Stackelberg Game Theoretic Framework in Cognitive Green Heterogeneous Networks

Game theory has found an extensive application in wireless communication networks including cognitive radio networks, heterogeneous cellular networks, cooperative relay networks. Also, cognitive radio networks, green communications and heterogeneous cellular networks have attracted a wide attention on improve the spectrum efficiency and energy efficiency; therefore, the capacity, the coverage and the energy consumption. However, interference problem and energy consumption are critical for these networks. Introducing hierarchy among different decision-making players in cognitive, heterogeneous, green, cooperative cellular networks can both save energy and mitigate interference, thus enhance throughput. Stackelberg game suits to model, analyze and design the distributed algorithms in these hierarchical decision-making networking scenarios. In this chapter, we introduce basics of Stackelberg game and survey the extensive applications of Stackelberg game in cognitive, heterogeneous, cooperative cellular networks with the emphasis on resource management, green commutations design and interference management. This chapter highlights the potentials and applications with the promising vision of Stackelberg game theoretic framework for future cognitive green heterogeneous cellular networks.

Challenges in Energy-Efficient Communications as Enablers for Green Solutions on the 5G Heterogeneous Networks

One of the most representative challenges of multi-tier heterogeneous network architectures is the interference management among different Radio Access Technologies. In this sense, in order to achieve the potential increase on network capacity forecasted for 5G, the issue of interference must be addressed. Intelligent energy management, as proposed in the growing area of Green Communications could serve as an appealing solution to the interference issue. However developing an optimal energy management plan requires the understanding of the characteristics of 5G cellular networks that could be exploited to improve energy and resources efficiency. In this work we present a study about challenges in energy-efficient communications and technologies as enablers for green solutions and how this challenges can be extended to meet those of the 5G heterogeneous networks, in order to identify possible solutions to address the energy efficiency and interference mitigation issues.

Stable-Matching-Based Energy-Efficient Context-Aware Resource Allocation for Ultra-Dense Small Cells

Implementing caching to ultra-densely deployed small cells provides a promising solution for satisfying the stringent quality of service (QoS) requirements of delay-sensitive applications with limited backhaul capacity. With the rapidly increasing energy consumption, in this chapter, the authors investigate the NP-hard energy-efficient context-aware resource allocation problem and formulate it as a one-to-one matching problem. The preference lists in the matching are modeled based on the optimum energy efficiency (EE) under specified matching, which can be obtained by using an iterative power allocation algorithm based on nonlinear fractional programming and Lagrange dual decomposition. Next, on account of the Gale-Shapley algorithm, an energy-efficient matching algorithm is proposed. Some properties of the proposed algorithm are discussed and analyzed in detail. Moreover, the authors extend the algorithm to the matching with indifferent and incomplete preference lists. Finally, the significant performance gain of the proposed algorithm is demonstrated through simulation results.

Geometric Programming Based Resource Allocation for 5G High-Speed Mobile Networks

The high-speed railway (HSR) is a typical application case in 5G systems. Mobile relay stations (MRSs) which are mounted in a high-speed train (HST) is popular system architecture for high-speed mobile communications. However, sharing spectrums between the macro cell and the MRS cell, interference exists in this hybrid system. In this chapter, we investigate the downlink of a multi-cellular decode and forward (DF) relayed orthogonal frequency division multiple access (OFDMA) system and formulate the problem to maximize the system sum rate of all cells subject to a total power constraint and a new proposed time delay constraint. An effective resource allocation scheme combined by greedy sub-carriers allocation and geometric programming (GP) based power allocation algorithm is proposed to optimize subcarrier allocation and power allocation. Numerical experiments verify that the proposed resource allocation scheme outperforms the other traditional approaches and the necessity of introducing the time delay constraint.

Interference Mitigation for Satellite

For the coexistence and increasing interference of satellite-terrestrial network and terrestrial wireless network, we analyze a typical scenario where the GEO satellite-terrestrial network and the 4G mobile communication network coexist heterogeneously. Besides, a multi-user cognitive system model that secondary satellite terminals interfere the primary MIMO 4G base stations is also proposed, with whose general signal processing is deduced. Meanwhile, DBF technology in 4G base station system is adopted to minimize the cognitive interference caused by multi-antennas and multi-users. And we propose an OBW-FAI. Weight vector is only related to the azimuth of the interferences, thus the proposed algorithm does not need real-time and repeat calculations, and has small complexity. Finally, the numerical simulation results verify that the proposed system and algorithm can effectively reduce interference between satellite-terrestrial network and terrestrial wireless network to a certain extent.

