Fronthaul data compression for Uplink CoMP in cloud radio access network (C-RAN)

The design of efficient wireless fronthaul connections for future heterogeneous networks incorporating emerging paradigms such as cloud radio access network has become a challenging task that requires the most effective utilisation of fronthaul network resources. In this paper, we propose to use distributed compression to reduce the fronthaul traffic in uplink Coordinated Multi-Point for cloud radio access network. Unlike the conventional approach where each coordinating point quantises and forwards its own observation to the processing centre, these observations are compressed before forwarding. At the processing centre, the decompression of the observations and the decoding of the user message are conducted in a successive manner. The essence of this approach is the optimisation of the distributed compression using an iterative algorithm to achieve maximal user rate with a given fronthaul rate. In other words, for a target user rate the generated fronthaul traffic is minimised. Moreover, joint decompression and decoding is studied and an iterative optimisation algorithm is devised accordingly. Finally, the analysis is extended to multi-user case and our results reveal that, in both dense and ultra-dense urban deployment scenarios, the usage of distributed compression can efficiently reduce the required fronthaul rate and a further reduction is obtained with joint operation

Fronthaul-Constrained Cloud Radio Access Networks: Insights and Challenges

As a promising paradigm for fifth generation (5G) wireless communication systems, cloud radio access networks (C-RANs) have been shown to reduce both capital and operating expenditures, as well as to provide high spectral efficiency (SE) and energy efficiency (EE). The fronthaul in such networks, defined as the transmission link between a baseband unit (BBU) and a remote radio head (RRH), requires high capacity, but is often constrained. This article comprehensively surveys recent advances in fronthaul-constrained C-RANs, including system architectures and key techniques. In particular, key techniques for alleviating the impact of constrained fronthaul on SE/EE and quality of service for users, including compression and quantization, large-scale coordinated processing and clustering, and resource allocation optimization, are discussed. Open issues in terms of software-defined networking, network function virtualization, and partial centralization are also identified.Comment: 5 Figures, accepted by IEEE Wireless Communications. arXiv admin note: text overlap with arXiv:1407.3855 by other author

Online edge caching and wireless delivery in fog-aided networks

Multimedia content is the significant fraction of transferred data over the wireless medium in the modern cellular and wireless communication networks. To improve the quality of experience perceived by users, one promising solution is to push the most popular contents as close as to users, also known as the edge of network. Storing content at the edge nodes (ENs) or base stations (BSs) is called caching . In Fog Radio Access Network (F-RAN), each EN is equipped with a cache as well as a fronthaul connection to the content server. Among the new design problems raised by the outlined scenarios, two key issues are addressed in this dissertation: 1) How to utilize cache and fronthaul resources while taking into account the wireless channel impairments; 2) How to incorporate the time-variability of popular set in the performance evaluation of F-RAN. These aspects are investigated by using information-theoretic models, obtaining fundamental insights that have been corroborated by various illustrative examples. To address point 1), two scenarios are investigated. First, a single-cell scenario with two transmitters is considered. A fog-aided small-cell BS as one of the transmitters and a cloud-aided macro-cell BS as the second transmitter collaborate with each other to send the requested content over a partially connected wireless channel. The intended and interference channels are modeled by erasure channels. Assuming a static set of popular contents, offline caching maps the library of files to cached contents stored at small-cell BS such that the cache capacity requirement is met. The delivery time per bit (DTB) is adopted as a measure of the coding latency, that is, the duration of the transmission block, required for reliable delivery. It is proved that optimal DTB is a linear decreasing function of cache capacity as well as inversely proportional with capacity of fronthaul link. In the second scenario, the same single-cell model is used with the only caveat that the set of popular files is time-varying. In this case, online caching maps the library of files to cached contents at small-cell BS. Thanks to availability of popular set at macro-BS, the DTB is finite and has upper and lower bounds which are functions of system resources i.e., cache and fronthaul link capacities. As for point 2), the model is comprised of an arbitrary number of ENs and users connected through an interference-limited wireless channel at high-SNR regime. All equally important ENs are benefited from cache capacity as well as fronthaul connection to the content server. The time-variability of popular set necessitates online caching to enable ENs keep track of changes in the popular set. The analysis is centered on the characterization of the long-term Normalized Delivery Time (NDT), which captures the temporal dependence of the coding latencies accrued across multiple time slots in the high-SNR regime. Online edge caching and delivery schemes based on reactive and proactive caching principles are investigated for both serial and pipelined transmission modes across fronthaul and edge segments. The outcome of analytical results provides a controversial view of contemporary research on the edge caching. It is proved that with a time-varying set of popular files, the capacity of fronthaul link between ENs and content server set a fundamental limit on the system performance. This is due to the fact that the original information source is content server and the only way to retrieve information is via fronthaul links. While edge caching can provide some gains in term of reduced latency, the gain diminishes as a result of the fact that the cached content is prone to be outdated with time-varying popularity

Ieee access special section editorial: Cloud and big data-based next-generation cognitive radio networks

In cognitive radio networks (CRN), secondary users (SUs) are required to detect the presence of the licensed users, known as primary users (PUs), and to find spectrum holes for opportunistic spectrum access without causing harmful interference to PUs. However, due to complicated data processing, non-real-Time information exchange and limited memory, SUs often suffer from imperfect sensing and unreliable spectrum access. Cloud computing can solve this problem by allowing the data to be stored and processed in a shared environment. Furthermore, the information from a massive number of SUs allows for more comprehensive information exchanges to assist the