Analytical Evaluation of Chunk-Based Tractable Multi-cell OFDMA system

This paper evaluates thoroughly the performance of multi-cell OFDMA system. The two types of deployment in multi-cell OFDMA system, such as Strict Fractional Frequency Reuse (FFR) and Soft FFR (SFR) were evaluated. In order to model the base station locations, homogeneous Poisson point processes were used, i.e. tractable model instead of hexagonal grid was considered. In order to reduce complexity, chunk-based resource allocation scheme was embedded. Each cell divides the users into the users of the central cell area and the users of the cell edge area according to their average received Signal to Interference and Noise Ratio (SINR) compared with FFR threshold. The primary stage of the analysis includes the spectral efficiency’s expression deriving from these two deployment scenarios, followed by the analysis with the use of coverage probability. However, the improvement of spectral efficiency is achieved in the case of SFR. On the contrary, coverage probability is far improved by using strict FFR scheme. Through numerical anaysis, We have shown that the optimal FFR threshold to achieve the highest spectral efficiency was 12 dB for both Strict FFR as well as SFR

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

D13.1 Fundamental issues on energy- and bandwidth-efficient communications and networking

Deliverable D13.1 del projecte europeu NEWCOM#The report presents the current status in the research area of energy- and bandwidth-efficient communications and networking and highlights the fundamental issues still open for further investigation. Furthermore, the report presents the Joint Research Activities (JRAs) which will be performed within WP1.3. For each activity there is the description, the identification of the adherence with the identified fundamental open issues, a presentation of the initial results, and a roadmap for the planned joint research work in each topic.Preprin

Distributed radio resource management in LTE-advanced networks with type 1 relay

Long Term Evolution (LTE)-Advanced is proposed as a candidate of the 4th generation (4G) mobile telecommunication systems. As an evolved version of LTE, LTE- Advanced is also based on Orthogonal Frequency Division Multiplexing (OFDM) and in addition, it adopts some emerging technologies, such as relaying. Type I relay nodes, de_ned in LTE-Advanced standards, can control their cells with their own reference signals and have Radio Resource Management (RRM) functionalities. The rationale of RRM is to decide which resources are allocated to which users for optimising performance metrics, such as throughput, fairness, power consumption and Quality of Service (QoS). The RRM techniques in LTE-Advanced networks, including route selection, resource partitioning and resource scheduling, are facing new challenges brought by Type 1 relay nodes and increasingly becoming research focuses in recent years. The research work presented in this thesis has made the following contributions. A service-aware adaptive bidirectional optimisation route selection strategy is proposed to consider both uplink optimisation and downlink optimisation according to service type. The load between di_erent serving nodes, including eNBs and relay nodes, are rebalanced under the _xed resource partitioning. The simulation results show that larger uplink throughputs and bidirectional throughputs can be achieved, compared with existing route selection strategies. A distributed two-hop proportional fair resource allocation scheme is proposed in order to provide better two-hop end-to-end proportional fairness for all the User Equipments (UEs), especially for the relay UEs. The resource partitioning is based on the cases of none Frequency Reuse (FR) pattern, full FR pattern and partial FR patterns. The resource scheduling in access links and backhaul links are considered jointly. A proportional fair joint route selection and resource partitioning algorithm isproposed to obtain an improved solution to the two-hop Adaptive Partial Frequency Reusing (APFR) problem with one relay node per cell. In addition, two special situations of APFR, full FR and no FR, are utilised to narrow the iterative search range of the proposed algorithm and reduce its complexity

A Study about Heterogeneous Network Issues Management based on Enhanced Inter-cell Interference Coordination and Machine Learning Algorithms

Under the circumstance of fast growing demands for mobile data, Heterogeneous Networks (HetNets) has been considered as one of the key technologies to solve 1000 times mobile data challenge in the coming decade. Although the unique multi-tier topology of HetNets has achieved high spectrum efficiency and enhanced Quality of Service (QoS), it also brings a series of critical issues. In this thesis, we present an investigation on understanding the cause of HetNets challenges and provide a research on state of arts techniques to solve three major issues: interference, offloading and handover. The first issue addressed in the thesis is the cross-tier interference of HetNets. We introduce Almost Blank Subframes (ABS) to free small cell UEs from cross-tier interference, which is the key technique of enhanced Inter-Cell Interference Coordination (eICIC). Nash Bargain Solution (NBS) is applied to optimize ABS ratio and UE partition. Furthermore, we propose a power based multi-layer NBS Algorithm to obtain optimal parameters of Further enhanced Inter-cell Interference Coordination (FeICIC), which significantly improve macrocell efficiency compared to eICIC. This algorithm not only introduces dynamic power ratio but also defined opportunity cost for each layer instead of conventional zero-cost partial fairness. Simulation results show the performance of proposed algorithm may achieve up to 31.4% user throughput gain compared to eICIC and fixed power ratio FeICIC. This thesis’ second focusing issue is offloading problem of HetNets. This includes (1) UE offloading from macro cell and (2) small cell backhaul offloading. For first aspect, we have discussed the capability of machine learning algorithms tackling this challenge and propose the User-Based K-means Algorithm (UBKCA). The proposed algorithm establishes a closed loop Self-Organization system on our HetNets scenario to maintain desired offloading factor of 50%, with cell edge user factor 17.5% and CRE bias of 8dB. For second part, we further apply machine learning clustering method to establish cache system, which may achieve up to 70.27% hit-ratio and reduce request latency by 60.21% for Youtube scenario. K-Nearest Neighbouring (KNN) is then applied to predict new users’ content preference and prove our cache system’s suitability. Besides that, we have also proposed a system to predict users’ content preference even if the collected data is not complete. The third part focuses on offloading phase within HetNets. This part detailed discusses CRE’s positive effect on mitigating ping-pong handover during UE offloading, and CRE’s negative effect on increasing cross-tier interference. And then a modified Markov Chain Process is established to map the handover phases for UE to offload from macro cell to small cell and vice versa. The transition probability of MCP has considered both effects of CRE so that the optimal CRE value for HetNets can be achieved, and result for our scenario is 7dB. The combination of CRE and Handover Margin is also discussed

Distributed radio resource allocation in wireless heterogeneous networks

This dissertation studies the problem of resource allocation in the radio access network of heterogeneous small-cell networks (HetSNets). A HetSNet is constructed by introducing smallcells(SCs) to a geographical area that is served by a well-structured macrocell network. These SCs reuse the frequency bands of the macro-network and operate in the interference-limited region. Thus, complex radio resource allocation schemes are required to manage interference and improve spectral efficiency. Both centralized and distributed approaches have been suggested by researchers to solve this problem. This dissertation follows the distributed approach under the self-organizing networks (SONs) paradigm. In particular, it develops game-theoretic and learning-theoretic modeling, analysis, and algorithms. Even though SONs may perform subpar to a centralized optimal controller, they are highly scalable and fault-tolerant. There are many facets to the problem of wireless resource allocation. They vary by the application, solution, methodology, and resource type. Therefore, this thesis restricts the treatment to four subproblems that were chosen due to their significant impact on network performance and suitability to our interests and expertise. Game theory and mechanism design are the main tools used since they provide a sufficiently rich environment to model the SON problem. Firstly, this thesis takes into consideration the problem of uplink orthogonal channel access in a dense cluster of SCs that is deployed in a macrocell service area. Two variations of this problem are modeled as noncooperative Bayesian games and the existence of pure-Bayesian Nash symmetric equilibria are demonstrated. Secondly, this thesis presents the generalized satisfaction equilibrium (GSE) for games in satisfaction-form. Each wireless agent has a constraint to satisfy and the GSE is a mixed-strategy profile from which no unsatisfied agent can unilaterally deviate to satisfaction. The objective of the GSE is to propose an alternative equilibrium that is designed specifically to model wireless users. The existence of the GSE, its computational complexity, and its performance compared to the Nash equilibrium are discussed. Thirdly, this thesis introduces verification mechanisms for dynamic self-organization of Wireless access networks. The main focus of verification mechanisms is to replace monetary transfers that are prevalent in current research. In the wireless environment particular private information of the wireless agents, such as block error rate and application class, can be verified at the access points. This verification capability can be used to threaten false reports with backhaul throttling. The agents then learn the truthful equilibrium over time by observing the rewards and punishments. Finally, the problem of admission control in the interfering-multiple access channel with rate constraints is addressed. In the incomplete information setting, with compact convex channel power gains, the resulting Bayesian game possesses at least one pureBayesian Nash equilibrium in on-off threshold strategies. The above-summarized results of this thesis demonstrate that the HetSNets are amenable to self-organization, albeit with adapted incentives and equilibria to fit the wireless environment. Further research problems to expand these results are identified at the end of this document

