Random caching based cooperative transmission in heterogeneous wireless networks

Abstract

Base station cooperation in heterogeneous wireless networks (HetNets) is a promising approach to improve the network performance, but it also imposes a significant challenge on backhaul. On the other hand, caching at small base stations (SBSs) is considered as an efficient way to reduce backhaul load in HetNets. In this paper, we jointly consider SBS caching and cooperation in a downlink largescale HetNet. We propose two SBS cooperative transmission schemes under random caching at SBSs with the caching distribution as a design parameter. Using tools from stochastic geometry and adopting appropriate integral transformations, we first derive a tractable expression for the successful transmission probability under each scheme. Then, under each scheme, we consider the successful transmission probability maximization by optimizing the caching distribution, which is a challenging optimization problem with a non-convex objective function. By exploring optimality properties and using optimization techniques, under each scheme, we obtain a local optimal solution in the general case and global optimal solutions in some special cases. Compared with some existing caching designs in the literature, e.g., the most popular caching, the i.i.d. caching and the uniform caching, the optimal random caching under each scheme achieves better successful transmission probability performance. The analysis and optimization results provide valuable design insights for practical HetNets.

On LOS Contribution to Ultra-Dense Network

“…By replacing (23), (24) and (25) in (16), we have derived our approximation¯ M . Note that in case the approximated terms in (11) and (14) were not considered, the derived SCDP in (15) and (16) would write as a non solvable integral which involves a modified Bessel function of the first kind as in [10]. Also, it is known that a closed-form solution for…”

Energy-Efficient Transceiver Design for Cache-Enabled Millimeter-Wave Systems

“…Each eRRH i ∈ K R is equipped with a cache of size nB i > 0 nats, where B i is the normalized cache size. To provide the spatial file diversity (which can improve the performance of dense wireless networks) [19], each eRRH i ∈ K R randomly prestores nB i nats of nF S nats in the library to its local cache according to certain preferences [20]- [22]. In other words, each eRRH i ∈ K R randomly selects B i /S files from library F at the BBU to store at its local cache.…”

“…1) Problem Transformation: In problem (18), equality constraints (16d) and (16e) are two main obstacles for solving it. Fortunately, the researches on equality constraint optimization in [13], [14] have shown that problem (17) can be further reformulated as (19), at the bottom of the next page. In (19a), matrix Ξ s is calculated as (20), at the bottom of the next page, where Φ f,i and Ψ i are Lagrange Multiplier matrices associated with equality constraints (16d) and (16e), respectively.…”

“…Recently, to alleviate the fronthaul capacity requirement and reduce the user-perceived latency in C-RANs, an evolved cache-enabled RAN was proposed in which the remote radio heads (RRHs), referred as enhanced RRHs (eRRHs), have the abilities to store popular contents and perform baseband signal processing [3], [4]. During the off-peak traffic periods, some most frequently requested files can be pre-fetched to the local cache at the network edge to reduce delivery latency and increase spectral efficiency [17]- [19]. A cache placement strategy with limited fronthaul and cache capacity was studied to minimize the average download delay of user requests [17].…”

“…The authors of [18] investigated how to cache the files at different caching units with the objective to maximize the average requested data rate subject to a finite service latency. Successful transmission probabilities were analyzed for a two-tier large-scale cache-enabled wireless multicasting network [19]. Joint optimization of cloud-edge precoders was also investigated with aiming to maximize or minimize the system performance criterion under certain constraints for cache-enabled RANs [20]- [22].…”