Kok Keong Chai

Distributed Energy Efficient Fair User Association in Massive MIMO Enabled HetNets

Massive multiple-input and multiple-output (MIMO) and heterogeneous networks (HetNets) have been recognized as key enabling technologies for future fifth generation (5G) mobile networks. However, the circuit power consumption of massive MIMO scales with the tremendous number of antennas. As a result, the problem of energy efficient user association in massive MIMO enabled HetNets is of vital importance. We investigate the energy efficient user association problem in massive MIMO enabled HetNets, and formulate the network logarithmic utility maximization problem. Based on the Lagrangian dual analysis, a low complexity distributed user association algorithm is developed for energy efficient fair user association while considering quality of service (QoS) provision for users. Simulation results demonstrate the effectiveness of the proposed algorithm in improving the energy efficiency and user fairness, compared to other user association algorithms.

Opportunistic User Association for Multi-Service HetNets Using Nash Bargaining Solution

We propose an opportunistic user association for multi-service HetNets aiming to guarantee quality of service (QoS) of human-to-human (H2H) traffic while providing fair resource allocation for machine-to-machine (M2M) traffic. We classify H2H traffic as primary service and M2M traffic as secondary service. The opportunistic user association is formulated as an optimization problem, which can be resolved by Nash Bargaining Solution (NBS). Simulation results show that the proposed algorithm can enable network operators to support fair resource allocation for M2M traffic without jeopardizing QoS of H2H traffic.

Two-Dimensional Optimization on User Association and Green Energy Allocation for HetNets With Hybrid Energy Sources

In green communications, it is imperative to reduce the total on-grid energy consumption as well as minimize the peak on-grid energy consumption, since the large peak on-grid energy consumption will translate into the high operational expenditure (OPEX) for mobile network operators. In this paper, we consider the two-dimensional optimization to lexicographically minimize the on-grid energy consumption in heterogeneous networks (HetNets). All the base stations (BSs) therein are envisioned to be powered by both power grid and renewable energy sources, and the harvested energy can be stored in rechargeable batteries. The lexicographic minimization of on-grid energy consumption involves the optimization in both the space and time dimensions, due to the temporal and spatial dynamics of mobile traffic and green energy generation. The reasonable assumption of time scale separation allows us to decompose the problem into two sub-optimization problems without loss of optimality of the original optimization problem. We first formulate the user association optimization in space dimension via convex optimization to minimize total energy consumption through distributing the traffic across different BSs appropriately in a certain time slot. We then optimize the green energy allocation across different time slots for an individual BS to lexicographically minimize the on-grid energy consumption. To solve the optimization problem, we propose a low complexity optimal offline algorithm with infinite battery capacity by assuming non-causal green energy and traffic information. The proposed optimal offline algorithm serves as performance upper bound for evaluating practical online algorithms. We further develop some heuristic online algorithms with finite battery capacity which require only causal green energy and traffic information. The performance of the proposed optimal offline and online algorithms is evaluated by simulations.

LTE-A an overview and future research areas

This paper gives an overview of the Long Term Evolution (LTE) of the Universal Mobile Telecommunication System (UMTS), which is being developed by the 3rd Generation Partnership Project (3GPP). LTE constitutes the latest step towards the 4th generation (4G) of radio technologies designed to increase the capacity and speed of mobile communications. Particular attention is given to the requirements and targets of LTE, its use of multiple antenna techniques, and to the Single Carrier Frequency Division Multiple Access (SC-FDMA) modulation scheme used in the LTE uplink. Furthermore new future research areas are proposed here.

Adaptive user association in HetNets with renewable energy powered base stations

In this paper, we propose adaptive user association in the Heterogeneous Networks (HetNets) with renewable energy powered base stations (BSs), where all the BSs are assumed solely powered by the harvested energy from the renewable energy sources. BSs across tiers differ in terms of energy harvesting rate, maximum transmit power and deployment density. In conventional grid-powered HetNets, user association is determined based on the assumption that all the BSs can transmit with constant powers, whereas the transmit powers of BSs vary in the HetNets with renewable energy powered BSs. The adaptive user association is formulated as an optimization problem which aims to maximize the number of accepted user equipments (UEs) and minimize the radio resource consumption in the scenario where the available energy of BSs is dependent on the harvested energy in a certain period of time. We first propose an optimal offline algorithm, where the gradient descent method is used to achieve the pseudo-optimal user association solution. The performance of proposed gradient descent based user association algorithm is verified by simulation results. Considering practical implementation, we further propose a heuristic online user association algorithm which is capable of making timely user association decision for the incoming UEs based on remaining available network resources. Simulation result indicates the proposed online algorithm achieves good tradeoff between UEs acceptance ratio and association delay.

Stackelberg Game Based Cooperative User Relay Assisted Load Balancing in Cellular Networks

We propose a Stackelberg game based cooperative user relay assisted load balancing (LB) scheme to tackle SNR degradation problem of shifted cell-edge users which commonly occurs in a conventional direct handover LB scheme. In the proposed scheme, users from a lightly loaded cell can be selected as cooperative user-relays and will be paid by the shifted cell-edge users. Stackelberg game theory is applied to optimize the strategies of both the user relays and shifted cell-edge users, in order to maximize both of their utilities in terms of SNR and payment. Theoretical analysis and simulation study are undertaken to show the effectiveness of the proposed scheme.

