Enhancing Performance of Random Caching in Large-Scale Wireless Networks With Multiple Receive Antennas

Abstract

To improve signal-to-interference ratio (SIR) and make better use of file diversity provided by random caching, we consider two types of linear receivers, i.e., maximal ratio combining (MRC) receiver and partial zero forcing (PZF) receiver, at users in a large-scale cache-enabled single-input multi-output (SIMO) network. First, for each receiver, by utilizing tools from stochastic geometry, we derive a tractable expression and a tight upper bound for the successful transmission probability (STP). In the case of the MRC receiver, we also derive a closed-form expression for the asymptotic outage probability in the low SIR threshold regime. Then, for each receiver, we maximize the STP. In the case of the MRC receiver, we consider the maximization of the tight upper bound on the STP by optimizing the caching distribution, which is a non-convex problem. We obtain a stationary point, by solving an equivalent difference of convex (DC) programming problem using concave-convex procedure (CCCP). We also obtain a closed-form asymptotically optimal solution in the low SIR threshold regime. In the case of the PZF receiver, we consider the maximization of the tight upper bound on the STP by optimizing the caching distribution and the degrees of freedom (DoF) allocation (for boosting the signal power), which is a mixed discrete-continuous problem. Based on structural properties, we obtain a low-complexity near optimal solution by using an alternating optimization approach. The analysis and optimization results reveal the impact of antenna resource at users on random caching. Finally, by numerical results, we show that the random caching design with the PZF receiver achieves significant performance gains over the random caching design with the MRC receiver and some baseline caching designs.

Enhancing Performance of Random Caching in Large-Scale Heterogeneous Wireless Networks With Random Discontinuous Transmission

“…When the coverage regions of different BSs overlap, a user can fetch the desired file from multiple adjacent BSs, and hence the performance can be increased by caching different files among BSs, i.e., providing file diversity. In [3]- [16], the authors analyze the performance of various caching designs in large-scale cache-enabled wireless networks. In particular, in [3] and [4], the authors study the most popular caching design, where each BS only stores the most popular files.…”

“…As the most popular caching design can not provide any spatial file diversity, it may not yield the optimal network performance. To provide more spatial file diversity, the authors in [5]- [16] consider random caching. Specifically, in [5], the authors consider uniform caching where each BS randomly stores a file according to the uniform distribution.…”

“…In [7]- [16], besides analysis, the authors also consider the optimization of random caching to either maximize the cache hit probability [7], [8], the successful offloading probability [9] and the successful transmission probability (STP) [10]- [14], [16] or minimize the average caching failure probability [15]. Note that, in [5]- [16], a user may associate with a relatively farther BS when nearer BSs do not cache the requested file [16]. In this case, the signal is usually weak compared with the interference, and the user may not successfully receive the requested file and benefit from the file diversity offered by random caching.…”

Enhancing Physical Layer Security of Random Caching in Large-Scale Multi-Antenna Heterogeneous Wireless Networks

“…Similarly, we define the confidential transmission probability (CTP) of file n as the probability that the transmission of file n is confidential, which is expressed as (14), as shown at the top of the next page. Remark 1 (Interpretation of RTP and CTP of file n): The RTP and the CTP of file n measure the transmission reliability and the transmission confidentiality of file n, respectively.…”

Optimal content placement for cache‐enabled IoT networks with local channel state information based joint transmission

“…There are two main categories of research problems with respect to caching, i.e. content placement strategy design [3–10] and content delivery strategy design [11–14]. Carefully designing the placement strategy can take full advantage of file diversity gains provided by caching due to the limited size of the local caches at edge notes.…”