Throughput and Energy Efficiency for S-FFR in Massive MIMO Enabled Heterogeneous C-RAN

This paper considers the massive multiple-input multiple-output (MIMO) enabled heterogeneous cloud radio access network (C-RAN), in which both remote radio heads (RRHs) and massive MIMO macrocell base stations (BS) are deployed to potentially accomplish high throughput and energy efficiency (EE). In this network, the soft fractional frequency reuse (S-FFR) is employed to mitigate the inter-tier interference. We develop a tractable analytical approach to evaluate the throughput and EE of the entire network, which can well predict the impacts of the key system parameters such as number of macrocell BS antennas, RRH density, and S-FFR factor, etc. Our results demonstrate that massive MIMO is still a powerful tool for improving the throughput of the heterogeneous C-RAN while RRHs are capable of achieving higher EE. The impact of S-FFR on the network throughput is dependent on the density of RRHs. Furthermore, more radio resources allocated to the RRHs can greatly improve the EE of the network

Secrecy and Energy Efficiency in Massive MIMO Aided Heterogeneous C-RAN: A New Look at Interference

In this paper, we investigate the potential benefits of the massive multiple-input multiple-output (MIMO) enabled heterogeneous cloud radio access network (C-RAN) in terms of the secrecy and energy efficiency (EE). In this network, both remote radio heads (RRHs) and massive MIMO macrocell base stations (BSs) are deployed and soft fractional frequency reuse (S-FFR) is adopted to mitigate the inter-tier interference. We first examine the physical layer security by deriving the area ergodic secrecy rate and secrecy outage probability. Our results reveal that the use of massive MIMO and C-RAN can greatly improve the secrecy performance. For C-RAN, a large number of RRHs achieves high area ergodic secrecy rate and low secrecy outage probability, due to its powerful interference management. We find that for massive MIMO aided macrocells, having more antennas and serving more users improves secrecy performance. Then we derive the EE of the heterogeneous C-RAN, illustrating that increasing the number of RRHs significantly enhances the network EE. Furthermore, it is indicated that allocating more radio resources to the RRHs can linearly increase the EE of RRH tier and improve the network EE without affecting the EE of the macrocells.Comment: 26 pages, 11 figures, to appear in IEEE Journal of Selected Topics in Signal Processin

Performance Evaluation and Enhancement in 5G Networks : A Stochastic Geometry Approach

PhDThe deployment of heterogeneous networks (HetNets), in which low power nodes (LPNs) and high power nodes (HPNs) coexist, has become a promising solution for extending coverage and increasing capacity in wireless networks. Meanwhile, several advanced technologies such as massive multi-input multi-output (MIMO), cloud radio access networks (C-RAN) and device-to-device (D2D) communications have been proposed as competent candidates for supporting the next generation (5G) network. Since single technology cannot solely achieve the envisioned 5G requirements, the e ect of integrating multiple technologies in one system is worth to be investigated. In this thesis, a thoroughly theoretical analysis is conducted to evaluate the network performance in di erent scenarios, where two or more 5G techniques are employed. First, the downlink performance of massive MIMO enabled HetNets is fully evaluated. The exact and asymptotic expressions for the probability of a user being associated with a macro cell or a small cell are presented. The analytical expressions for the spectrum e ciency (SE) and energy e ciency (EE) in the K-tier network are also derived. The analysis reveals that the implementation of massive MIMO in the macro cell can considerably improve the network performance and decrease the demands for small cells in HetNets, which simpli es the network deployment. Then, the downlink performance of a massive MIMO enabled heterogeneous C-RAN is investigated. The exact expressions for the SE and EE of the remote radio heads (RRHs) tier and a tractable approximation approach for evaluating the SE and EE of the macrocell tier are obtained. Numerical results collaborate the analysis and prove that massive MIMO with dense deployment of RRHs can signi cantly enhance the performance of heterogeneous C-RAN theoretically. Next, the uplink performance of massive MIMO enabled HetNets is exploited with interference management via derived SE and EE expressions. The numerical results show that the uplink performance in the massive MIMO macrocells can be signi cantly improved through uplink power control in the small cells, while more uplink transmissions in the macrocells have mild adverse e ect on the uplink performance of the small cells. In addition, the SE and EE of the massive MIMO macrocells with heavier load can be improved by expanding the small cell range. Lastly, the uplink performance of the D2D underlaid massive MIMO network is investigated and a novel D2D power control scheme is proposed. The average uplink achievable SE and EE expressions for the cellular and D2D are derived and results demonstrate that the proposed power control can e ciently mitigate the interference from the D2D. Moreover, the D2D scale properties are obtained, which provide the su cient conditions for achieving the anticipated SE. The results demonstrate that there exists the optimal D2D density for maximizing the area SE of D2D tier. In addition, the achievable EE of a cellular user can be comparable to that of a D2D user. Stochastic geometry is applied to model all of the systems mentioned above. Monte Carlo simulations are also developed and conducted to validate the derived expressions and the theoretical analysis

Improvement of 5G performance through network densification in millimetre wave band

