Optimal performance of resource allocation in LTE-A for heterogeneous cellular network

Long Term Evolution-Advanced (LTE-A) is the most widely used and encouraging technology for 4G and 5G mobile networks. The LTE technology in wireless networks has achieved a significantly high throughput because it makes use of multiple access schemes. We propose an iterative heuristic optimal resource allocation (HORA) algorithm and a chunk based resource block allocation (CRBA) scheduling algorithm to determine resource block (RB) allocation among users to satisfy the quality of service requirement. A heuristic approach which is used in HORA offers a tradeoff between computational complexity and performance. It performs RB and power allocation separately to reduce computational complexity. In the CRBA algorithm sets of RBs are allocated to groups of users keeping power constant to all users. User selection is performed based on channel conditions to improve throughput. RB allocation is an additive method to maximize the data transmission rate and energy efficiency. The use of channel quality indicator feedback from the user equipment (UE) to eNodeB plays an important role in the selection of appropriate modulation and coding schemes and benefits the assigned chunk of RBs to users in the wideband channel-dependent selective frequency-time domain. Here, RB usage and quality-of-service (QoS) constraint are considered for the scheduling algorithm. The HORA algorithm assigns most RBs to users who have high-value signal to noise ratio and continues the RB allocation until it meets the QoS criteria of all users in consideration of the threshold value of the power budget. Problems that arise during continuous resource allocation to the scheduled user are considered as APX-hard and NP-hard problems. An RB and power allocation optimization problem is formulated for the maximum data rate in the cellular network. The simulation results show that the proposed approaches demonstrate considerable throughput improvement at the user end in a significant and robust condition.