireless networks, the commercial applications have been limited.
The increasing numbers of wireless connected devices and access points are altering this model. Many of these devices will be low-power and low-complexity Internet of Things (IoT) devices. Due to the low transmit powers of these nodes, a large fraction of the deployed IoT devices will not have any single-hop connection to a base station or access point. Multi-hop deployments will be critical to facilitating many of the proposed IoT applications.
Simultaneously, cellular systems, primarily deployed using 3GPP technical standards such as LTE and LTE-Advanced, are moving towards small cell models. Traditional fiber or copper backhaul networks cannot scale to meet the complexity of these complicated small cell deployments. Self-backhauling, where a fraction of the carrier's bandwidth is set aside for backhaul communication, is starting to dominate future deployment discussions. Though not generally thought of as multihop framework, self-backhauling systems clearly fall inside the academic multihop paradigm.
These commercial multihop deployments are further complicated by the growing focus on latency. 5G systems have a goal of a 10× latency improvement over 4G systems. When these low-latency requirements are combined with any self-backhaul or IoT scenarios, the results are troubling. This is primarily because the design of standardized systems focuses on long blocklengths, which are decoded and reencoded at intermediate nodes.
This new research area is best practically illustrated by 3GPP's recent focus on Integrated Access and Backhaul (see 3GPP TDoc RP-17148). This recently proposed study item aims to address multiple 5G requirements including that the network “shall support multi-hop wireless self-backhauling . . . to enable flexible extension of range and coverage area”, “shall support autonomous adaptation on wireless self-backhaul network topologies to minimize service disruptions”, and “shall support topologically redundant connectivity on the wireless self-backhaul . . . enhance reliability and capacity and reduce latency”.
The challenge of multihop communication with tight latency and/or computational constraints is of immediate commercial and academic interest. Finite blocklength information theoretic analysis has only recently become an area of emphasis within the research community. Instead of proposing a new ad-hoc design for specific applications, a general framework is needed.
Similar problems also arise in wired networks. Heterogeneous wired networks are commonly found. An example is a high-rate fiber line being interfaced to an Ethernet network, and such a wired multihop scenario faces the same challenges as the wireless counterpart, i.e., how to design low-latency high-throughput schemes. Therefore, improvements are needed in the field.
To address these, and other shortcomings of existing relaying and multi-hop techniques, the present disclosure provides a comprehensive technique referred to herein as “transcoding” which can improve throughput, reduce latency, and decrease computational demands at intermediate nodes.
According to one aspect, the present disclosure provides a method of operating a communication node, comprising configuring the node to receive a signal encoded by one or more codeword sets, configuring the node to remapping subpackets of the incoming signal for transmission over a second communication link, receiving an incoming signal, parsing the received signal into subpackets, encoding and remapping each of the subpackets, and transmitting the encoded and/or remapped subpackets over a communication link.
According to another aspect, the present disclosure provides a communication node apparatus comprising circuitry for configuring the node to receive a signal encoded by one or more codeword sets, circuitry for configuring the node to reencode/remap subpackets of the incoming signal for transmission over a second communication link, circuitry for receiving an incoming signal; circuitry for parsing the received signal into subpackets; circuitry for encoding/remapping each of the subpackets, and circuitry for transmitting the encoded/remapped subpackets over a communication link.
The above and other objects, features, and advantages of the present invention will become more apparent when taken in conjunction with the following description and drawings wherein identical reference numerals have been used, where possible, to designate identical features that are common to the figures, and wherein:
Wired and wireless networks are becoming increasing complicated. Before the transmitted signal reaches its final destination, it must pass through one or more “relay nodes.” A relay node, as used herein, may be an access point, base station, user equipment, portable device, switch, router, communication node, or other communication equipment. Each relay node typically performs an operation like decode-and-forward (DF) or amplify-and-forward (AF). In DF, a relay node would demodulate and/or decode its received signal to produce a detected version of the transmitted bits brec. These bits are then reencoded and remodulated to produce a signal to send over the second hope of the channel (i.e., the relay node sends a signal to the final destination or to another relay node). In AF, the relay node simply scales and retransmits the signal it received.
Relays are found in networks throughout the world, but the de facto industry standard is still the simplest DF policy. Based on the concept proposed in 1979 (see T. Cover and A. El Gamal, “Capacity theorems for the relay channel,” IEEE Trans. Info. Theory, vol. 25, no. 5, pp. 572-584, September 1979.), DF simplifies the design of a multi-hop network into the concatenation of multiple point-to-point links. Each intermediate node thus has to accumulate a whole coding block of received symbols before performing any decoding, re-encoding, and transmission.
This incurs at least1 a full coding block of delay and requires full operations of the channel coding hardware for every intermediate node. Since both the delay and the complexity of DF increase linearly with respect to the number of hops, the delay-throughput performance of DF is significantly suboptimal for modern high-performance applications (i.e., self-backhauling) and the computational/power cost may also be prohibitively high for the low-power scenarios (i.e., IoT). 1 This delay estimate is optimistic since we assume that decoding and re-encoding operations are instantaneous and do not incur any decoding delay.
AF actually avoids such a delay and complexity penalty by simply amplifying the received signal without any block coding/decoding. However, for almost all scenarios, the low cost of AF is accompanied by substantial throughput-loss (30-70% compared to DF) due to the noise accumulated at the intermediate node.
The present disclosure provide a novel technique, referred to herein as “transcoding.” In transcoding, the relay partially decodes or partially processes the received signal before transmission. This avoids the delay and computational issues associated with DF and significantly improves upon the performance of AF.
Systems and methods for relaying in wired and wireless networks are described herein. In an illustrative, non-limiting embodiment, a method may include a transmit signal employing an error control code (constructed in some field such as the binary field, real numbers, or complex numbers). This error control code may be constructed through the concatenation of two or more error control codes. In the case of two error control codes, a number of transmit bits b is encoded using a first error control code to yield c=Q1(b) as shown in
If the code is binary, the code could be constructed from any code including a low density parity check (LDPC) code, polar code, turbo code, convolutional code, or Reed-Solomon code. Turbo codes and convolutional codes are used in LTE, LTE-Advanced, and LTE-Advanced Pro (see coding discussion in 3GPP TS 36.211, 36.212, 36.213). LDPC and polar codes have recently been adopted for the 5G standard (often called 5GNR), with initial standardization activity summarized in 3GPP TS 38 series documents. These include 3GPP TS 38.211, 38.212, 38.213.
The first error control code output c is then encoded by a second code to yield d=Q2(c) as shown in
Each of the L subpackets can then be encoded using a shorter code that takes k1 input symbols and generates m coded symbols. Example codes include, but are not limited to, Hamming codes, Reed-Mueller codes, convolutional codes, cyclic codes, and polar codes. The output of the inner code is then the concatenated vector d=[[d1 d2 . . . dm] [dm+1 dm+2 . . . d2m] . . . [d(L-1)m+1 d(L-1)m+2 . . . dLm]]. In this terminology, the short code used to produce the inner code is of rate k1/m. Each encoded subpacket is chosen from a codeword set D. The entire coded stream is of length n2=Lm. If the short code producing the inner code is a linear block code, each subpacket di is written as di=ciG where G is the short code's generator matrix. Here ci=[cik1+1 cik1+2 . . . c(i+1)k1] and di=[dim+1 dim+2 . . . d(i+1)m].
In an example embodiment, the transcoder works by processing the inner code (i.e., the C2 code). As shown in
One embodiment of the mapping when q=m is for the transcoder to decode each ri to obtain a received version of the subpacket, denoted by di,rec. The distance (e.g., using some distance like Hamming distance, Euclidean distance, etc.) of di,rec from ri could be computed. If the distance is less than some threshold, di,rec is transmitted on the second hop. If the distance is greater than some threshold, ri is transmitted on the second hop.
This short code could also be nested. One definition of a nested code is when D is a subset of another set Dexpand. One way to constructed a nested code D is to expurgate the code Dexpand. This structure gives rise to another embodiment for transcoding. In this embodiment the relay can decode each subpacket ri over the codeword set Dexpand. If Dexpand is a linear block code with generator matrix Gexpand, then the relay can decode over this larger code, which generates more decoder output bits. In this framework, the relay functions like a source coder using an error control coding structure for the source code.
