The Impact of Antenna Height Difference on the Performance of Downlink Cellular Networks

Capable of significantly reducing cell size and enhancing spatial reuse, network densification is shown to be one of the most dominant approaches to expand network capacity. Due to the scarcity of available spectrum resources, nevertheless, the over-deployment of network infrastructures, e.g., cellular base stations (BSs), would strengthen the inter-cell interference as well, thus in turn deteriorating the system performance. On this account, we investigate the performance of downlink cellular networks in terms of user coverage probability (CP) and network spatial throughput (ST), aiming to shed light on the limitation of network densification. Notably, it is shown that both CP and ST would be degraded and even diminish to be zero when BS density is sufficiently large, provided that practical antenna height difference (AHD) between BSs and users is involved to characterize pathloss. Moreover, the results also reveal that the increase of network ST is at the expense of the degradation of CP. Therefore, to balance the tradeoff between user and network performance, we further study the critical density, under which ST could be maximized under the CP constraint. Through a special case study, it follows that the critical density is inversely proportional to the square of AHD. The results in this work could provide helpful guideline towards the application of network densification in the next-generation wireless networks.Comment: conference submission - Mar. 201

Distributed Energy and Resource Management for Full-Duplex Dense Small Cells for 5G

We consider a multi-carrier and densely deployed small cell network, where small cells are powered by renewable energy source and operate in a full-duplex mode. We formulate an energy and traffic aware resource allocation optimization problem, where a joint design of the beamformers, power and sub-carrier allocation, and users scheduling is proposed. The problem minimizes the sum data buffer lengths of each user in the network by using the harvested energy. A practical uplink user rate-dependent decoding energy consumption is included in the total energy consumption at the small cell base stations. Hence, harvested energy is shared with both downlink and uplink users. Owing to the non-convexity of the problem, a faster convergence sub-optimal algorithm based on successive parametric convex approximation framework is proposed. The algorithm is implemented in a distributed fashion, by using the alternating direction method of multipliers, which offers not only the limited information exchange between the base stations, but also fast convergence. Numerical results advocate the redesigning of the resource allocation strategy when the energy at the base station is shared among the downlink and uplink transmissions.Comment: In Proc. of IEEE IWCMC-2017, Valencia, Spain, Jun. 201