Modeling and Performance of Uplink Cache-Enabled Massive MIMO Heterogeneous Networks

Abstract

A significant burden on wireless networks is brought by the uploading of user-generated contents to the Internet by means of applications such as the social media. To cope with this mobile data tsunami, we develop a novel multipleinput multiple-output (MIMO) network architecture with randomly located base stations (BSs) a large number of antennas employing cache-enabled uplink transmission. In particular, we formulate a scenario, where the users upload their content to their strongest base stations (BSs), which are Poisson point process (PPP) distributed. In addition, the BSs, exploiting the benefits of massive MIMO, upload their contents to the core network by means of a finite-rate backhaul. After proposing the caching policies, where we propose the modified von Mises distribution as the popularity distribution function, we derive the outage probability and the average delivery rate by taking advantage of tools from the deterministic equivalent (DE) and stochastic geometry analyses. Numerical results investigate the realistic performance gains of the proposed heterogeneous cacheenabled uplink on the network in terms of cardinal operating parameters. For example, insights regarding the BSs storage size are exposed. Moreover, the impacts of the key parameters such the file popularity distribution, and the target bitrate are investigated. Specifically, the outage probability decreases if the storage size is increased, while the average delivery rate increases. In addition, the concentration parameter, defining the number of files stored at the intermediate nodes (popularity), affects directly the proposed metrics. Furthermore, a higher target rate results in higher outage because fewer users obey this constraint. Also, we demonstrate that a denser network decreases the outage and increases the delivery rate. Hence, the introduction of caching at the uplink of the system design ameliorates the network performance.

On the Performance of Cache-Enabled Hybrid Wireless Networks

“…is the distribution of the serving distance between the serving BS and the typical user given as (11). Now, the aim is to compute the expectation term in the integral with respect to the interference.…”

“…For tractability, we consider λ FR2 that appears in the rateRx FR1 as constant (in order to choose the initial point). This is due to the fact that λ FR2 plays a prominent role for the case of small cells only 11. Note that in a x-term approximation, with x ∈ {1, 2, .…”

Performance Analysis on Cache-Enabled FR2 IAB Networks

“…Further, stochastic-geometry-based cache-enabled small cell networks was analyzed in terms of the outage probability and average content delivery rate in [5] and cache miss probability with respect to storage-bandwidth tradeoff in [6]. Next, 5G enabling solutions amalgamated with WEC, such as cache-enabled FR2 networks and massive multi-input multi-output (mMIMO)-aided self-backhauled dense HetNets were studied in [7] and [8]- [10], respectively. Further, WEC was applied to FR1-FR2 hybrid networks in [11], where the optimal caching placement algorithm was proposed to minimize the average success probability (ASP) of file delivery.…”

SDN-Enabled MIMO Heterogeneous Cooperative Networks With Flexible Cell Association

“…Although the beginning of the research in HetNets involved single-antenna base stations (BSs) [8], [9], current studies have considered the symbiosis and synergy of HetNets and multiantenna techniques as the literature reveals [10]- [13]. In this direction, powerful tools from stochastic geometry have allowed the tractable characterization of even multi-user multiple-input multiple-output (MU-MIMO) HetNets [10], [13]- [15].…”

“…Although the beginning of the research in HetNets involved single-antenna base stations (BSs) [8], [9], current studies have considered the symbiosis and synergy of HetNets and multiantenna techniques as the literature reveals [10]- [13]. In this direction, powerful tools from stochastic geometry have allowed the tractable characterization of even multi-user multiple-input multiple-output (MU-MIMO) HetNets [10], [13]- [15]. One of the main observations is that single user beamforming (SU-BF) may result in better coverage on the downlink than multi-user (MU) beamforming such as space division multiple access (SDMA) in the case of perfect channel state information (CSI).…”