Joint Power Control and Fronthaul Rate Allocation for Throughput Maximization in OFDMA-based Cloud Radio Access Network

The performance of cloud radio access network (C-RAN) is constrained by the limited fronthaul link capacity under future heavy data traffic. To tackle this problem, extensive efforts have been devoted to design efficient signal quantization/compression techniques in the fronthaul to maximize the network throughput. However, most of the previous results are based on information-theoretical quantization methods, which are hard to implement due to the extremely high complexity. In this paper, we consider using practical uniform scalar quantization in the uplink communication of an orthogonal frequency division multiple access (OFDMA) based C-RAN system, where the mobile users are assigned with orthogonal sub-carriers for multiple access. In particular, we consider joint wireless power control and fronthaul quantization design over the sub-carriers to maximize the system end-to-end throughput. Efficient algorithms are proposed to solve the joint optimization problem when either information-theoretical or practical fronthaul quantization method is applied. Interestingly, we find that the fronthaul capacity constraints have significant impact to the optimal wireless power control policy. As a result, the joint optimization shows significant performance gain compared with either optimizing wireless power control or fronthaul quantization alone. Besides, we also show that the proposed simple uniform quantization scheme performs very close to the throughput performance upper bound, and in fact overlaps with the upper bound when the fronthaul capacity is sufficiently large. Overall, our results would help reveal practically achievable throughput performance of C-RAN, and lead to more efficient deployment of C-RAN in the next-generation wireless communication systems.Comment: submitted for possible publicatio

Green OFDMA Resource Allocation in Cache-Enabled CRAN

Cloud radio access network (CRAN), in which remote radio heads (RRHs) are deployed to serve users in a target area, and connected to a central processor (CP) via limited-capacity links termed the fronthaul, is a promising candidate for the next-generation wireless communication systems. Due to the content-centric nature of future wireless communications, it is desirable to cache popular contents beforehand at the RRHs, to reduce the burden on the fronthaul and achieve energy saving through cooperative transmission. This motivates our study in this paper on the energy efficient transmission in an orthogonal frequency division multiple access (OFDMA)-based CRAN with multiple RRHs and users, where the RRHs can prefetch popular contents. We consider a joint optimization of the user-SC assignment, RRH selection and transmit power allocation over all the SCs to minimize the total transmit power of the RRHs, subject to the RRHs' individual fronthaul capacity constraints and the users' minimum rate constraints, while taking into account the caching status at the RRHs. Although the problem is non-convex, we propose a Lagrange duality based solution, which can be efficiently computed with good accuracy. We compare the minimum transmit power required by the proposed algorithm with different caching strategies against the case without caching by simulations, which show the significant energy saving with caching.Comment: Presented in IEEE Online Conference on Green Communications (Online GreenComm), Nov. 2016 (Invited Paper

Resource Management in Converged Optical and Millimeter Wave Radio Networks: A Review

Three convergent processes are likely to shape the future of the internet beyond-5G: The convergence of optical and millimeter wave radio networks to boost mobile internet capacity, the convergence of machine learning solutions and communication technologies, and the convergence of virtualized and programmable network management mechanisms towards fully integrated autonomic network resource management. The integration of network virtualization technologies creates the incentive to customize and dynamically manage the resources of a network, making network functions, and storage capabilities at the edge key resources similar to the available bandwidth in network communication channels. Aiming to understand the relationship between resource management, virtualization, and the dense 5G access and fronthaul with an emphasis on converged radio and optical communications, this article presents a review of how resource management solutions have dealt with optimizing millimeter wave radio and optical resources from an autonomic network management perspective. A research agenda is also proposed by identifying current state-of-the-art solutions and the need to shift all the convergent issues towards building an advanced resource management mechanism for beyond-5G