As mentioned earlier, transcoding can be implemented over any field. An error control code may be combined with modulation. In this scenario, the transcoding could apply to the modulation, error control code, or both. Note that one or both codes can be combined with interleaving. An embodiment of transcoding in the real field is to use lattice codes. In this embodiment, the inner code could be a lattice code. The transcoder could decode using this lattice code or a nested lattice code.
Transcoding could also be implemented over multiple relay nodes operating in parallel and/or serial. Each node would have a transcoder designed in a complementary way to maximize throughput. This implementation could be sequential.
In a further embodiment, the relay will decode the inner code of each of the subpackets and transmit them to the destination directly. However, at the end of receiving all subpackets from the source, the relay will then decode the correct, final information bits and compare the bit string to the inner code decision made earlier for each subpacket. If there was any error made during the inner-decoding, then an additional correction subpackage is sent to the destination to inform the destination how to ignore or compensate for the erroneous subpackets sent earlier. The overall correction mechanisms will take advantage of the structures of both the inner and outer codes to further reduce the error rate.
Yet another embodiment of the transcoder implementation uses linear-programming-based (LP-based) optimization tools when designing the optimal transcoder. Specifically, the LP-based tools can be used to find the encoder/decodering mappings that maximize the end-to-end Hamming or Euclidean distances. By maximizing the Hamming or Euclidean distance, the transcoder will improve the signal-to-noise ratio experienced by the outer code and thus decrease the error rate and shorten the delay.
In another illustrative, non-limiting embodiment, the transcoder may be implemented in a backhaul modem. Standardized techniques, such as those discussed for the Integrated Access and Backhaul study item in 3GPP, could use transcoding at each backhaul model. The backhaul may include a processor and a memory coupled to the processor, the memory configured to store program instructions executable by the processor to cause the device to: be configured for transcoding, receive an incoming signal over a wired or wireless link, and map (or transcode) subpackets of the incoming signal to subpackets for transmission over a next hop.
In yet another illustrative, non-limiting embodiment, a non-transitory electronic storage medium may have program instructions stored thereon that, upon execution by a processor of a device, cause the device to: be configured for transcoding, receive an incoming signal over a wired or wireless link, map (or transcode) subpackets of the incoming signal to subpackets for transmission over a next hop.
In certain embodiments, one or more communications devices or computer systems may perform one or more of the techniques described herein. In other embodiments, a tangible computer-readable or electronic storage medium may have program instructions stored thereon that, upon execution by one or more communications devices or computer systems, cause the one or more communications devices or computer systems to execute one or more operations disclosed herein. In yet other embodiments, a communications system (e.g., a device or modem) may include at least one processor and a memory coupled to the at least one processor (as shown in
Many of the operations described herein may be implemented in hardware, software, and/or firmware, and/or any combination thereof. When implemented in software, code segments perform the necessary tasks or operations. The program or code segments may be stored in a processor-readable, computer-readable, or machine-readable medium. The processor-readable, computer-readable, or machine-readable medium may include any device or medium that can store or transfer information. Examples of such a processor-readable medium include an electronic circuit, a semiconductor memory device, a flash memory, a ROM, an erasable ROM (EROM), a floppy diskette, a compact disk, an optical disk, a hard disk, a fiber optic medium, etc. Software code segments may be stored in any volatile or non-volatile storage device, such as a hard drive, flash memory, solid state memory, optical disk, CD, DVD, computer program product, or other memory device, that provides tangible computer-readable or machine-readable storage for a processor or a middleware container service. In other embodiments, the memory may be a virtualization of several physical storage devices, wherein the physical storage devices are of the same or different kinds. The code segments may be downloaded or transferred from storage to a processor or container via an internal bus, another computer network, such as the Internet or an intranet, or via other wired or wireless networks.
Many modifications and other embodiments of the invention(s) will come to mind to one skilled in the art to which the invention(s) pertain having the benefit of the teachings presented in the foregoing descriptions, and the associated drawings. Therefore, it is to be understood that the invention(s) are not to be limited to the specific embodiments disclosed. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.
The present patent application is related to and claims the priority benefit of U.S. Provisional Patent Application Ser. No. 62/563,626, filed Sep. 26, 2017, the contents of which is hereby incorporated by reference in its entirety into the present disclosure.
| Number | Date | Country | |
|---|---|---|---|
| 62563626 | Sep 2017 | US |
