2 research outputs found
Mixed-Timescale Online PHY Caching for Dual-Mode MIMO Cooperative Networks
Recently, physical layer (PHY) caching has been proposed to exploit the
dynamic side information induced by caches at base stations (BSs) to support
Coordinated Multi-Point (CoMP) and achieve huge degrees of freedom (DoF) gains.
Due to the limited cache storage capacity, the performance of PHY caching
depends heavily on the cache content placement algorithm. In existing
algorithms, the cache content placement is adaptive to the long-term popularity
distribution in an offline manner. We propose an online PHY caching framework
which adapts the cache content placement to microscopic spatial and temporary
popularity variations to fully exploit the benefits of PHY caching.
Specifically, the joint optimization of online cache content placement and
content delivery is formulated as a mixed-timescale drift minimization problem
to increase the CoMP opportunity and reduce the cache content placement cost.
We propose a low-complexity algorithm to obtain a throughput-optimal solution.
Moreover, we provide a closed-form characterization of the maximum sum DoF in
the stability region and study the impact of key system parameters on the
stability region. Simulations show that the proposed online PHY caching
framework achieves large gain over existing solutions.Comment: 34 pages, 7 figure
Joint Long-Term Cache Updating and Short-Term Content Delivery in Cloud-Based Small Cell Networks
Explosive growth of mobile data demand may impose a heavy traffic burden on
fronthaul links of cloud-based small cell networks (C-SCNs), which deteriorates
users' quality of service (QoS) and requires substantial power consumption.
This paper proposes an efficient maximum distance separable (MDS) coded caching
framework for a cache-enabled C-SCNs, aiming at reducing long-term power
consumption while satisfying users' QoS requirements in short-term
transmissions. To achieve this goal, the cache resource in small-cell base
stations (SBSs) needs to be reasonably updated by taking into account users'
content preferences, SBS collaboration, and characteristics of wireless links.
Specifically, without assuming any prior knowledge of content popularity, we
formulate a mixed timescale problem to jointly optimize cache updating,
multicast beamformers in fronthaul and edge links, and SBS clustering.
Nevertheless, this problem is anti-causal because an optimal cache updating
policy depends on future content requests and channel state information. To
handle it, by properly leveraging historical observations, we propose a
two-stage updating scheme by using Frobenius-Norm penalty and inexact block
coordinate descent method. Furthermore, we derive a learning-based design,
which can obtain effective tradeoff between accuracy and computational
complexity. Simulation results demonstrate the effectiveness of the proposed
two-stage framework.Comment: Accepted by IEEE Trans. Commu