In this paper, signal space diversity (SSD) is introduced in an underlay cognitive two-way relay network where two secondary source terminals communicate with each other directly and via an intermediate secondary relay in the presence of a primary user. SSD is applied at all transmitting nodes in the secondary network to rotate and interleave the signal components before transmission that enables both source terminals and intermediate relay to transmit different symbols. Therefore, SSD enhances the mutual information of the SSD-based underlay cognitive two-way relay network compared to the conventional one. Thus, performance analysis and results of the proposed system are different than that of the conventional system. It is shown that the proposed system improves the outage performance and spectral efficiency of the underlay cognitive two-way relay network. Moreover, the closed-form expression for exact outage probability of the proposed system is derived over Rayleigh fading channels. Monte Carlo simulations are carried out to validate the analytical work. In all analysis, interference power constraints and correlation among signal-to-noise ratios are taken into consideration to provide accurate results. Furthermore, the impact of channel estimation error on the outage probability of the system is investigated and the closed-form expression of the outage probability is derived.

Entrepreneurially Minded Learning is a pedagogical technique that seeks to equip students to be more curious about trends in the changing world, make connections from disparate sources of information to gain insight, and identify unexpected opportunities to create extraordinary value for themselves and their communities. The core of the entrepreneurial mindset can be summarized succinctly by the three Cs: Curiosity, Connections, and Creating value. This interactive workshop will introduce participants to these three Cs using three specific tools that facilitators have successfully used in their engineering classrooms. The workshop is targeted towards a total of 40 participants and will require only projection capabilities for audio-visual equipment.

In recent years, entrepreneurial mindset has become a hot topic in engineering education. The core of the entrepreneurial mindset on which we focus is summarized succinctly by the three C's: Curiosity, Connections, and Creating value. This paper describes ways to use a tool within the engineering curriculum focused on creating value. Specifically, we utilize the Need-Approach-Benefits-Competition (NABC) framework developed by Stanford Research International to teach engineering students how to articulate value propositions. Our teaching approach involves multiple assignments or projects that expose students to the NABC framework in several core engineering courses, with each subsequent assignment building on the previous experience that the cohort of students has with the NABC framework (i.e., a spiral approach). We argue that such a spiral approach using the NABC framework is advantageous in order to instill a value creation mindset in engineering students.

One of the key goals as an educator is to stimulate the curiosity of students in order to instill a desire to further explore and learn the subject matter outside of the classroom. Another important goal, often underemphasized, is to enhance the student's ability to formulate questions relevant to the subject matter. In this paper, we describe a technique, called the Question Formulation Technique (QFT), which is well established in the K-12 environment, and elaborate on several ways in which QFT may be utilized to stimulate curiosity and hone question formulation ability in a core undergraduate engineering course, Electric Circuits. While many of the details of the QFT implementations are specific to the Electric Circuits course, the essential elements may easily be extrapolated to any core engineering course.

In a competitive global economy, it is important for engineering students to develop entrepreneurial skills that include effective collaboration and communication, persisting and learning from failure, management, and solving ambiguous problems. This paper summarizes a project that aims to instill these skills as part of an entrepreneurial mindset in engineering students. The project was implemented in an introductory electric circuits class with a mixed representation of students majoring in electrical, computer, civil, and mechanical engineering. Students were organized into groups of two or three to design a temperature sensor using a negative temperature coefficient thermistor. Students groups were provided with customer specifications and were given a month to research the problem and obtain a viable solution. The groups were required to provide evidence compiled into a written product proposal that included a bill of materials, cost analysis, circuit design and simulation, testing plan, layout of the printed circuit board and packaging schematic, delivery time, and the voltage-temperature relationship of the designed circuit. After submitting the written proposal, each group was given five minutes to pitch their proposal using a poster in an effort to convince the customer (in this case, the instructor) that their design was the best and most cost-effective solution.

In this paper, we study local interaction rules that enable a network of dynamic agents to synchronize to a common zero-input state trajectory despite the malicious influence of a subset of adversary agents. The agents in the networked system influence one another by sharing state or output information according to a directed, time-varying graph. The normal agents have identical dynamics modeled by linear time-invariant (LTI) systems that are weakly stable, stabilizable, and detectable. The adversary agents are assumed to be omniscient and can take any uniformly continuous state or output trajectory. We design dynamic state and output control laws under the assumption that there is either an upper bound on the number of neighbors that may be adversaries, or an upper bound on the total number of adversary agents in the network. The control laws use only local information (i.e., information from neighbors in the network) and are resilient in the sense that they are able to mitigate the malicious influence of the adversary nodes and facilitate asymptotic synchronization of the normal agents. The conditions on the network topology required for the success of the synchronization control laws are specified in terms of network robustness. Network robustness is a novel topological property that codifies the notion of sufficient redundancy of directed edges between subsets of nodes in the network.

