WO2022208041A1 - Mobile or airborne relay network and protocol - Google Patents

Abstract

A network comprising artificial intelligence for optimising network topology between transceiver nodes via link quality which leverage blind transception, transmit and receive without demodulation of signals. (Figure 3). The network may be configured to self-heal or reform in reaction to interference or physical events, and in which nodes which disappear or become unresponsible are ignored and a new topology is created based on new calculations instead of the network not being able to route traffic through a broken part of the network.

Description

MOBILE OR AIRBORNE RELAY NETWORK AND PROTOCOL

This invention relates to a mobile or airborne relay network and protocol. More especially, this invention relates to a blind transceiver based aerial network system leveraging Artificial Intelligence (Al) to manage physical and network topology for communication with other systems as well as maximizing its ability to avoid interference.

Aerial relay systems are known. Almost all of the known aerial relay systems focus on specific scenarios and use specific bands of the Radio Frequency (RF) spectrum such as LTE. These systems are often insecure, using 802.11 or 802.15 based protocols that do not work well for Mobile Ad- hoc Networks (MANETs) let alone flying MANETs. These systems tend to be insecure, are easily jammed and exploited as well as have poor data service or range.

It is an aim of the present invention to avoid or reduce the above mentioned problems.

Accordingly, in one non-limiting embodiment of the present invention, there is provided a network comprising artificial intelligence for optimising network topology between transceiver modes via link quality which leverage blind transception, transmit and receive without demodulation of signals. The network may be configured to self-heal or reform in reaction to interference or physical events, and in which nodes which disappear or become unresponsive are ignored and a new topology is created based on new calculations instead of the network not being able to route traffic through a broken part of the network.

The network may comprise a linear network coding transport layer between network transceivers that avoids the problem of network congestion on commonly used transport layers by removing the need for acknowledgement between transceiver nodes.

The network may comprise beam forming means for countering jamming issues, allowing for increased gain and/or signal detection, and for providing the ability to project more power than traditional antennae.

The network may comprise frequency hopping spread spectrum means for maximising band width without the need for modulation or demodulation.

The network may comprise multiple sub-nodes of relays formed to increase range or provide services in an area. These services may be special services. The network may create a new topology where a cell is made up of relays which intercommunicate but provide backhaul to a main airborne relay network. All nodes in the cell may operate as one from an outside perspective, for example via cooperative MIMO. This may enable the network to be used to increase network coverage for traditional LTE or WiFi providers as either a permanent or temporary augmentation of the entire network. The present invention may provide a signal relay system comprising a network comprising a plurality of transceivers that act as network nodes in a mesh network, and wherein the network comprises a plurality of nodes communicating with each other as part of one collective network as well as external nodes.

The signal relay system may use a simple protocol for moving messages within the network, the protocol being such that it leverages blind transception, transmit and receive, to receive and transmit a message without demodulating or modulation of the signal at any time in the network.

The network may contain a plurality of transceivers that act as network nodes in a mesh network, the network being made up of many nodes communicating with each other as part of one collective network as well as external nodes.

The network may comprise a simple protocol for moving messages within the network, said protocol leveraging blind transceptiion, transmit and receive, to receive and transmit a message without demodulating or modulation the signal at any time in the network, and the nodes collecting information on where messages need to go from signal frames creating a ultra-light method of communication resulting in faster signal traversal times through the network as well as greater bandwidth.

The network may comprise nodes that move around in the air, creating a capability for rapid and physical reshaping of the network. The network may comprise moving nodes in the network increasing signal diversity and increasing performance by benefitting beamforming capability and other transmission capabilities which are inherently low powered.

The network may comprise a mesh of RF nodes able, depending on scale, to more easily evade jamming and kinetic attacks compared to fixed base stations, mobile base stations, or aerostats, whereby if part of the network is degraded the network can sense the degrading of internode communication and reorganize to evade.

The network may comprise nodes which do not need a singular master node of which all signals are routed through to organize, rather each node being capable of calculating its best connections to other nodes and local nodes vote for their local authority node, whereby the network can better respond to losses in part because there is no central node that may be overwhelmed, jammed or destroyed which would otherwise trigger a much more complex and slower recovery.

