Kausik Ray Chaudhuri

UE-Based Adaptive Uplink Power Control to Enhance Cell Capacity of LTE Systems

We consider the uplink open-loop power control (OLPC) procedure in Long Term Evolution (LTE) cellular networks. We propose a UE based adaptive OLPC approach where a UE selectively, and autonomously, applies predetermined offsets to the standardized open-loop power control parameters such as PO_UE_PUSCH and α as a function of its relative location. The proposed approach increases overall uplink signal to interference and noise ratio (UL SINR) at eNodeBs. As a result, UL cell throughput improves with no additional over the air signaling or extra processing load at eNodeBs. Our simulation results show that the UE-based adaptive OLPC approach significantly increases the center-cell UEs throughput at the expense of a slight, and controllable, throughput degradation of the UEs at the cell-edge.

Layer management through idle-mode parameter optimization in multi-carrier LTE networks

In this paper, we investigate the load balancing problem in multi-carrier LTE networks. We propose a probabilistic framework for idle-mode parameter optimization in Self-Optimizing Networks (SON) in order to achieve the target traffic distribution per carrier. In particular, we consider different layer management strategies such as hierarchical, equal priorities. For each strategy, we mathematically optimize the underlying idle-mode parameters defined by 3GPP specification, based on the statistical information of radio frequency (RF) propagation in order to achieve the target traffic distribution. Moreover, we characterize the underlying tradeoffs between the traffic controllability and user experience for each strategy. Finally, we show the performance of our proposed framework in real network deployments.

Distributed and Adaptive Optimization of LTE-TDD Configuration Based on UE Traffic Type

Interference mitigation is one of the main challenges in LTE TDD networks, which requires that all cells in the network follow the same TDD UL/DL configuration. However, different UEs in the network may have different UL or DL traffic types, which may also vary with time; as a result, different cells may require different TDD UL/DL configurations in time. In this paper, we consider an LTE network, where each eNodeB in the network has backhaul links, i.e. X2 interfaces, only with its immediate neighboring eNodeBs. We investigate an adaptive optimization of TDD UL/DL configuration index in mean square error (MSE) sense based on the available UL and DL traffic of all RRC connected UEs in different cells within the network. We then propose a distributed algorithm, where all eNodeBs in the network will reach consensus on the optimum TDD UL/DL configuration through local communications with their neighboring eNodeBs over X2 interfaces. Our simulation results show that the LTE network, which is running the proposed algorithm, provides the better utilization of the available frequency-time resources and achieves a higher UE Throughput compared to a fixed TDD UL/DL configuration.