Location Aided Energy Balancing Strategy in Green Cellular Networks

Most cellular network communication strategies are focused on data traffic scenarios rather than energy balance and efficient utilization. Thus mobile users in hot cells may suffer from low throughput due to energy loading imbalance problem. In state of art cellular network technologies, relay stations extend cell coverage and enhance signal strength for mobile users. However, busy traffic makes the relay stations in hot area run out of energy quickly. In this paper, we propose an energy balancing strategy in which the mobile nodes are able to dynamically select and hand over to the relay station with the highest potential energy capacity to resume communication. Key to the strategy is that each relay station merely maintains two parameters that contains the trend of its previous energy consumption and then predicts its future quantity of energy, which is defined as the relay station potential energy capacity. Then each mobile node can select the relay station with the highest potential energy capacity. Simulations demonstrate that our approach significantly increase the aggregate throughput and the average life time of relay stations in cellular network environment.Comment: 6 pages, 5 figures. arXiv admin note: text overlap with arXiv:1108.5493 by other author

Interference mitigation and interference avoidance for cellular OFDMA-TDD networks

In recent years, cellular systems based on orthogonal frequency division multiple access – time division duplex (OFDMA-TDD) have gained considerable popularity. Two of the major reasons for this are, on the one hand, that OFDMA enables the receiver to effectively cope with multipath propagation while keeping the complexity low. On the other hand, TDD offers efficient support for cell-specific uplink (UL)/downlink (DL) asymmetry demands by allowing each cell to independently set its UL/DL switching point (SP). However, cell-independent SP gives rise to crossed slots. In particular, crossed slots arise when neighbouring cells use the same slot in opposing link directions, resulting in base station (BS)-to-BS interference and mobile station (MS)-to-MS interference. BS-to-BS interference, in particular, can be quite detrimental due to the exposed location of BSs, which leads to high probability of line-of-sight (LOS) conditions. The aim of this thesis is to address the BS-to-BS interference problem in OFDMA-TDDcellular networks. A simulation-based approach is used to demonstrate the severity of BS-to-BS interference and a signal-to-interference-plus-noise ratio (SINR) equation for OFDMA is formulated to aid system performance analysis. The detrimental effects of crossed slot interference in OFDMA-TDD cellular networks are highlighted by comparing methods specifically targeting the crossed slots interference problem. In particular, the interference avoidance method fixed slot allocation (FSA) is compared against state of the art interference mitigation approaches, viz: random time slot opposing (RTSO) and zone division (ZD). The comparison is done based on Monte Carlo simulations and the main comparison metric is spectral efficiency calculated using the SINR equation formulated in this thesis. The simulation results demonstrate that when LOS conditions among BSs are present, both RTSO and ZD perform worse than FSA for all considered performance metrics. It is concluded from the results that current interference mitigation techniques do not offer an effective solution to the BS-to-BS interference problem. Hence, new interference avoidance methods, which unlike FSA, do not sacrifice the advantages of TDD are open research issues addressed in this thesis. The major contribution of this thesis is a novel cooperative resource balancing technique that offers a solution to the crossed slot problem. The novel concept, termed asymmetry balancing, is targeted towards next-generation cellular systems, envisaged to have ad hoc and multi-hop capabilities. Asymmetry balancing completely avoids crossed slots by keeping the TDD SPs synchronised among BSs. At the same time, the advantages of TDD are retained, which is enabled by introducing cooperation among the entities in the network. If a cell faces resource shortage in one link direction, while having free resources in the opposite link direction, the free resources can be used to support the overloaded link direction. In particular, traffic can be offloaded to near-by mobile stations at neighbouring cells that have available resources. To model the gains attained with asymmetry balancing, a mathematical framework is developed which is verified by Monte Carlo simulations. In addition, asymmetry balancing is compared against both ZD and FSA based on simulations and the results demonstrate the superior performance of asymmetry balancing. It can be concluded that the novel interference avoidance approach is a very promising candidate t

A survey on intelligent computation offloading and pricing strategy in UAV-Enabled MEC network: Challenges and research directions

The lack of resource constraints for edge servers makes it difficult to simultaneously perform a large number of Mobile Devices’ (MDs) requests. The Mobile Network Operator (MNO) must then select how to delegate MD queries to its Mobile Edge Computing (MEC) server in order to maximize the overall benefit of admitted requests with varying latency needs. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligent (AI) can increase MNO performance because of their flexibility in deployment, high mobility of UAV, and efficiency of AI algorithms. There is a trade-off between the cost incurred by the MD and the profit received by the MNO. Intelligent computing offloading to UAV-enabled MEC, on the other hand, is a promising way to bridge the gap between MDs' limited processing resources, as well as the intelligent algorithms that are utilized for computation offloading in the UAV-MEC network and the high computing demands of upcoming applications. This study looks at some of the research on the benefits of computation offloading process in the UAV-MEC network, as well as the intelligent models that are utilized for computation offloading in the UAV-MEC network. In addition, this article examines several intelligent pricing techniques in different structures in the UAV-MEC network. Finally, this work highlights some important open research issues and future research directions of Artificial Intelligent (AI) in computation offloading and applying intelligent pricing strategies in the UAV-MEC network

Towards reliable communication in LTE-A connected heterogeneous machine to machine network