A Specification-Based IDS for Detecting Attacks on RPL-Based Network Topology

Routing Protocol for Low power and Lossy network (RPL) topology attacks can downgrade the network performance significantly by disrupting the optimal protocol structure. To detect such threats, we propose a RPL-specification, obtained by a semi-auto profiling technique that constructs a high-level abstract of operations through network simulation traces, to use as reference for verifying the node behaviors. This specification, including all the legitimate protocol states and transitions with corresponding statistics, will be implemented as a set of rules in the intrusion detection agents, in the form of the cluster heads propagated to monitor the whole network. In order to save resources, we set the cluster members to report related information about itself and other neighbors to the cluster head instead of making the head overhearing all the communication. As a result, information about a cluster member will be reported by different neighbors, which allow the cluster head to do cross-check. We propose to record the sequence in RPL Information Object (DIO) and Information Solicitation (DIS) messages to eliminate the synchronized issue created by the delay in transmitting the report, in which the cluster head only does cross-check on information that come from sources with the same sequence. Simulation results show that the proposed Intrusion Detection System (IDS) has a high accuracy rate in detecting RPL topology attacks, while only creating insignificant overhead (about 6.3%) that enable its scalability in large-scale network.

Duty cycle control with joint optimisation of delay and energy efficiency for capillary machine-to-machine networks in 5G communication system

A hybrid network architecture has been proposed for machine-to-machine M2M communications in the fifth generation wireless systems, where M2M gateways connect the capillary networks and cellular networks. In this paper, we develop novel energy efficient and end-to-end delay duty cycle control scheme for controllers at the gateway and the capillary networks coordinator. We first formulate a duty cycle control problem with joint-optimisation of energy consumption and end-to-end delay. Then, a distributed duty cycle control scheme is proposed. The proposed scheme consists of two parts i a transmission policy, which decides the optimal number of packets to be transmitted between M2M devices, coordinators and gateways; and ii a duty cycle control for IEEE 802.15.4. We analytically derived the optimal duty cycle control and developed algorithms to compute the optimal duty cycle. It is to increase the feasibility of implementing the control on computation-limited devices where a suboptimal low complexity rollout algorithm-based duty cycle control RADutyCon is proposed. The simulation results show that RADutyCon achieves an exponential reduction of the computation complexity as compared with that of the optimal duty cycle control. The simulation results show that RADutyCon performs close to the optimal control, and it performs no worse than the heuristic base control. Copyright

Multi-relay selection schemes based on evolutionary algorithm in cooperative relay networks

In cooperative relay networks, the selected relay nodes have great impact on the system performance. In this paper, a multi-relay selection schemes that consider both single objective and multi-objective are proposed based on evolutionary algorithms. First, the single-objective optimization problems of the best cooperative relay nodes selection for signal-to-noise ratio SNR maximization or power efficiency optimization are solved based on the quantum particle swarm optimization QPSO. Then the multi-objective optimization problems of the best cooperative relay nodes selection for SNR maximization and power consumption minimization two contradictive objectives or SNR maximization and power efficiency optimization also two contradictive objectives are solved based on a non-dominated sorting QPSO, which can obtain the Pareto front solutions of the problems considering two contradictive objectives simultaneously. The relay systems can select one solution from the Pareto front solutions according to the trade-off of SNR and power consumption or the trade-off of SNR and power efficiency to take part in the cooperative transmission. Simulation results show that the QPSO-based multi-relay selection schemes have the ability to search global optimal solution compared with other multi-relay selection schemes in literature. Simulation results also show that the non-dominated sorting QPSO-based multi-relay selection schemes obtain the same Pareto solutions as exhaustive search, but the proposed schemes have a very low complexity. Copyright

Joint user association and green energy allocation in HetNets with hybrid energy sources

In the heterogeneous networks (HetNets) powered by hybrid energy sources, it is imperative to reduce the total on-grid energy consumption as well as minimize the peak-to-average on-grid energy consumption ratio, since the large peak-to-average on-grid energy consumption ratio will translate into the high operational expenditure (OPEX) for mobile network operators. In this paper, we propose a joint user association and green energy allocation algorithm which aims to lexicographically minimize the on-grid energy consumption in HetNets, where all the base stations (BSs) are assumed to be powered by both the power grid and renewable energy sources. The optimization problem involves both the user association optimization in space dimension, and the green energy allocation in time dimension. The independence nature of this two-dimensional optimization allows us to decompose the problem into two sub-problems. We first formulate the user association optimization in space dimension as a convex optimization problem to minimize total energy consumption via balancing the traffic across different BSs in a certain time slot. We then optimize the green energy allocation across different time slots for an individual BS to lexicographically minimize the on-grid energy consumption. Simulation results indicate the proposed algorithm achieves significant on-grid energy saving, and substantially reduces peak-to-average on-grid energy consumption ratio.