Recently, there has been a substantial growth in mobile data traffic due to the widespread of data hungry devices such as mobiles and laptops. The anticipated high traffic demands and low latency requirements stemmed from the Internet of Things (IoT) and Machine Type Communications (MTC) can only be met with radical changes to the network paradigm such as harnessing the millimetre wave (mmWave) band in Ultra-Dense Network (UDN). This thesis presents many challenges, problems and questions that arise in research and design stage of 5G network. The main challenges of 5G in mmWave can be characterised with the following attributes: i- huge traffic demands, with very high data rate requirements, ii- high interference in UDN, iii increased handover in UDN, higher dependency on Line of Sight (LOS) coverage and high shadow fading, and iv-massive MTC traffic due to billions of connected devices. In this work, software simulation tools have been used to evaluate the proposed solutions. Therefore, we have introduced 5G network based on network densification. Network densification includes densification over frequency through mmWave, and densification over space through higher number of antennas, Higher Order Sectorisation (HOS), and denser deployment of small-cells. Our results show that the densification theme has significantly improved network capacity and user Quality of Experience (QoE). UDN network can efficiently raise the user experience to the level that 5G vision promised. However, one of the drawback of using UDN and HOS is the significant increase in Inter-Cell Interference (ICI). Therefore, ICI has been addressed in this work to increase the gain of densification. ICI can degrade the performance of wireless network, particularly in UDN due to the increased interference from surrounding cells. We have used Fractional Frequency Reuse (FFR) as ICI Coordination (ICIC) for UDN network and HOS environment. The work shows that FFR has improved the network performance in terms of cell-edge data throughput and average cell throughput, and maintain the peak data throughput at a certain threshold. Additionally, HOS has shown even greater gain over default sectored sites when the interference is carefully coordinated. To generalise the principle of densification, we have introduced Distributed Base Station (DBS) as the envisioned network architecture for 5G in mmWave. Remotely distributed antennas in DBS architecture have been harnessed in order to compensate for the high path loss that characterise mmWave propagation. The proposed architecture has significantly improved the user data throughput, decreased the unnecessary handovers as a result of dense network, increased the LOS coverage probability, and reduced the impact of shadow fading. Additionally, this research discusses the regulatory requirements at mmWave band for the Maximum Permissible Exposure (MPE). Finally, scheduling massive MTC traffic in 5G has been considered. MTC is expected to contribute to the majority of IoT traffic. In this context, an algorithm has been developed to schedule this type of traffic. The results demonstrate the gain of using distributed antennas on MTC traffic in terms of spectral efficiency, data throughput, and fairness. The results show considerable improvement in the performance metrics. The combination of these contributions has provided remarkable increase in data throughput to achieve the 5G vision of “massive” capacity and to support human and machine traffic

Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

Energy efficiency and interference management in long term evolution-advanced networks.

Doctoral Degree. University of KwaZulu-Natal, Durban.Cellular networks are continuously undergoing fast extraordinary evolution to overcome technological challenges. The fourth generation (4G) or Long Term Evolution-Advanced (LTE-Advanced) networks offer improvements in performance through increase in network density, while allowing self-organisation and self-healing. The LTE-Advanced architecture is heterogeneous, consisting of different radio access technologies (RATs), such as macrocell, smallcells, cooperative relay nodes (RNs), having various capabilities, and coexisting in the same geographical coverage area. These network improvements come with different challenges that affect users’ quality of service (QoS) and network performance. These challenges include; interference management, high energy consumption and poor coverage of marginal users. Hence, developing mitigation schemes for these identified challenges is the focus of this thesis. The exponential growth of mobile broadband data usage and poor networks’ performance along the cell edges, result in a large increase of the energy consumption for both base stations (BSs) and users. This due to improper RN placement or deployment that creates severe inter-cell and intracell interferences in the networks. It is therefore, necessary to investigate appropriate RN placement techniques which offer efficient coverage extension while reducing energy consumption and mitigating interference in LTE-Advanced femtocell networks. This work proposes energy efficient and optimal RN placement (EEORNP) algorithm based on greedy algorithm to assure improved and effective coverage extension. The performance of the proposed algorithm is investigated in terms of coverage percentage and number of RN needed to cover marginalised users and found to outperform other RN placement schemes. Transceiver design has gained importance as one of the effective tools of interference management. Centralised transceiver design techniques have been used to improve network performance for LTE-Advanced networks in terms of mean square error (MSE), bit error rate (BER) and sum-rate. The centralised transceiver design techniques are not effective and computationally feasible for distributed cooperative heterogeneous networks, the systems considered in this thesis. This work proposes decentralised transceivers design based on the least-square (LS) and minimum MSE (MMSE) pilot-aided channel estimations for interference management in uplink LTE-Advanced femtocell networks. The decentralised transceiver algorithms are designed for the femtocells, the macrocell user equipments (MUEs), RNs and the cell edge macrocell UEs (CUEs) in the half-duplex cooperative relaying systems. The BER performances of the proposed algorithms with the effect of channel estimation are investigated. Finally, the EE optimisation is investigated in half-duplex multi-user multiple-input multiple-output (MU-MIMO) relay systems. The EE optimisation is divided into sub-optimal EE problems due to the distributed architecture of the MU-MIMO relay systems. The decentralised approach is employed to design the transceivers such as MUEs, CUEs, RN and femtocells for the different sub-optimal EE problems. The EE objective functions are formulated as convex optimisation problems subject to the QoS and transmit powers constraints in case of perfect channel state information (CSI). The non-convexity of the formulated EE optimisation problems is surmounted by introducing the EE parameter substractive function into each proposed algorithms. These EE parameters are updated using the Dinkelbach’s algorithm. The EE optimisation of the proposed algorithms is achieved after finding the optimal transceivers where the unknown interference terms in the transmit signals are designed with the zero-forcing (ZF) assumption and estimation errors are added to improve the EE performances. With the aid of simulation results, the performance of the proposed decentralised schemes are derived in terms of average EE evaluation and found to be better than existing algorithms

セルラ分散MU-MIMO通信システムの干渉制御

Tohoku University博士（工学）thesi