Wireless communication systems are faced with superlative challenges. The advent of the smartphone era, initiated in 2007 with the launch of the first iPhone, has created an unexpected volume of data which brought to its knees the cellular telephony infrastructure, demonstrating that it is rigid, costly, and ill-suited to rapid evolution. In contrast, the other technology through which we consume wireless data, WiFi-type wireless networks, offers rapid, flexible, and low-cost deployment. However, such networks are limited in range, and — being victimes of their own success — were never intended for the volume of traffic they currently bear. Furthermore, they cannot guarantee quality of service, neither in delay nor in throughput, given their random and unstructured nature.
In this context, the continued evolution of wireless communications is faced with two important barriers, and profound innovations are called for to overcome them. Internet traffic is predicted to triple between 2017 and 2022, by which time 80% of the traffic will be video, and 20% of the traffic will be mobile. This is evocative of the first barrier, which consists in the explosion of data traffic. In parallel, to address this increasing demand and continue to evolve, wireless network and radio resource allocation processes are becoming increasingly multidimensional and complex, making them nearly intractable with traditional top-down deterministic approaches. More organic and flexible approaches are called for, including self-organization and forms of artificial intelligence. This is the second barrier, namely increasing logistic complexity.
Research activities center on the above crucial challenges within a systemic framework. Adaptive antenna arrays, or smart antennas, constitute one major thrust given their status as a keystone technology enabling an order-of-magnitude increase of the user population and data volume per user. Specifically, we look at the practical and implementation aspects of such technologies in order to reduce their cost and / or energy footprint. Also, we consider the feasibility of practical systems with massive numbers of antennas (hundreds or even thousands of antennas). To address the logistic barrier mentioned above, self-organization approaches based on distributed intelligence concepts (swarming, emergent behavior) and spontaneous cooperation are being studied. The application of both smart antennas and self-organization to wireless sensor networks comprised of very large numbers of simple energy-limited nodes is also of interest.