On the Benefits of Edge Caching for MIMO Interference Alignment

Abstract

In this contribution, we jointly investigate the benefits of caching and interference alignment (IA) in multiple-input multiple-output (MIMO) interference channel under limited backhaul capacity. In particular, total average transmission rate is derived as a function of various system parameters such as backhaul link capacity, cache size, number of active transmitter-receiver pairs as well as the quantization bits for channel state information (CSI). Given the fact that base stations are equipped both with caching and IA capabilities and have knowledge of content popularity profile, we then characterize an operational regime where the caching is beneficial. Subsequently, we find the optimal number of transmitter-receiver pairs that maximizes the total average transmission rate. When the popularity profile of requested contents falls into the operational regime, it turns out that caching substantially improves the throughput as it mitigates the backhaul usage and allows IA methods to take benefit of such limited backhaul.

20 pages, 5 figures. A shorter version is to be presented at 16th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC'2015), Stockholm, Sweden

References in corpus (4)

• Optimal Geographic Caching In Cellular Networks
• Interference Alignment with Limited Feedback
• Performance Analysis and Optimization for Interference Alignment over MIMO Interference Channels with Limited Feedback
• Device-to-Device Data Storage with Regenerating Codes

Cited by in corpus (4)

• Edge Learning for B5G Networks with Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing
• Application of Machine Learning in Wireless Networks: Key Techniques and Open Issues
• Fundamental Limits of Cache-Aided Wireless BC: Interplay of Coded-Caching and CSIT Feedback
• Modeling and Analysis for Cache-Enabled Networks with Dynamic Traffic