The network may comprise mesh of nodes which can rapidly find the best route from one node to the other while they are moving in a stochastic manner via the use of machine learning techniques, wherein a node calculates the position of the nodes it wants to communicate to and on finding the right path it knows where each node should be in space and time thereby reducing total messaging and loss of data. The network may comprise multiple sub-nodes of relays formed to increase range or provide special services in an area, the network creating a new topology where a ‘cell’ made up of relays, e.g. numbering as little as three, intercommunicate but one provides backhaul to the main airborne relay network.

The network may be one which is able to self-heal or reform in reaction to interference or physical events, and comprising nodes that disappear or become unresponsive are ignored and a new topology is created based on new calculations instead of the network not being able to route traffic through a broken part of the network.

The network may be one which is able to detect and geo-locate RF systems for both countering issues such as jamming but also detect them by acting as a virtual cooperative antenna, and wherein a virtual antenna array allows for greatly increased gain and/or signal detection as well as the ability to project far more power than traditional antennae.

The network may comprise virtual antennae arrays formed as needed depending on the nature and design of aerial nodes, and wherein multiple arrays can be formed to meet numerous needs and the system is not limited to specific patterns.

The network may be configured to create an inherent anti-jamming capability as well as LPI (Low Probability of Intercept), this being in part due to the nodes being able to use tighter beams/signals for Line of Sight (LoS) communication, unlike traditional MANET (Mobile Ad-hoc Networks) where signals are usually omnidirectional, and wherein blind signal transmission and detection also allow for LPI.

The network may be able to incorporate Low Probability of Intercept/Detect (LPI/LPD) techniques, where signals are generated or parasitically repeated between the nodes and potential end-users, the signals being distorted so that a symbol of the modulated signal is then changed so that the symbol would then contain another constellation of symbols that allow for the embedding of signals in a signal, and the signal being further changed to look like Gaussian noise.

Embodiments of the invention will now be described solely by way of example and with reference to the accompanying drawings in which:

Figure 1 illustrates how the signal relay system of the present invention comprises two protocols, with the first to govern low level layers of the OSI model, in darker grey, that will do things such for example as support blind relay, and with the second, in light grey, providing higher level services such as internal network message routing;

Figure 2 illustrates sub-nodes within the airborne relay network of the present invention;

Figure 3 shows a predictive network protocol where the system predicts where the next node will be so that it can forward a signal, and wherein the first circle indicated by the arrows, the signal source from a drone transceiver passes information to an intermediate node based on an Ai model, and wherein the next node discovers the destination and passes it off to the destination node, in this case the end circle indicated by the arrows;

Figure 4 shows how a relay at a higher level transmit a signal which the network blindly detects, the system leveraging the predictive node network routing protocol quickly to select the best node to pass the signal of the ground vehicles and vice a versa, and wherein the drones continue to fly organising as needed dictated by the ML algorithms;

Figure 5 shows an explanation of hop times and dwell time meanings;

Figure 6 is an example of functional architecture of the invention; and

Figure 7 is an overview of LNC packet encoding.

The invention will now described with reference to Figures 1 - 7.

The system, at layers 1 and 2 (see Figure 1), uses blind signal transceiver approach, removing the need for demodulation and modulation of signal at each node, thereby greatly reducing time and compute cost. This also increases bandwidth. The system also makes use of a number of technologies involving the capability to create virtual arrays with the system allowing for greater reception and transmission. More than a single node may be produced. The system also uses a machine learning AI approach for signal routing which is superior when working with systems like flying nodes since it can better predict what network paths will be and what nodes will be where (see Figure 3). The same AI can also change and reconfigure the flying formation to maximise various states such as reception and to avoid threats to the network integrity such as jamming or interference.

These capabilities let users move from experimental and academic platforms to systems that are able to be used in real life, often offering better service than existing ground based system such as LTE. While this approach of using aerial platform has obvious problems such as weather too bad for the drones to fly, the system’s approach offers many of the same benefits to normal ad-hoc mobile networks. Additional applications include squad radios, vehicle MANETs, as well as commercial applications.

The present invention focuses on two components, a transmission protocol for multi-hop and multi-path networking and an airborne network transceiver. The novel protocol aims to achieve low dwell times and high bandwidth even in challenging conditions. The solution comprises of omnidirectional networking, beamforming, and detection of interference on the protocol side as well as anti-jamming detection, and extraction of network signals under jamming on the transceiver.