This paper addresses the problem of resilient in-network consensus in the presence of misbehaving nodes. Secure and fault-tolerant consensus algorithms typically assume knowledge of nonlocal information; however, this assumption is not suitable for large-scale dynamic networks. To remedy this, we focus on local strategies that provide resilience to faults and compromised nodes. We design a consensus protocol based on local information that is resilient to worst-case security breaches, assuming the compromised nodes have full knowledge of the network and the intentions of the other nodes. We provide necessary and sufficient conditions for the normal nodes to reach asymptotic consensus despite the influence of the misbehaving nodes under different threat assumptions. We show that traditional metrics such as connectivity are not adequate to characterize the behavior of such algorithms, and develop a novel graph-theoretic property referred to as network robustness. Network robustness formalizes the notion of redundancy of direct information exchange between subsets of nodes in the network, and is a fundamental property for analyzing the behavior of certain distributed algorithms that use only local information.

Recently, many applications have arisen in distributed control that require consensus protocols. Concurrently, we have seen a proliferation of malicious attacks on large-scale distributed systems. Hence, there is a need for (i) consensus problems that take into consideration the presence of adversaries and specify correct behavior through appropriate conditions on agreement and safety, and (ii) algorithms for distributed control applications that solve such consensus problems resiliently despite breaches in security. This paper addresses these issues by (i) defining the adversarial asymptotic agreement problem, which requires that the uncompromised agents asymptotically align their states while satisfying an invariant condition in the presence of adversaries, and (ii) by designing a low complexity consensus protocol, the Adversarial Robust Consensus Protocol (ARC-P), which combines ideas from distributed computing and cooperative control. Two types of omniscient adversaries are considered: (i) Byzantine agents can convey different state trajectories to different neighbors in the network, and (ii) malicious agents must convey the same information to each neighbor. For each type of adversary, sufficient conditions are provided that ensure ARC-P guarantees the agreement and safety conditions in static and switching network topologies, whenever the number of adversaries in the network is bounded by a constant. The conservativeness of the conditions is examined, and the conditions are compared to results in the literature.

The integration of physical systems through computing and networking has become pervasive, a trend now known as cyber-physical systems (CPS). Functionality in CPS emerges from the interaction of networked computational and physical objects. System design and integration are particularly challenging because fundamentally different physical and computational design concerns intersect. The impact of these interactions is the loss of compositionality which creates tremendous challenges. The key idea in this article is to use passivity for decoupling the control design of networked systems from uncertainties such as time delays and packet loss, thus providing a fundamental simplification strategy that limits the complexity of interactions. The main contribution is the application of the approach to an experimental case study of a networked multi-robot system. We present a networked control architecture that ensures the overall system remains stable in spite of implementation uncertainties such as network delays and data dropouts, focusing on the technical details required for the implementation. We describe a prototype domain-specific modeling language and automated code generation tools for the design of networked control systems on top of passivity that facilitate effective system configuration, deployment, and testing. Finally, we present experimental evaluation results that show decoupling of interlayer interactions.

In the past decade, numerous consensus protocols for networked multi-agent systems have been proposed. Although some forms of robustness of these algorithms have been studied, reaching consensus securely in networked multi-agent systems, in spite of intrusions caused by malicious agents, or adversaries, has been largely underexplored. In this work, we consider a general model for adversaries in Euclidean space and introduce a consensus problem for networked multi-agent systems similar to the Byzantine consensus problem in distributed computing. We present the Adversarially Robust Consensus Protocol (ARC-P), which combines ideas from consensus algorithms that are resilient to Byzantine faults and from linear consensus protocols used for control and coordination of dynamic agents. We show that ARC-P solves the consensus problem in complete networks whenever there are more cooperative agents than adversaries. Finally, we illustrate the resilience of ARC-P to adversaries through simulations and compare ARC-P with a linear consensus protocol for networked multi-agent systems.