consumption model where the dissipation in circuits depends non-linearly on the above parameters. Simple closed-form expressions for the EE-maximizing parameter values and their scaling behaviors are derived for zero-forcing (ZF) processing with perfect channel state information (CSI) and verified by simulations for other processing schemes under imperfect CSI.

The EE analysis of multi-cellular networks is much more involved than in the single-cell case due to the complicated network topology and the arising inter-cell interference. The simplest approach is to rely on heavy Monte Carlo simulations. Attempts in this direction can be found in [@Kurniawan2012] and [@Liu2013]. Unfortunately, Monte Carlo simulated results are often anecdotal since one cannot separate fundamental properties from behaviors induced by parameter selection. Alternatively, simplified network topologies can be considered, such as the Wyner model [@Wyner1994a] or the symmetric grid-based deployment [@Bjornson2015a]. While attractive for its analytical simplicity, the Wyner model does not well capture the essential characteristics of real and practical networks [@Xu2011a]. Similarly, the symmetric grid-based models cannot capture the irregular structure of small-cell network deployments.

The need for developing tractable (yet reasonably accurate) models for future dense networks has increased the interest in random spatial models; more particularly, in using tools from stochastic geometry 