The airborne relay transceivers blindly detect a signal and determine its frame boundaries (see Figure 4). Once that is accomplished, the relays use machine learning algorithms to beam form. The transceivers exchange the signal by removing the Doppler Shift associated with the Frequency of Arrival (FOA). The airborne relays transceivers then evaluate the best route through the mobile network and pass on the signal. The relay system leverages a scheme of internal transmission and networking of taking a signal captured by the transponder and manipulating it to produce two smaller signals, for example, from 800 microsecond to 2 X 400 microsecond signals. While a higher dwell time allows the receiving radio more time to capture a signal, it also generally reduces the speed of processing and this bandwidth and data rate.

Figure 5 shows more detail on hop times and dwell times. In schemes such as Frequency Flopping Spread Spectrum (FHSS), the frequency of the narrowband signal is periodically changed, “hopping” the transmitted signal around the spectrum. The signal’s carrier frequency changes according to a pseudo-random “hopping sequence,” dwelling at each frequency for a short period of time, typically on the order of 100 microseconds. When the transmitted signal is observed over longer periods of time, the hopping sequence effectively “spreads” the signal into a wideband signal. Redundancy and error correction can be achieved by executing retransmission of the same data on different frequency hops.

In terms of anti-jamming capability, FHSS provides an effective countermeasure to narrowband, tone and frequency follower jamming. Shorter dwell times provide greater jamming resistance, but, since more time is spent hopping, shorter dwells also decrease the amount of data that can be sent.

Another benefit of FHSS is LPI in general, as an adversary will have difficulty intercepting the transmission because of the pseudo-random nature of the hopping pattern. These are all reasons why having short dwell times are useful. There may be some issues relating to sending data containing short dwell times over longer distances where not all packets are received, and minimum operating characteristics for the system may need to be defined for end users.

The transmission protocol may be developed to address the technical challenges of implementing a multi-hop multi-path network focusing on mobile airborne relays that enable flexibility in waveform selection. In a preliminary approach, the end nodes are assumed to communicate over multiple time- frequency transmission dwells with 1 microsecond time durations and 20 MHz channel bandwidths, and with the internal dwell structure. Each dwell is assumed to transport 10,000 bits within a 400 microsecond (ps) sub-dwell, transmitted redundantly and with a 150ps cyclic prefix (CP) (dynamically adjusted based on deployment strategy) covering time-of-flight over a 45km slant range. The transmitted dwells are further multiplied by a random or pseudorandom cyclic shift that allows discrimination of co-channel intended bursts and spoof-resistant excision of jammers. In full-duplex systems, the dwells are further grouped into 10ms frames, allowing communication at a full- duplex rate of 1 Mbps per dwell-pair. For example, the 4,400-4,940 MHz band used for RQ-7A Shadow datalinks could support a 135 Mbps full-duplex rate using this approach. The approach would be useful for those trying to maximize speed of signals across multi-hop networks.

Referring to Figure 2, there are shown sub-nodes within an airborne relay network of the present invention. Figure 6 shows functional architecture of a network of the present invention. The component parts of the architecture are shown in block form in Figure 6.

Figure 7 is an overview of LNC packet encoding. Various steps within the packet encoding are shown on the left side of Figure 7.

In the network of the present invention transceivers (TCVs) are connected through the airborne transponder network. Each transponder possesses a multi-element antenna array, which receives, down-converts, and digitizes a set of dwells allocated to that transponder — potentially, all the dwells utilized by the network. The transponder then removes the 150ps CP and separates the remaining 800ps data burst into two 400ps sub-dwells, comprising identical replicas of each signal transmitted on that dwell, except for a phase offset proportional to the frequency of arrival (FOA) of that signal. The transmitted signal sub-dwells are then extracted from the noise and interference (jamming) also received by the array, using a mature (TRL 6+) self-coherence restoral (SCORE) algorithm, which has been demonstrated in numerous prototype and fielded systems over 25 years (see US Pat Nos. 5225210, 6128276, 6359943, 7079480, 9648444 and Publ. No. 2017/0026205). The extracted sub-dwells are passed to a transmit beamforming network (Tx BFN) that steers the transmit array to an intended beam-steering or beam-and-null steering solution for each dwell.

Importantly, the transponder do not implement the initial sub-dwell modulation or final demodulation operations performed at end nodes. This greatly simplifies implementation and reduces the vulnerability of the network if captured by hostile forces. This removal of modulation and demodulation steps could be adapted to other RF communication platforms to increase speed of communication roundtrip and greatly enhances the utility of the transponder to other communication missions.

It will be appreciated from Figures 1 - 7 that the invention may be able to provide the following structure and advantages.

