Inter-tier Interference Suppression in Heterogeneous Cloud Radio Access Networks

Incorporating cloud computing into heterogeneous networks, the heterogeneous cloud radio access network (H-CRAN) has been proposed as a promising paradigm to enhance both spectral and energy efficiencies. Developing interference suppression strategies is critical for suppressing the inter-tier interference between remote radio heads (RRHs) and a macro base station (MBS) in H-CRANs. In this paper, inter-tier interference suppression techniques are considered in the contexts of collaborative processing and cooperative radio resource allocation (CRRA). In particular, interference collaboration (IC) and beamforming (BF) are proposed to suppress the inter-tier interference, and their corresponding performance is evaluated. Closed-form expressions for the overall outage probabilities, system capacities, and average bit error rates under these two schemes are derived. Furthermore, IC and BF based CRRA optimization models are presented to maximize the RRH-accessed users' sum rates via power allocation, which is solved with convex optimization. Simulation results demonstrate that the derived expressions for these performance metrics for IC and BF are accurate; and the relative performance between IC and BF schemes depends on system parameters, such as the number of antennas at the MBS, the number of RRHs, and the target signal-to-interference-plus-noise ratio threshold. Furthermore, it is seen that the sum rates of IC and BF schemes increase almost linearly with the transmit power threshold under the proposed CRRA optimization solution

Energy-Efficient Resource Allocation Optimization for Multimedia Heterogeneous Cloud Radio Access Networks

The heterogeneous cloud radio access network (H-CRAN) is a promising paradigm which incorporates the cloud computing into heterogeneous networks (HetNets), thereby taking full advantage of cloud radio access networks (C-RANs) and HetNets. Characterizing the cooperative beamforming with fronthaul capacity and queue stability constraints is critical for multimedia applications to improving energy efficiency (EE) in H-CRANs. An energy-efficient optimization objective function with individual fronthaul capacity and inter-tier interference constraints is presented in this paper for queue-aware multimedia H-CRANs. To solve this non-convex objective function, a stochastic optimization problem is reformulated by introducing the general Lyapunov optimization framework. Under the Lyapunov framework, this optimization problem is equivalent to an optimal network-wide cooperative beamformer design algorithm with instantaneous power, average power and inter-tier interference constraints, which can be regarded as the weighted sum EE maximization problem and solved by a generalized weighted minimum mean square error approach. The mathematical analysis and simulation results demonstrate that a tradeoff between EE and queuing delay can be achieved, and this tradeoff strictly depends on the fronthaul constraint

Cloud Based Small Cell Networks: System Model, Performance Analysis and Resource Allocation

In cloud-based small cell networks (C-SCNs), radio resource allocation at the base station (BS) is moved to a cloud data centre for centralised optimisation. In the centre, multiple processors referred to as the cloud computational unit (CCU), is used for the optimisation. As the cell size and networks become respectively smaller and denser, the number of BSs to be optimised grows exponentially, resulting in high computational complexity and latency at CCUs. This thesis propose belief propagation (BP) based power allocation schemes for C-SCNs that can be used for any network optimisation objectives such as energy efficiency at the centre and BSs; and spectral efficiency (SE). The computation for the schemes is done in parallel, leading to very low latency and computational complexity with increasing number of BSs. The transmission-latency depends on the number of bits used to quantise the received signal from terminals at the remote radio head (RRH). The computational-latency depend on the speed of resource allocation procedure at the CCU. BP based joint SE and latency optimisation scheme that compute the optimum terminal’s uplink power and number of quantisation bits for each RRHs. The results indicate a significant reduction in transmission and computational-latencies compared to other schemes. This thesis further investigates a user association (UA) to the BS and subcarrier allocation (SCA) where a BS allocates different number of SC to different users associated to it. In jointly optimising the UA and SCA, the Sharpe Ratio (SR) is used as the utility function, which is defined as the ratio between the mean of user achievable rates to its standard deviation. Thus, the achieved user rates will be closer to each other, leading to a fair network access. By using binary BP algorithm, the results show that the achievable user rates are doubled in comparison with other schemes