Outage-Constrained Beamforming for Two-Tier Massive MIMO Downlink with Pilot Reuse

Massive multiple-input multiple-output (MIMO) systems and small cell networks are both regarded as promising candidates to meet the exponential growth of mobile data traffic for the next generation (5G) wireless communications. Hence, a new kind of multitier networks which combine massive MIMO macro cells with a secondary tier of small cells is proposed to resolve the contradiction of large network coverage and high data rate. In such multitier networks, it is inevitable to allocate nonorthogonal uplink pilot sequences to user equipment (UE) due to the large number of users. We propose a pilot reuse scheme by exploiting the unique architecture of this networks and analyse the special mixed channel state information (CSI) yielded by the pilot reuse scheme. Based on the mixed CSI, we formulate a downlink transmit beamforming problem of minimizing the total power consumption while satisfying the quality of service (QoS) requirements with outage constraints. After decomposing the original problem into simpler subproblems, we provide an efficient algorithm to combine these subproblems and solve them iteratively for generating the beamforming vectors. Monte Carlo simulations show that the average power consumption of the proposed pilot reuse scheme and its associated beamforming algorithm is close to that of the perfect CSI case

Multi-Cell Interference Exploitation: Enhancing the Power Efficiency in Cell Coordination

In this paper, we propose a series of novel coordination schemes for multi-cell downlink communication. Starting from full base station (BS) coordination, we first propose a fully-coordinated scheme to exploit beneficial effects of both inter-cell and intra-cell interference, based on sharing both channel state information (CSI) and data among the BSs. To reduce the coordination overhead, we then propose a partiallycoordinated scheme where only intra-cell interference is designed to be constructive while inter-cell is jointly suppressed by the coordinated BSs. Accordingly, the coordination only involves CSI exchange and the need for sharing data is eliminated. To further reduce the coordination overhead, a third scheme is proposed, which only requires the knowledge of statistical inter-cell channels, at the cost of a slight increase on the transmission power. For all the proposed schemes, imperfect CSI is considered. We minimize the total transmission power in terms of probabilistic and deterministic optimizations. Explicitly, the former statistically satisfies the users’ signal-to-interferenceplus-noise ratio (SINR) while the latter guarantees the SINR requirements in the worst case CSI uncertainties. Simulation verifies that our schemes consume much lower power compared to the existing benchmarks, i.e., coordinated multi-point (CoMP) and coordinated-beamforming (CBF) systems, opening a new dimension on multi-cell coordination

Resource Allocation Techniques for Non-Orthogonal Multiple Access Scheme for 5G and Beyond Wireless Networks

The exponential growth of wireless networks and the number of connected devices as well as the emergence of new multimedia-based services have resulted in growing demands for high data-rate communications, and a spectrum crisis. Hence, new approaches are required for better utilization of spectrum and to address the high data- rate requirements in future wireless communication systems. Non-orthogonal multiple access (NOMA) has been envisioned as a promising multiple access technique for 5G and beyond wireless networks due to its potential to achieve high spectral efficiency (SE) and energy efficiency (EE) as well as to provide massive connectivity in supporting the proliferation of Internet of Things. In NOMA, multiple users can share the same wireless resources by applying superposition coding (SC) and power domain multi- plexing at the transmitter and employing successive interference cancellation (SIC) technique at the receiver for multi-user detection. NOMA outperforms conventional orthogonal multiple access (OMA) by simultaneously sharing the available communication resources between all users via the power domain multiplexing which offers a significant performance gain in terms of SE. In this thesis, several resource allocation problems have been addressed in NOMA based communication systems, in order to improve network performance in terms of power consumption, fairness and EE. In particular, the NOMA scheme has been studied in multiple-input-single-output transmissions where transmit beamformers are designed to satisfy quality of service using convex optimization techniques. To incorporate the channel uncertainties in beamforming design, robust schemes are proposed based on the worst-case design and the outage probabilistic-based design. Finally, the EE is investigated for non-clustering and clustering NOMA schemes with imperfect channel state information. To eliminate the interference between different clusters, zero-forcing beamformers are employed at the base station. Theoretical analysis and algorithmic solutions are derived and the performance of all these schemes has been verified using simulation results

