Designing Wireless Broadband Access for Energy Efficiency: Are Small Cells the Only Answer?

The main usage of cellular networks has changed from voice to data traffic, mostly requested by static users. In this paper, we analyze how a cellular network should be designed to provide such wireless broadband access with maximal energy efficiency (EE). Using stochastic geometry and a detailed power consumption model, we optimize the density of access points (APs), number of antennas and users per AP, and transmission power for maximal EE. Small cells are of course a key technology in this direction, but the analysis shows that the EE improvement of a small-cell network saturates quickly with the AP density and then "massive MIMO" techniques can further improve the EE.Comment: Published at Small Cell and 5G Networks (SmallNets) Workshop, IEEE International Conference on Communications (ICC), 6 pages, 5 figures, 1 tabl

NoCo: ILP-based worst-case contention estimation for mesh real-time manycores

Manycores are capable of providing the computational demands required by functionally-advanced critical applications in domains such as automotive and avionics. In manycores a network-on-chip (NoC) provides access to shared caches and memories and hence concentrates most of the contention that tasks suffer, with effects on the worst-case contention delay (WCD) of packets and tasks' WCET. While several proposals minimize the impact of individual NoC parameters on WCD, e.g. mapping and routing, there are strong dependences among these NoC parameters. Hence, finding the optimal NoC configurations requires optimizing all parameters simultaneously, which represents a multidimensional optimization problem. In this paper we propose NoCo, a novel approach that combines ILP and stochastic optimization to find NoC configurations in terms of packet routing, application mapping, and arbitration weight allocation. Our results show that NoCo improves other techniques that optimize a subset of NoC parameters.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under grant TIN2015- 65316-P and the HiPEAC Network of Excellence. It also received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (agreement No. 772773). Carles Hernández is jointly supported by the MINECO and FEDER funds through grant TIN2014-60404-JIN. Jaume Abella has been partially supported by the Spanish Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717. Enrico Mezzetti has been partially supported by the Spanish Ministry of Economy and Competitiveness under Juan de la Cierva-Incorporaci´on postdoctoral fellowship number IJCI-2016-27396.Peer ReviewedPostprint (author's final draft

Deploying Dense Networks for Maximal Energy Efficiency: Small Cells Meet Massive MIMO

How would a cellular network designed for maximal energy efficiency look like? To answer this fundamental question, tools from stochastic geometry are used in this paper to model future cellular networks and obtain a new lower bound on the average uplink spectral efficiency. This enables us to formulate a tractable uplink energy efficiency (EE) maximization problem and solve it analytically with respect to the density of base stations (BSs), the transmit power levels, the number of BS antennas and users per cell, and the pilot reuse factor. The closed-form expressions obtained from this general EE maximization framework provide valuable insights on the interplay between the optimization variables, hardware characteristics, and propagation environment. Small cells are proved to give high EE, but the EE improvement saturates quickly with the BS density. Interestingly, the maximal EE is achieved by also equipping the BSs with multiple antennas and operate in a "massive MIMO" fashion, where the array gain from coherent detection mitigates interference and the multiplexing of many users reduces the energy cost per user.Comment: To appear in IEEE Journal on Selected Areas in Communications, 15 pages, 7 figures, 1 tabl