Adaptive time division duplexing configuration mode selection mechanism for accommodating asymmetric traffic in time division long term evolution‐advanced systems

Abstract

Recently, mobile networks have been suffering from asymmetric traffic congestion as various multimedia services have been newly introduced. To solve the congestion, mobile networks should be able to adaptively adjust resource volume for uplink and downlink transmissions. However, for a 3rd Generation Partnership Project time‐division long term evolution advanced system, research has not been carried out on the details of the dynamic resource adjustment. In this paper, we propose a mechanism in which evolved NodeB can adaptively adjust resource volume for uplink and downlink transmissions by switching the time division duplexing configuration mode. Simulation results show that the proposed mechanism can effectively accommodate uplink and downlink traffic, and can maintain queueing delays of mobile traffic at low levels in both uplink and downlink channels. Copyright © 2013 John Wiley & Sons, Ltd.

Joint allocation of uplink and downlink resources for interactive mobile cloud applications

“…d max is the maximum allowable PG drop rate. By introducing the Lagrange multiplierˇ> 0, the aforementioned constrained optimization problem can be converted to a unconstrained one as that in (15).…”

“…If there exists a unichain policy ˇD ı ˇ. X/, 8X 2 X N , which satisfy (17) with the Lagrange reward function given by (25), then g is equal to the optimal average expected reward per slot, which satisfies (15). In the following, the solution of the problem is exlored, based on which a two-step allocation scheme is proposed to offer a sub-optimal but low-complexity solution to the joint resource allocation problem in multi-user scenario.…”

Joint dynamic switching point configuration and resource allocation in TDD‐OFDMA networks: optimal formulation and suboptimal solution

“…The two new continuous variables are z BS BS i,j,x,l,s and y BS BS i,j,x,l,s where the former corresponds to terms with a positive constant and the latter to terms with a negative constant value. Constraints (11)- (12) and (13)-(16) correspond to z BS BS i,j,x,l,s and y BS BS i,j,x,l,s , respectively. They are added to ensure that the solution of the reformulated problem is equivalent to the original one.…”

“…Finally, in , an analytical method is provided to determine the best allocation of resources to the uplink and downlink in order to minimize the blocking rate. Recently, an approach was proposed in to address the problem of adapting TDD frame configurations to the changing uplink and downlink traffic. The scheme used first estimates the required number of resource blocks based on the buffer and arrival data volumes then selects the frame configuration based on the ratio of resource blocks in the uplink and downlink before performing some calibration.…”

“…Two recent publications stand out in this domain. In , TDD frames are configured based on the current arriving and buffered traffic volumes. In , different aspects of the dynamic uplink‐downlink configuration in TD long‐term evolution (LTE) systems are discussed with some preliminary general results.…”