Interference Management for Full-Duplex Massive MIMO Relaying System with Hardware Impairments

Massive MIMO full-duplex relaying (MM-FDR), where multiple source-destination pairs communicate simultaneously with the help of a common full-duplex relay equipped with very large antenna arrays, is studied in this chapter. Different from the traditional MM-FDR protocol, a general model where sources/destinations are allowed to equip with multiple antennas is considered. The effect of hardware impairments is taken into consideration, and is modeled using transmit/receive distortion noises. We propose a low complexity hardware impairments aware transceiver scheme (named as HIA scheme) to mitigate the distortion noises by exploiting the statistical knowledge of channels and antenna arrays at sources and destinations. A joint degree of freedom and power optimization algorithm is presented to further optimize the spectral efficiency of HIA based MM-FDR. The results show that the HIA scheme can mitigate the ``ceiling effect” appears in traditional MM-FDR protocol, if the numbers of antennas at sources and destinations can scale with that at the relay.

Pricing Methodology and Its Applications in Cognitive Radio and Multi-Tier Heterogeneous Cellular Networks

In this chapter, we concentrate on different technical applications and research directions of pricing theory and methodology, where we investigate following technical applications and functions of pricing including cooperative incentive mechanism design, Pareto- and social optimality improvement, distributed algorithm design with the low signaling overhead. We first clarify different concepts of pricing, summarize the motivation, present a taxonomy according to these different technical applications. Then, we survey applications of pricing theory and methodology with understandings and observations in cognitive radio and multi-tier heterogeneous cellular networks. We emphasize some of the recent critical problems, such as the cooperation incentive, resource and interference management and economics of small cells. Finally, we conclude this chapter with the possible research directions and more potential network applications of pricing theory and methodology.

The Combination of Resource Allocation and Interference Alignment for Ultra-Dense Heterogeneous Cellular Networks

Different with the traditional resource allocation problems, the consistency of resource occupation and the diversity of interference of participants in interference alignment (IA) clusters bring about the complexity in the combination of resource allocation and IA. Therefore, this chapter gives a transformed conflict graph-based solution framework which considers the low complexity of chordal graph, where the selection criteria of IA clusters are determined by the influence of IA on the resource occupation and the interference. The simulation results show that the proposed schemes can improve the network performance.

Toward Green Evolution of Cellular Networks by High Order Sectorisation and Small Cell Densification

Network densification by adding either more sectors per site or by deploying an overlay of small cells is always considered to be a key method for enhancing the RAN coverage and capacity. The impact of these two techniques on cellular network energy consumption is investigated in this chapter. The aim is to find an energy efficient deployment strategy when trading-off the order of sectorisation with the intensity of small cell densification. A new enhanced base station power consumption model is presented, followed by a novel metric framework for the evaluation of the RAN energy efficiency. The use of the power model and the proposed metrics is demonstrated by applying them to a RAN case study when the two techniques are used to improve the network capacity. In addition, the chapter evaluates the amount of network energy efficiency improvement when various adaptive sectorisation schemes are implemented. The results show that the strategy of adding more sectors is less energy efficient than directly deploying an overlay of small cells, even when adaptive sectorisation is implemented.

Self-Organization and Optimization in Heterogenous Networks

Driven by the continuous growth of wireless and mobile communication users, Long Term Evolution (LTE) and Long Term evolution-Advanced (LTE-A) have taken up densification of network as a new paradigm to meet the growing capacity demands. Small cells come with the advantage of enhanced coverage in indoor and hard reach areas and offer traffic offloading capacity in hotspots. However, there are challenges of interference management and self-adaptability with the overlaying macro cellular network since most small cell base stations are user deployed and do not have centralized control on their configuration and operation. The purpose of this chapter is to elaborate the concept of heterogeneous network and Self Organization Network (SON) in LTE-A. The various use cases of SON that can benefit the heterogeneous network have been discussed laying emphasis on interference management use case. Further the current trend of research in this field has been highlighted. It provides a holistic picture of the heterogeneous network and SON in LTE-A and upcoming mobile communication generations.