Proportional Fair Resource Partition for LTE-Advanced Networks with Type I Relay Nodes

Liang

2014 International Wireless Communications and Mobile Computing Conference (IWCMC)

2014

For M2M (Machine-to-Machine) machines in cellular networks, employing high transmission rates or transmitting in large power actually cost them much energy. This is harmful to the machines, especially they are operated by batteries. The Relay Node (RN) in Long-Term Evolution-Advanced (LTE-A) networks is used to enhance the coverage of high data rate and solve the coverage hole problem. Considering the limited energy nature of machines, connecting to the RN instead of the BS is a better choice for cell-edge machines. In this paper, we consider an uplink resource and power allocation problem for energy conservation in LTE-A relay networks. The objective is to minimize the total energy consumption of machines while guarantee their quality of service (QoS). We prove this uplink resource and power allocation problem to be NP-complete and develop an energy-conserved resource and power allocation method to solve the problem. Simulation results show that our algorithm can effectively reduce the energy consumption of machines and guarantee their required service qualities.

Section: Introductionmentioning

confidence: 99%

Energy-efficient uplink radio resource management in LTE-advanced relay networks for Internet of Things

Liang

2014 International Wireless Communications and Mobile Computing Conference (IWCMC)

2014

2012 IFIP Wireless Days

“…To the best of our knowledge, at the time of this writing, only few contributions are available in literature on this subject [3]- [5]. They propose very basic schemes that are unable to offer any sharp QoS bounds to real-time applications.…”

Section: Introductionmentioning

confidence: 99%

QoS provisioning in LTE-A networks with relay nodes

Piro

Grieco

Boggia

et al. 2012

Abstract-In the vision of heterogeneous networks, the Quality of Service provided by classic cellular systems is improved thanks to a jointly adoption of macro and small-range cells (i.e., micro, pico, and femtocells) working in the same area. This rationale has been also assimilated by 3GPP, which now proposes its possible exploitation in the upcoming Long Term Evolution-Advanced architecture. In this context, the wireless relay technology represents an interesting solution for extending the coverage of a macrocell by means of a relay node which offers wireless connectivity to mobile users and, at the same time, is connected to the eNode-B (and hence to the backbone) through a wireless backhaul link. But, the standard does not specify any optimal resource allocation strategy for the two hop path formed by the user and the backhaul links, which is indeed very relevant to satisfy the level of QoS expected by end users. To this aim, in the present contribution, we present a novel scheduling strategy, conceived as an extension of the recently proposed TwoLevel Scheduler approach, able to effectively support real-time applications in the presence of relay nodes. Its performance has been tested in several network scenarios that involve a variable number of users hosting real-time multimedia applications and best effort flows. A comparison with respect to Proportional Fair and Logarithmic strategies has been also provided, showing that the proposed approach is able to greatly reduce the Packet Loss Ratio experienced by multimedia applications, at the expense of a slight impairment of the throughput of the best effort flows.

IEEE Trans. Wireless Commun.

“…Equations (15) and (18) are the average and instantaneous power constraints for the eNB and RNs. The constraint (16) ensures that the admitted data cannot be more than the data in the outgoing queue. The constraint (19) ensures that each RB can only be assigned to one UE.…”

Section: G Dynamic Joint Resource Optimization Problemmentioning

confidence: 99%

Dynamic Joint Resource Optimization for LTE-Advanced Relay Networks

Liang

et al. 2013

Abstract-A dynamic optimization algorithm is proposed for the joint allocation of subframes, resource blocks, and power in the Type 1 inband relaying scheme mandatory in the LTEAdvanced standard. Following the general framework of Lyapunov optimization, we decompose the original problem into three sub-problems in the forms of convex programming, linear programming, and mixed-integer programming. We solve the last sub-problem in the Lagrange dual domain, showing that it has zero duality gap, and that a primal optimum can be obtained with probability one. The proposed algorithm dynamically adapts to traffic and channel fluctuations, it accommodates both instantaneous and average power constraints, and it obtains arbitrarily near-optimal sum utility of each user's average throughput. Simulation results demonstrate that the joint optimum can significantly outperform suboptimal alternatives.