Obviousness

Based on the provided prior art analysis, the following is an assessment of the obviousness of the independent claims of U.S. Patent 9,794,797 ("the '797 patent") under 35 U.S.C. § 103.

This analysis considers what a Person Having Ordinary Skill in the Art (PHOSITA) in wireless communications and network theory would have understood at the time of the invention. An invention is considered obvious if the differences between the invention and the prior art are such that the subject matter as a whole would have been obvious to a PHOSITA.

Obviousness Analysis of Independent Claims 1 and 8

Independent claims 1 and 8 describe a wireless node that uses a game theory-based decision process to select a directional antenna radiation pattern, considering the states of other nodes and a subjective value function to maximize its own benefit.

A strong argument for obviousness can be made by combining the teachings of Gu (US 2005/0073981) and the general knowledge of a PHOSITA regarding antenna technology, further supported by the teachings of Jain (US 8,170,591).

1. The Primary Reference: Gu (US 2005/0073981)

• Gu teaches a complete game-theoretic framework for resource allocation in a wireless ad-hoc network.
• It explicitly models network nodes as "players" in a cooperative game.
• The goal is to maximize utility for the nodes, which is directly analogous to the '797 patent's "subjective value function."
• The decision-making process in Gu is inherently based on the potential actions (states) and payoffs of other nodes in the network.

Gu teaches every element of claims 1 and 8 except for the specific application of its game-theoretic framework to the selection of a directional antenna radiation pattern. Gu applies its framework to other crucial wireless resources like power and bandwidth.

2. The Motivation to Combine Gu with Known Antenna Optimization Techniques

A PHOSITA would have been well aware that managing interference and improving network efficiency (i.e., spatial reuse of spectrum) could be achieved by controlling the directional state of antennas. This was a common and well-understood technique in the field. The motivation to apply Gu's sophisticated resource allocation framework to antenna direction would have been to solve the known problem of interference in a more optimal and decentralized way.

The teachings of Jain (US 8,170,591) support this motivation. Jain discloses a cognitive radio system that "self-optimizes" a variety of its transmission parameters—such as frequency, power, and modulation—based on utility functions to maximize performance. While Jain does not explicitly list antenna direction, it establishes the principle of applying automated, utility-driven optimization to any available transmission parameter to improve network performance.

A PHOSITA, seeing Gu's game-theoretic method for optimizing resources like power and bandwidth and Jain's principle of self-optimizing any available transmission parameter, would have found it obvious to apply Gu's method to another well-known and critical transmission parameter: the directional state of an antenna. This combination would be a predictable application of a known optimization technique (Gu's game theory) to a known system component (a directional antenna) to achieve a predictable result (improved interference management and network efficiency).

Conclusion for Claims 1 and 8: The combination of Gu's game-theoretic framework with the well-understood principle of using directional antennas for interference mitigation, as exemplified by the broader optimization goals in Jain, would render the subject matter of claims 1 and 8 obvious to a PHOSITA.

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Obviousness Analysis of Independent Claim 14

Independent claim 14 describes a method of optimizing an ad-hoc network where nodes negotiate the selection of their antenna's directional state using a Vickrey-Clarke-Groves (VCG) auction.

A strong argument for obviousness can be made by combining the teachings of Agrawal (US 8,401,570) and Gu (US 2005/0073981).

1. The Primary Reference: Agrawal (US 8,401,570)

• Agrawal teaches the core mechanism of claim 14: using a market-based auction, specifically mentioning Vickrey auctions (a VCG auction is a type of Vickrey auction for multiple items), for automated negotiation and allocation of a scarce wireless resource.
• In Agrawal, the resource being allocated is licensed spectrum, but the principle is the automated, economically-driven allocation of a shared resource among competing nodes.

Agrawal teaches the use of the specific auction type (VCG) for automated negotiation over a wireless resource. The key element missing is the application of this auction to negotiate the directional state of an antenna.

2. The Motivation to Combine Agrawal with the Ad-Hoc Context of Gu

A PHOSITA would recognize that the "spatial channel" created by a directional antenna is a sharable, and often conflicting, network resource, just like the frequency spectrum discussed in Agrawal. The problem addressed by Agrawal (efficiently allocating a resource to the user who values it most) is the same problem that exists with directional antenna patterns in a dense ad-hoc network.

Gu provides the context of a cooperative, multi-hop ad-hoc network where resource allocation is critical for the network to function. A PHOSITA, familiar with the challenges of ensuring cooperation in the ad-hoc environment described by Gu, would look for robust mechanisms to incentivize nodes. Agrawal provides just such a mechanism: a VCG auction, which is known to be "strategy-proof," meaning it incentivizes truthful bidding.

The motivation to combine these references would be to apply the powerful, strategy-proof VCG auction mechanism from Agrawal to the allocation of spatial resources (antenna beams) within the cooperative ad-hoc network context described by Gu. A PHOSITA would reason that if a VCG auction is an effective and fair way to allocate spectrum (Agrawal), it would likewise be an effective and fair way to allocate antenna directions to minimize interference and maximize overall network utility. This would be a straightforward substitution of one type of allocable wireless resource (spectrum) for another (spatial direction) within a known optimization framework (VCG auction).

Conclusion for Claim 14: The combination of Agrawal's teaching of a VCG auction for wireless resource allocation with the ad-hoc networking context of Gu would have motivated a PHOSITA to apply the VCG auction to the problem of selecting directional antenna states, thus rendering the subject matter of claim 14 obvious.