Paul DE KERRET
ThesisDistributed cooperation in interference-limited wireless networks
Recent research on cooperative communications has revealed that tools from MIMO theory, and more generally spatial processing, are instrumental in reaching the upper limits of capacity in large and dense networks . Indeed an ideal bound on the capacity can be envisioned by treating every transmitting/receiving node of the network as an element in a huge distributed MIMO array of antenna, thus exhibiting maximum spatial processing related gains:
Diversity, multiplexing, beamforming and interference mitigation gains. In this setup, the denser the network gets, the more spatial degrees of freedom are left for use in its optimization.
However, the ideal MIMO bounds and techniques are not applicable as is in real-life networks: First, devices (especially at user end) are characterized by limited computational capability (consistent with low power constraint), and size.
Second, the knowledge of the propagation environment at any one device will be limited to local channel conditions only (i.e. the channel conditions directly observable from measurements at that device) in order to limit the inter-node signaling. Exchange of channel-related knowledge between nodes directly competes with the resource allocated to the payload data transfer itself. This prohibits the form of centralized optimization which is typically assumed when applying traditional spatial processing (precoding, decoding).