Our Technology

• Dynamic networking planning and deployment model
• Supporting guaranteed real-time services with unlimited scalability
• Better network resource utilization
• Robust to wireless interferences
  
• Compatibility with current industrial standards
• Supporting scalable radio complexity (low power)
• Better economics and business case (low cost)

Our unique large-scale cognitive networking technology is largely differentiated from traditional wireless networking, by its opportunistic network resource utilization of both spectrum bandwidth and mesh station/radio availability. On the contrary, traditional wireless networking assumes that those resources can be predetermined.

In principle, the cognitive-networking technology creates a dynamic (fluid) wireless network without predetermined topology and spectrum allocation. For example, in multi-hop wireless communications, every packet takes opportunistically available paths in the wireless network, and with opportunistically available spectrum on each hop. The network-resource utilization can thereby reach its instantaneous maximum, disregarding volatile changes and the demand placed on the network.

In large-scale wireless networks, the problem of volatile spectrum availability is typical in unlicensed bands where interference prevails. Similarly, the problem of random radio availability is also often encountered due to the dynamic traffic load and other factors such as radio failure. In dynamic wireless environment, traditional wireless networking seldom functions properly, given its assumption of predetermined “virtual-wired” links and network topology for (ad-hoc) network routing protocols. As a result, despite research and development efforts, almost every today’s real-world wireless network is based on single-hop wireless (e.g., cellular networks, WLAN – wireless local area networks) rather than a true multi-hop mesh.

Our company currently holds eight patents (with a growing portfolio), comprehensively covering this innovative technology of cognitive wireless networking. The technology can also provide an effective application development platform for any large-scale wireless systems.

A set of key comparative advantages of the technology is further explained as follows.

Dynamic networking planning and deployment model:
No deterministic network topology has to be maintained, because the mesh radio resource is opportunistically utilized. The mesh stations/radios, when implemented with the cognitive-networking technology, become “drop-and-play” in the network deployment. Inserting more radios/stations can improve the radio resource to be opportunistically exploited, and therefore increase the network capacity. Likewise removing any individual radio/station does not create bottlenecks in the network. This fluid “drop-and-play” nature offers the potential of vast cost-saving in mesh infrastructure planning and deployments. The setup of mesh stations/radios does not need expensive planning and calibration, as multi-tier new deployments (for example introduced by service providers or subscribers) guarantee improved network capacity. High mobility of the mesh stations/radios can be supported.

Better network resource utilization:
The network resource in large-scale wireless networks includes: the amount of spectrum bandwidth and the number of mesh radios. Theoretical network capacity is decided by the network resources, and the multiplication of these two factors. Traditional wireless networking depends on a deterministic mesh-network topology. It is therefore difficult to efficiently utilize the network resources, subject to a dynamic wireless networking environment where both spectrum bandwidth and mesh radio availability cannot be predetermined. Our technology offers a means of better network-resource utilization, approaching the information-theoretical limit on wireless-network capacity.

Supporting guaranteed real-time services with unlimited scalability:
Due to the opportunistic network-resource utilization, reliable wireless communications with specified dataflow throughput, end-to-end delay, and delay variance can be supported over multiple wireless hops. Therefore, real-time services, including high-quality multimedia (over Internet Protocols), can be supported in a wireless mesh infrastructure by the cognitive-networking technology. In order to better understand this, note that the opportunistic exploitation of local random-networking environment can result in overall reliable end-to-end communications. Dataflow throughput is independent of the number of wireless hops; end-to-end delay and delay variance only increase linearly with the number of wireless hops; and delay variance can also diminish to zero with higher network density. Therefore, network operators only need to assure that sufficient network resources are deployed to support their applications, so as to provide guaranteed services of real-time communications, where the resources, e.g., gateway capacity and mesh radios, can be deployed with low cost.

Robust to wireless interferences:
Due to the opportunistic network-resource utilization of spectrum bandwidth, the network is very robust to interferences which can be substantial in unlicensed spectrum bands (e.g., ISM bands). For example, viable operation within unlicensed bands brings large free bandwidth to wireless mesh infrastructures, which results in large network capacity with virtually zero cost.

Compatibility with current industrial standards:
The cognitive-networking technology can be compatible with all established wireless radio standards, so that the implementation can be independent of physical radios. Therefore, the radio modules (with cognitive-networking capabilities) can use off-the-shelf RF chips which offer relatively low cost. The implementation can also be seamlessly integrated with all network-layer protocols, including for example Internet Protocols.

Supporting scalable radio complexity (low power):
The complexity of individual radio modules (with cognitive networking capabilities) is low and independent of network scale. The low radio complexity results in low power consumption, lower cost, and long battery life. When needed, it also makes it possible to power the mesh radio by cost-effective solar panel, which will further reduce installation cost by removing any cable attachment.

Better economics and business case (low cost):
As explained above, the cognitive-networking technology can offer excellent economics in large-scale wireless systems, by which 1) the costs of deploying network resources could be vastly reduced by the utilization of unlicensed spectrum bands and drop-and-play or mobile mesh radios; 2) much higher efficiency in network-resource utilization results in excellent performance with all the available resources being used to their instantaneous maximum.