In this paper, the performance of fifth generation (5G) cellular networks under two promising technologies, namely dual connectivity and coordinated multi-point transmission (CoMP) is investigated. In this regard, a joint access and fronthaul radio resource allocation for a two tier downlink heterogeneous cloud radio access network (H-CRAN) is formulated. The main aim of the proposed problem formulation is to maximize the system energy efficiency (EE) by using both millimeter wave (mmW) and micro wave (μW) links in access and fronthaul. The proposed optimization is a mixed integer nonconvex problem with a high computational complexity solution. Therefore, existing convex optimization methods can not be used directly to solve this problem. To solve this issue, an iterative algorithm based on a successive convex approximation (SCA) approach with low complexity is exploited. As the numerical results show, via dual connectivity and CoMP EE is improved by approximately 90% compared to using only μW subcarriers.

In this paper, fifth-generation (5G) cellular networks under three promising technologies, namely, dual connectivity, coordinated multi-point transmission (CoMP), and power domain non orthogonal multiple access (PD-NOMA) are investigated. The main aim is to maximize the downlink energy efficiency (EE) by using both millimeter wave (mmW) and micro wave (μW) links in access and fronthaul, while employing CoMP and PD-NOMA. In this regard, joint access and fronthaul radio resource allocation for a downlink heterogeneous cloud radio access network is considered. The proposed optimization is a mixed integer non-convex problem with a high computational complexity solution, and hence, the alternate search method based on a successive convex approximation approach using fractional programming is exploited. Furthermore, the convergence of the proposed iterative resource allocation method is proved and its computational complexity is investigated. As the numerical results show, via dual connectivity through receiving signals from both mmW and μW transmitters, the system EE is improved by approximately 50%, in contrast to using only μW subcarriers (e.g., as in local thermal equilibrium). In addition, by applying both PD-NOMA and CoMP technologies on the μW subcarriers, the EE of the system increases by approximately 45%.

This study investigates energy efficient allocation of radio resource blocks in orthogonal frequency division multiple access (OFDMA) systems while considering the status of the users’ data buffers to reduce packet dropping rate by the downlink scheduler. The proposed scheme exploits the fluctuations of traffic load to efficiently schedule users’ data packets by reducing the overall energy consumption of the system whenever the status of data buffers permits. From information theory point of view, the proposed scheme exploits the fundamental trade‐off between energy efficiency and spectral efficiency to perform scheduling. First, the problem is formulated as an optimisation problem and then a novel solution, based on dynamic programming, is applied. By comparing the analytical solution with the ones obtained by exhaustive search, it is demonstrated that the proposed scheme is close to the optimal solution, with low computational complexity. In addition, comprehensive simulations are conducted to evaluate the performance of the suggested algorithm. Both analytical and simulation results demonstrate the superiority of the proposed algorithm compared with the well‐known benchmark schemes in terms of energy efficiency and packet dropping rate.