Arms race is a typical conflict among rational and non-myopic decision-makers (DMs). Nevertheless, the assumption of basis graph model for conflict resolution (GMCR) is not suitable for this issue that each DM possesses identical priority disregarding the difference of their capabilities. In order to handle with this drawback, this paper proposes a novel methodology, entitled capability-based GMCR. First, performance criteria and capability parameters are investigated through feature analysis for arms race. Then, definitions and algorithms to quantify their impacts are presented for preferences elicitation. Finally, an illustrative example is utilized to demonstrate the proposed approach and analysis results are discussed to summarize related conclusions.

Coordinated Multipoint (CoMP) techniques have promised substantial throughput improvement by exploiting the cooperation across base stations in cellular networks. In addition to the high computation and implementation complexity, existing CoMP proposals also require different base stations to exchange co-channel condition information through backhaul links. Such cooperation incurs additional costs in pilots and backhaul bandwidth, which in turn reduces the resource allocated to data transmission. Therefore, the promised throughput gain is greatly degraded in practical applications. Aiming to overcome this limitation, we develop a novel coordinated power control scheme for uplink cellular networks, named Checks and Balances (C&B), which can realize the potential benefits of CoMP with minimum complexity and cost. C&B checks the signal strength of one user and its generated interference to neighboring base stations, and tries to balance the two. We evaluate the throughput performance of C&B on an LTE system-level simulation platform, which is carefully calibrated with Huawei. Our simulation results suggest that C&B achieves up to 52% increase in average throughput, and up to 156% increase in edge-user throughput, compared to existing power control schemes.

We consider a system in which two nodes take correlated measurements of a random source with time-varying and unknown statistics. The observations of the source at the first node are to be losslessly replicated with a given probability of outage at the second node, which receives data from the first node over a constant-rate channel. We develop a system and associated strategies for joint distributed source coding (encoding and decoding) and transmission control in order to achieve low end-to-end delay. Slepian-Wolf coding in its traditional form cannot be applied in our scenario, since the encoder requires the joint statistics of the observations and the associated decoding delay is very high. We analytically evaluate the performance of our strategies and show that the delay achieved by them are order optimal, as the conditional entropy of the source approaches to the channel rate. We also evaluate the performance of our algorithms based on real-world experiments using two cameras recording videos of a scene at different angles. Having realized our schemes, we demonstrated that, even with a very low-complexity quantizer, a compression ratio of approximately 50% is achievable for lossless replication at the decoder, at an average delay of a few seconds.

There has been numerous studies on the security of vehicular networks, focusing mainly at higher layers of the network stack. Vulnerabilities of vehicular communications at the physical layer have not been explored thoroughly. To that end, we study internal and external vehicular communication under a variety of attack strategies involving jamming at the physical layer. We consider a couple of attack strategies, differing in how the attacker jams the resource blocks within a targeted spectrum. In particular, we focus on flat and random jamming, which are oblivious to the existing assignments and smart jamming, which senses the assignments and allocates power in frequency accordingly. For intra- vehicular setting, we consider an attacker attached to various locations within the vehicle. We used software-defined radios in an actual vehicle to emulate potential realistic attack setups and tested the effectiveness of various attack strategies. We show that, the smart jamming attack can lead to significant degradations in communication performance, to the extent of a complete blockage even with a low jamming power, in most setups. For external communication setting, we consider a busy intersection and study uplink communication in a multicellular LTE network. Using a system-level LTE simulator we developed, we show that a flat jamming attack by a static attacker can degrade the global performance significantly, while the smart jamming attack by a stalking attacker can almost block the communication initiated from a targeted vehicle. In short, we demonstrate via real-world experiments and system-level simulations that, with an appropriate strategy, the impact of a physical layer jamming attacker can be highly detrimental to both internal and external vehicular communication, seriously threatening the security of vehicular networks.