Optimizing Resource Allocation with Energy Efficiency and Backhaul Challenges

To meet the requirements of future wireless mobile communication which aims to increase the data rates, coverage and reliability while reducing energy consumption and latency, and also deal with the explosive mobile traffic growth which imposes high demands on backhaul for massive content delivery, developing green communication and reducing the backhaul requirements have become two significant trends. One of the promising techniques to provide green communication is wireless power transfer (WPT) which facilitates energy-efficient architectures, e.g. simultaneous wireless information and power transfer (SWIPT). Edge caching, on the other side, brings content closer to the users by storing popular content in caches installed at the network edge to reduce peak-time traffic, backhaul cost and latency. In this thesis, we focus on the resource allocation technology for emerging network architectures, i.e. the SWIPT-enabled multiple-antenna systems and cache-enabled cellular systems, to tackle the challenges of limited resources such as insufficient energy supply and backhaul capacity. We start with the joint design of beamforming and power transfer ratios for SWIPT in MISO broadcast channels and MIMO relay systems, respectively, aiming for maximizing the energy efficiency subject to both the Quality of Service (QoS) constraints and energy harvesting constraints. Then move to the content placement optimization for cache-enabled heterogeneous small cell networks so as to minimize the backhaul requirements. In particular, we enable multicast content delivery and cooperative content sharing utilizing maximum distance separable (MDS) codes to provide further caching gains. Both analysis and simulation results are provided throughout the thesis to demonstrate the benefits of the proposed algorithms over the state-of-the-art methods

A Comprehensive Survey on Resource Allocation for CRAN in 5G and Beyond Networks

The diverse service requirements coming with the advent of sophisticated applications as well as a large number of connected devices demand for revolutionary changes in the traditional distributed radio access network (RAN). To this end, Cloud-RAN (CRAN) is considered as an important paradigm to enhance the performance of the upcoming fifth generation (5G) and beyond wireless networks in terms of capacity, latency, and connectivity to a large number of devices. Out of several potential enablers, efficient resource allocation can mitigate various challenges related to user assignment, power allocation, and spectrum management in a CRAN, and is the focus of this paper. Herein, we provide a comprehensive review of resource allocation schemes in a CRAN along with a detailed optimization taxonomy on various aspects of resource allocation. More importantly, we identity and discuss the key elements for efficient resource allocation and management in CRAN, namely: user assignment, remote radio heads (RRH) selection, throughput maximization, spectrum management, network utility, and power allocation. Furthermore, we present emerging use-cases including heterogeneous CRAN, millimeter-wave CRAN, virtualized CRAN, Non- Orthogonal Multiple Access (NoMA)-based CRAN and fullduplex enabled CRAN to illustrate how their performance can be enhanced by adopting CRAN technology. We then classify and discuss objectives and constraints involved in CRAN-based 5G and beyond networks. Moreover, a detailed taxonomy of optimization methods and solution approaches with different objectives is presented and discussed. Finally, we conclude the paper with several open research issues and future directions

Multibeam Joint Processing in Satellite Communications

Cooperative Satellite Communications (SatComs) involve multi-antenna satellites enabled for the joint transmission and reception of signals. This joint processing of baseband signals is realized amongst the distinct but interconnected antennas. Advanced signal processing techniques –namely precoding and Multiuser Detection (MUD)– are herein examined in the multibeam satellite context. The aim of this thesis is to establish the prominence of such methods in the next generation of broadband satellite networks. To this end, two approaches are followed. On one hand, the performance of the well established and theoretically concrete MUD is analysed over the satellite environments. On the other, optimal signal processing designs are developed and evaluated for the forward link. In more detail, the present dissertation begins by introducing the topic of multibeam joint processing. Thus, the most significant practical constraints that hinder the application of advanced interference mitigation techniques in satellite networks are identified and discussed. Prior to presenting the contributions of this work, the multi-antenna joint processing problem is formulated using the generic Multiuser (MU) Multiple InputMultiple Output (MIMO) baseband signal model. This model is also extended to apply in the SatComs context. A detailed presentation of the related work, starting from a generic signal processing perspective and then focusing on the SatComs field, is then given. With this review, the main open research topics are identified. Following the comprehensive literature review, the first contribution of this work, is presented. This involves the performance evaluation of MUD in the Return Link (RL) of multiuser multibeam SatComs systems. Novel, analytical expressions are derived to describe the information theoretic channel capacity as well as the performance of practical receivers over realistic satellite channels. Based on the derived formulas, significant insights for the design of the RL of next generation cooperative satellite systems are provided. In the remaining of this thesis, the focus is set on the Forward Link (FL) of multibeam SatComs, where precoding, combined with aggressive frequency reuse configurations, are proposed to enhance the offered throughput. In this context, the alleviation of practical constraints imposed by the satellite channel is the main research challenge. Focusing on the rigid framing structure of the legacy SatCom standards, the fundamental frame-based precoding problem is examined. Based on the necessity to serve multiple users by a single transmission, the connection of the frame-based precoding and the fundamental signal processing problem of physical layer multigroup multicasting is established. In this framework and to account for the power limitations imposed by a dedicated High Power Amplifier (HPA) per transmit element, a novel solution for multigroup multicasting under Per Anntenna Constraints (PACs) is derived. Therefore, the gains offered by multigroup multicasting in frame-based systems are quantified over an accurate simulation setting. Finally, advanced multicast and interference aware scheduling algorithms are proposed to glean significant gains in the rich multiuser satellite environment. The thesis concludes with the main research findings and the identification of new research challenges, which will pave the way for the deployment of cooperative multibeam satellite systems

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