Ho Ting Cheng

Step-Wise Optimal Low Power Node Deployment in LTE Heterogeneous Networks

In this paper, we propose a step-wise optimal low power node (LPN) deployment algorithm for LTE heterogeneous networks. Our proposed LPN deployment algorithm takes signal quality, relative loading among macro cells and LPN cells, and user density into account. Simulation results show that the proposed algorithm can achieve close to 100% coverage gain and more than 50% average cell throughput gain over a random LPN deployment scheme.

Spectral Efficiency and Fairness Tradeoffs in Cellular Networks with Realtime+Nonrealtime Traffic Mix Using Stochastic Petri Nets

Resource scheduling in OFDMA cellular wireless networks is a powerful technique on the MAC layer. Utilizing adaptive modulation and coding allows the effective use of all signal-to-interference ratio (SINR) ranges. Typical single antenna spectral efficiency values for LTE-Advanced range between 4.8 near the base station and 0.2 b/s/Hz at the cell edge. With best-effort traffic and full buffer assumption the tradeoff between emphasizing the cell center or cell edge can be explored extensively. However, with real-time traffic present, this takes priority without fairness adjustment alternatives. In this paper the mixed traffic scenario is studied with an abstract stochastic Petri net model. The exploration of the degrees of freedom by studying the real-time traffic proportion and a fairness adjustment parameter provides new insight to the potential feasible region. The results show that the tradeoff between emphasizing the cell edge performance and maintaining a high average spectral efficiency is most powerful in the best-effort case, while an increasing level of real-time traffic reduces the room for a tradeoff. The stochastic Petri net analysis approach allows numeric analysis without simulation by utilizing Markov chain equivalence and steady state calculations. This model is deliberately abstract but flexible enough to study the tradeoff.

Downlink Transmission Optimization Framework

This paper presents an optimization framework for downlink transmission parameters of mobile cellular systems. A typical network optimization approach is to divide the network into disjoint clusters of base-stations (BS). Optimization is then performed within each cluster for important parameters such as transmit power, precoder, etc. This approach is widely adopted in academic research and industrial standard bodies, e.g. 3GPP LTE-Advanced. While reducing the optimization complexity, this strategy suffers from a performance limit due to interference from the nodes outside cluster. We thus propose a framework to overcome this limit by allowing clusters to exchange their parameters and optimization information via low-rate and non-zero delay backhauls. System-level simulations for LTE downlink transmit power optimization show that the proposed optimization model, while having the low-complexity of cluster-based approach, could nearly achieve the performance of network-wise optimization. Therefore, this model is particularly suitable for optimization of 4G and beyond-4G cellular networks.