It has been a significant issue to satisfy the rapidly growing data traffic with the limited wireless radio resources. Licensed-assisted access to unlicensed spectrum (e.g., LAA) brings hope for the service provider (SP) to mitigate the deficiency of radio resources. This work contributes on designing a pricing model in a licensed and unlicensed coexisting network, modelled as a two-sided market with content providers (CPs) and end users (EUs) at the SP's two sides. A premium content delivery deal is further designed via the optimal auction in order to efficiently allocate the scarce radio resources for the CPs with higher traffic load and QoS requirement. Thus, the SP and CPs form a prioritized spectrum game, and the SP and EUs form a radio access subscription game. By backward induction, we derive the basic delivery price and the premium delivery price to CPs, the reservation price, and the LTE-only and LAA subscription prices to EUs. Analysis shows that all players benefit from the premium delivery deal and co-existence of unlicensed LTE. When the unlicensed spectrum becomes reliable, all players' payoffs and the subscription ratio increase. In addition, the impact of the subsidies and technology heterogeneity are also addressed in this article.

Device-to-Device (D2D) communication is a promising concept used to improve user experience and enhance resource utilization in cellular networks, enabling two close-by D2D devices to establish a direct local link and bypass a base station. The proximity of two D2D devices allows for high data rate, low latency, and low energy consumption. D2D communication for proximity-based services (ProSe) is one of the most popular issues discussed in the 3rd Generation Partnership Project (3GPP). D2D devices require to discover each other (i.e. D2D discovery) before D2D communication. It can be applied to various important fields such as the environment and habitat monitoring, disaster management, and emergency response. In this work, we consider D2D communication is adopted for Internet-of-Things (IoT) devices for local operation. These devices may be randomly deployed and expose to uncontrolled, harsh and hostile environments. Thus, energy-harvesting technology is considered to enable devices to gather energy from the ambient sources and recharge their batteries. We investigate the constraints of an LTE-A system to serve energy-harvesting D2D devices. We develop a low complexity algorithm for D2D discovery resource allocation. Moreover, Sleep-Coordinative Mechanism (SCM) and Saving-before-Activity Mechanism (SBA) are proposed to realize energy-harvesting D2D discovery under the resource and energy constraints. Simulation results show that the combination of SCM and SBA effectively achieves almost 100% discovery rate with fewer time slots and lower energy consumption.

When it comes to machine-to-machine (M2M) communications in advanced cellular networks, the resource allocation scheme should be re-examined to satisfy both low-cost M2M and mission-critical M2M. Because most M2M applications are uplink-dominated, we propose a mixed waiting-time auction and price-based dedicated uplink resource allocation framework for the low-cost and mission-critical M2M. The prioritized framework guarantees resources for traditional human-to-human (H2H) communications while meeting the needs of low-cost and mission-critical M2M devices on the basis of either time bids or direct price. In addition, the scheme ensures the existence and uniqueness of the Bayesian Nash equilibrium and the interregional and waiting-time-based truth-telling properties. This indirect mechanism holds with Bayesian-Nash incentive compatibility, interim efficiency, interim individual rationality, and weak budget balance. The results show that low-cost M2M devices with lower energy awareness are more willing to participate in the waiting-time auction, while mission-critical M2M with higher energy awareness turn to directly pay for guaranteed access. The delay in connected mode and the optimal price vary according to the M2M/H2H traffic loads and resource pool partitions. This paper contributes insights that with proper mechanism design, low-cost M2M and mission-critical M2M can be served together, while the operator is financially compensated.

Since Machine-to-Machine (M2M) communications is going to be realized in advanced cellular networks, the resource allocation scheme should be re-examined to satisfy both traditional Human-to-Human (H2H) communications (e.g., voice calls) and M2M communications. Because most M2M applications are delay-tolerant and uplink-dominated, we propose a waiting-line based uplink resource allocation framework in the M2M/H2H co-existence scenario. The proposed scheme guarantees resources for H2H communications while meeting the needs of M2M communications on a first-come first-served basis. In addition, the scheme ensures the existence and uniqueness of the Bayesian Nash equilibrium and the truth-telling property. Results show that M2M devices with lower energy opportunity cost are more willing to participate in the waiting-line based scheme, and the delay in the connected mode varies according to the H2H traffic load and the total number of competitors. However, M2M devices with higher energy opportunity cost may not join this time bid resource allocation scheme. This work contributes insights into the types of resource allocation schemes, bidding with time or bidding with money, for M2M devices with different levels of energy awareness.

To explore the energy efficient Machine-Type Communication (MTC) for 5G cellular systems, we developed a simulation platform to investigate the complete uplink procedures of energy-harvesting MTC devices in LTE-A (Long Term Evolution Advanced) system. Though the 3rd Generation Partnership (3GPP) has worked on LTE-A cellular standards in support of MTC transmission, the standards have not taken energy-harvesting MTC devices into their scope. Energy-harvesting technology can be the candidate to support the MTC features by allowing the devices to harvest ambient energy and support their own power usage without manual upgrade. The proposed Energy-Aware LTE-A scheme, serving as power control and admission control, prevents the devices from building the network connections greedily but ending up with energy shortage and packet loss. This scheme not only can reduce the contention level of control channels but also can decrease energy wastage on network entry procedures, thereby improving the overall energy efficiency.

Machine-to-Machine (M2M) communications characterize a huge number of devices and small data transmission, which render admission control and resource allocation two key components to guarantee similar quality of service (QoS) for homogeneous devices. In view of this, we propose a pricing model based on option pricing and auction, aiming to guarantee the required QoS (i.e., throughput in this study) in the successive reserved time slots. We also introduce the concept of TotalPayment, referring to the price paid by the device when entering a M2M network, based on which we further suggest the optimal value of TotalPayment and its corresponding optimal range of strike price. The combination of QoS guarantee, admission control and market modelling in M2M network is an innovative business concept.