The network contains a plurality of transceivers that act as network nodes in a mesh network. The network is made up of many nodes communicating with each other as part of one collective network as well as external nodes.

The system uses a simple protocol for moving messages within the network. The protocol leverages blind transception, transmit and receive, to receive and transmit a message without demodulating or modulation the signal at any time in the network. The nodes collect information on where messages need to go from signal frames creating an ultra-light method of communication resulting in faster signal traversal times through the network as well as greater bandwidth.

The system is made up of nodes that move around in the air (see Figure 2), creating a capability for rapid and physical reshaping of the network. Moving nodes in the network increases signal diversity and increases performance by benefitting beamforming capability and other transmission capabilities which are inherently low powered.

A network made up of a mesh of RF nodes can, depending on scale, more easily evade jamming and kinetic attacks compared to fixed base stations, mobile base stations, or aerostats. By its nature, if part of the network is degraded the network can sense the degrading of internode communication and reorganize to evade.

Nodes do not need a singular master node of which all signals are routed through to organize. Rather each node is capable of calculating its best connections to other nodes, and local nodes vote for their local authority node. In this way, the network can better respond to losses in part because there is no central node that may be overwhelmed, jammed or destroyed which would otherwise trigger a much more complex and slower recovery.

The mesh of nodes can rapidly find the best route from one node to the other while they are moving in a stochastic manner via the use of machine learning techniques. In this case, a node calculates the position of the nodes it wants to communicate to and on finding the right path it knows where each node should be in space and time, thereby reducing total messaging and loss of data.

Multiple sub-nodes of relays can be formed to increase range or provide special services in an area. The network creates a new topology where a ‘cell’ made up of relays, for example numbering as little as three, intercommunicate but one provides backhaul to the main airborne relay network.

System can self-heal or reform in reaction to interference or physical events. Nodes that disappear or become unresponsive are ignored and a new topology is created based on new calculations instead of the network not being able to route traffic through a broken part of the network.

The network can detect and geo-locate RF systems for both countering issues such as jamming but also detect them by acting as a virtual cooperative antenna. The virtual antenna array allows for greatly increased gain and/or signal detection as well as the ability to project far more power than traditional antennae.

Virtual antennae arrays can be formed as needed depending on the nature and design of aerial nodes. Multiple arrays can be formed to meet numerous needs and the system is not limited to specific patterns.

The system design creates an inherent anti-jamming capability as well as Low Probability of Intercept (LPI). This is in part due to the nodes being able to use tighter beams/signals for Line of Sight (LoS) communication, unlike traditional MANET (Mobile Ad-hoc Networks) where signals are usually omnidirectional. Blind signal transmission and detection also allow for LPI.

Furthermore, the system can incorporate Low Probability of Intercept/Detect (LPl/LPD) techniques (such as the one in patent application GB201 9583.0) where signals are generated or parasitically repeated between the nodes and potential end-users. In this implementation, the signals are distorted so that a symbol of the modulated signal is then changed so that the symbol would then contain another constellation of symbols that allow for the embedding of signals in a signal. That signal would be further changed to look like Gaussian noise.

It is to be appreciated that the embodiments of the invention described above with reference to the accompanying drawings have been given by way of example only and that modifications may be effected. Individual components shown in the drawings are not limited to use in their drawings and they may be used in other drawings and in all aspects of the invention. The invention also extends to the individual components mentioned and/or shown above, taken singly or in any combination.

Claims

1. A network comprising artificial intelligence for optimising network topology between transceiver nodes via link quality which leverage blind transception, transmit and receive without demodulation of signals.

2. A network according to claim 1 and which is configured to self-heal or reform in reaction to interference or physical events, and in which nodes which disappear or become unresponsible are ignored and a new topology is created based on new calculations instead of the network not being able to route traffic through a broken part of the network.

3. A network according to claim 1 or claim 2 and comprising a linear network coding transport layer between network transceivers that avoids the problem of network congestion on commonly used transport layers by removing the need for acknowledgements between transceiver nodes.

4. A network according to any one of the preceding claims and comprising beam forming means for countering jamming issues, for providing increased gain and/or signal detection, and for providing the ability to project more power than traditional antennae.

5. A network according to any one of the preceding claims and including frequency hopping spread spectrum means for maximising bandwidth without the need for modulation or demodulation.

6. A network according to any one of the preceding claims and comprising multiple sub-nodes of relays formed to increase range or provide services in an area.