Busy burst technology applied to OFDMA–TDD systems

The most significant bottleneck in wireless communication systems is an ever-increasing disproportion between the bandwidth demand and the available spectrum. A major challenge in the field of wireless communications is to maximise the spatial reuse of resources whilst avoiding detrimental co-channel interference (CCI). To this end, frequency planning and centralised coordination approaches are widely used in wireless networks. However, the networks for the next generation of wireless communications are often envisioned to be decentralised, randomly distributed in space, hierarchical and support heterogeneous traffic and service types. Fixed frequency allocation would not cater for the heterogeneous demands and centralised resource allocation would be cumbersome and require a lot of signalling. Decentralised radio resource allocation based on locally available information is considered the key. In this context, the busy burst (BB) signalling concept is identified as a potential mechanism for decentralised interference management in future generation networks. Interference aware allocation of time-frequency slots (chunks) is accomplished by letting receivers transmit a BB in a time-multiplexed mini-slot, upon successful reception of data. Exploiting channel reciprocity of the time division duplex (TDD) mode, the transmitters avoid reusing the chunks where the received BB power is above a pre-determined threshold so as to limit the CCI caused towards the reserved chunks to a threshold value. In this thesis, the performance of BB signalling mechanism in orthogonal frequency division multiple access - time division duplexing (OFDMA-TDD) systems is evaluated by means of system level simulations in networks operating in ad hoc and cellular scenarios. Comparisons are made against the state-of-the-art centralised CCI avoidance and mitigation methods, viz. frequency planning, fractional frequency reuse, and antenna array with switched grid of beams, as well as decentralised methods such as the carrier sense multiple access method that attempt to avoid CCI by avoiding transmission on chunks deemed busy. The results demonstrate that with an appropriate choice of threshold parameter, BB-based techniques outperform all of the above state-of-the-art methods. Moreover, it is demonstrated that by adjusting the BB-specific threshold parameter, the system throughput can be traded off for improving throughput for links with worse channel condition, both in the ad hoc and cellular scenario. Moreover, by utilising a variable BB power that allows a receiver to signal the maximum CCI it can tolerate, it is shown that a more favourable trade-off between total system throughput and link throughput can be made. Furthermore, by performing link adaptation, it is demonstrated that the spatial reuse and the energy efficiency can be traded off by adjusting the threshold parameter. Although the BB signalling mechanism is shown to be effective in avoiding detrimental CCI, it cannot mitigate CCI by itself. On the other hand, multiple antenna techniques such as adaptive beamforming or switched beam approaches allow CCI to be mitigated but suffer from hidden node problems. The final contribution of this thesis is that by combining the BB signalling mechanism with multiple antenna techniques, it is demonstrated that the hybrid approach enhances spatial reusability of resources whilst avoiding detrimental CCI. In summary, this thesis has demonstrated that BB provides a flexible radio resource mechanism that is suitable for future generation networks

Energy Efficient Cloud Computing Based Radio Access Networks in 5G. Design and evaluation of an energy aware 5G cloud radio access networks framework using base station sleeping, cloud computing based workload consolidation and mobile edge computing

Fifth Generation (5G) cellular networks will experience a thousand-fold increase in data traffic with over 100 billion connected devices by 2020. In order to support this skyrocketing traffic demand, smaller base stations (BSs) are deployed to increase capacity. However, more BSs increase energy consumption which contributes to operational expenditure (OPEX) and CO2 emissions. Also, an introduction of a plethora of 5G applications running in the mobile devices cause a significant amount of energy consumption in the mobile devices. This thesis presents a novel framework for energy efficiency in 5G cloud radio access networks (C-RAN) by leveraging cloud computing technology. Energy efficiency is achieved in three ways; (i) at the radio side of H-C-RAN (Heterogeneous C-RAN), a dynamic BS switching off algorithm is proposed to minimise energy consumption while maintaining Quality of Service (QoS), (ii) in the BS cloud, baseband workload consolidation schemes are proposed based on simulated annealing and genetic algorithms to minimise energy consumption in the cloud, where also advanced fuzzy based admission control with pre-emption is implemented to improve QoS and resource utilisation (iii) at the mobile device side, Mobile Edge Computing (MEC) is used where computer intensive tasks from the mobile device are executed in the MEC server in the cloud. The simulation results show that the proposed framework effectively reduced energy consumption by up to 48% within RAN and 57% in the mobile devices, and improved network energy efficiency by a factor of 10, network throughput by a factor of 2.7 and resource utilisation by 54% while maintaining QoS