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

Cross-layer design for single-cell OFDMA systems with heterogeneous QoS and partial CSIT

Abstract— This paper proposes a novel cross-layer scheduling scheme for a single-cell orthogonal frequency division multiple access (OFDMA) wireless system with partial channel state information (CSI) at transmitter (CSIT) and heterogeneous user delay requirements. Previous research efforts on OFDMA resource allocation are typically based on the availability of perfect CSI or imperfect CSI but with small error variance. Either case consists to typify a non tangible system as the potential facts of channel feedback delay or large channel estimation errors have not been considered. Thus, to attain a more realistic resolution our cross-layer design determines optimal subcarrier and power allocation policies based on partial CSIT and individual user’s quality of service (QoS) requirements. The simulation results show that the proposed cross-layer scheduler can maximize the system’s throughput and at the same time satisfy heterogeneous delay requirements of various users with significant low power consumption

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs