Wireless communication has become a key technology for competitiveness of next generation vehicles. Recently, the 3GPP has initiated standardization activities for LTE-based V2X services composed of vehicle-to-vehicle, vehicle-to-pedestrian, and vehicle-to-infrastructure/ network. The goal of these 3GPP activities is to enhance LTE systems to enable vehicles to communicate with other vehicles, pedestrians, and infrastructure in order to exchange messages for aiding in road safety, controlling traffic flow, and providing various traffic notifications. In this article, we provide an overview of the service flow and requirements of the V2X services LTE systems are targeting. This article also discusses the scenarios suitable for operating LTE-based V2X services, and addresses the main challenges of high mobility and densely populated vehicle environments in designing technical solutions to fulfill the requirements of V2X services. Leveraging the spectral-efficient air interface, the cost-effective network deployment, and the versatile nature of supporting different communication types, LTE systems along with proper enhancements can be the key enabler of V2X services.Hanbyul Seo and Ki-Dong Lee are with LG Electronics; Shinpei Yasukawa is with NTT DoCoMo; Ying Peng is with CATT; Philippe Sartori is with Huawei.

Interference alignment is a signaling technique that provides high multiplexing gain in the interference channel. It can be extended to multi-hop interference channels, where relays aid transmission between sources and destinations. In addition to coverage extension and capacity enhancement, relays increase the multiplexing gain in the interference channel. In this paper, three cooperative algorithms are proposed for a multiple-antenna amplify-and-forward (AF) relay interference channel. The algorithms design the transmitters and relays so that interference at the receivers can be aligned and canceled. The first algorithm minimizes the sum power of enhanced noise from the relays and interference at the receivers. The second and third algorithms rely on a connection between mean square error and mutual information to solve the end-to-end sum-rate maximization problem with either equality or inequality power constraints via matrix-weighted sum mean square error minimization. The resulting iterative algorithms converge to stationary points of the corresponding optimization problems. Simulations show that the proposed algorithms achieve higher end-to-end sum-rates and multiplexing gains that existing strategies for AF relays, decode-and-forward relays, and direct transmission. The first algorithm outperforms the other algorithms at high signal-to-noise ratio (SNR) but performs worse than them at low SNR. Thanks to power control, the third algorithm outperforms the second algorithm at the cost of overhead.Comment: submitted to IEEE Transactions on Signal Processing in December 2011, revised in April 2012 and in September 201

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