Machine to machine (M2M) communication is an emerging technology that enables heterogeneous devices to communicate with each other without human intervention and thus forming so-called Internet of Things (IoTs). Wireless cellular networks (WCNs) play a significant role in the successful deployment of M2M communication. Specially the ongoing massive deployment of long term evolution advanced (LTE-A) makes it possible to establish machine type communication (MTC) in most urban and remote areas, and by using LTE-A backhaul network, a seamless network communication is being established between MTC-devices and-applications. However, the extensive network coverage does not ensure a successful implementation of M2M communication in the LTE-A, and therefore there are still some challenges. Energy efficient reliable transmission is perhaps the most compelling demand for various M2M applications. Among the factors affecting reliability of M2M communication are the high endto-end delay and high bit error rate. The objective of the thesis is to provide reliable M2M communication in LTE-A network. In this aim, to alleviate the signalling congestion on air interface and efficient data aggregation we consider a cluster based architecture where the MTC devices are grouped into number of clusters and traffics are forwarded through some special nodes called cluster heads (CHs) to the base station (BS) using single or multi-hop transmissions. In many deployment scenarios, some machines are allowed to move and change their location in the deployment area with very low mobility. In practice, the performance of data transmission often degrades with the increase of distance between neighboring CHs. CH needs to be reselected in such cases. However, frequent re-selection of CHs results in counter effect on routing and reconfiguration of resource allocation associated with CH-dependent protocols. In addition, the link quality between a CH-CH and CH-BS are very often affected by various dynamic environmental factors such as heat and humidity, obstacles and RF interferences. Since CH aggregates the traffic from all cluster members, failure of the CH means that the full cluster will fail. Many solutions have been proposed to combat with error prone wireless channel such as automatic repeat request (ARQ) and multipath routing. Though the above mentioned techniques improve the communication reliability but intervene the communication efficiency. In the former scheme, the transmitter retransmits the whole packet even though the part of the packet has been received correctly and in the later one, the receiver may receive the same information from multiple paths; thus both techniques are bandwidth and energy inefficient. In addition, with retransmission, overall end to end delay may exceed the maximum allowable delay budget. Based on the aforementioned observations, we identify CH-to-CH channel is one of the bottlenecks to provide reliable communication in cluster based multihop M2M network and present a full solution to support fountain coded cooperative communications. Our solution covers many aspects from relay selection to cooperative formation to meet the user’s QoS requirements. In the first part of the thesis, we first design a rateless-coded-incremental-relay selection (RCIRS) algorithm based on greedy techniques to guarantee the required data rate with a minimum cost. After that, we develop fountain coded cooperative communication protocols to facilitate the data transmission between two neighbor CHs. In the second part, we propose joint network and fountain coding schemes for reliable communication. Through coupling channel coding and network coding simultaneously in the physical layer, joint network and fountain coding schemes efficiently exploit the redundancy of both codes and effectively combat the detrimental effect of fading conditions in wireless channels. In the proposed scheme, after correctly decoding the information from different sources, a relay node applies network and fountain coding on the received signals and then transmits to the destination in a single transmission. Therefore, the proposed schemes exploit the diversity and coding gain to improve the system performance. In the third part, we focus on the reliable uplink transmission between CHs and BS where CHs transmit to BS directly or with the help of the LTE-A relay nodes (RN). We investigate both type-I and type-II enhanced LTE-A networks and propose a set of joint network and fountain coding schemes to enhance the link robustness. Finally, the proposed solutions are evaluated through extensive numerical simulations and the numerical results are presented to provide a comparison with the related works found in the literature

D13.3 Overall assessment of selected techniques on energy- and bandwidth-efficient communications

Deliverable D13.3 del projecte europeu NEWCOM#The report presents the outcome of the Joint Research Activities (JRA) of WP1.3 in the last year of the Newcom# project. The activities focus on the investigation of bandwidth and energy efficient techniques for current and emerging wireless systems. The JRAs are categorized in three Tasks: (i) the first deals with techniques for power efficiency and minimization at the transceiver and network level; (ii) the second deals with the handling of interference by appropriate low interference transmission techniques; (iii) the third is concentrated on Radio Resource Management (RRM) and Interference Management (IM) in selected scenarios, including HetNets and multi-tier networks.Peer ReviewedPostprint (published version

Routing performance in ad hoc networks.

Thesis (M.Sc.Eng.)-University of Natal, Durban, 2003.An ad hoc network is a multi-hop wireless network in which mobile nodes communicate over a shared wireless channel. The network is formed cooperatively without specific user administration or configuration and is characterised by a distributed network management system and the absence of a wired backbone. Military, law enforcement, and disaster relief operations are often carried out in situations with no pre-existing network infrastructure and can benefit from such networks because base stations, which are single points of failure, are undesirable from a reliability standpoint. The rising popularity of mobile computing has also created a potentially large commercial market for multimedia applications applied over wireless ad hoc networks. This dissertation focuses on the routing aspects of ad hoc networking. The multi-hop routes between nodes constantly change as the mobile nodes migrate. Ad hoc network routing algorithms must therefore adapt to the dynamic and unpredictable topology changes, the random radio propagation conditions and portable power sources. Various routing protocols have been proposed in the literature for ad hoc networks. These protocols together with comparative simulations are discussed and a new protocol based on load balancing and signal quality determination is proposed . and the simulation results are presented. Currently the proposed routing protocols are compared using simulation packages which are often time consuming. This dissertation proposes a mathematical model for evaluating the routing protocols and the resultant end-to-end blocking probabilities. The mathematical model is based on a derivation of the reduced load approximation for analysing networks modelled as loss networks and the evaluation incorporates and adapts models that have been used for the analysis of cellular Code Division Multiple Access (CDMA) systems. While analytical methods of solving blocking probability can potentially generate results orders of magnitude faster than simulation, they are more importantly essential to network sensitivity analysis, design and optimisation

A PARADIGM SHIFTING APPROACH IN SON FOR FUTURE CELLULAR NETWORKS

The race to next generation cellular networks is on with a general consensus in academia and industry that massive densification orchestrated by self-organizing networks (SONs) is the cost-effective solution to the impending mobile capacity crunch. While the research on SON commenced a decade ago and is still ongoing, the current form (i.e., the reactive mode of operation, conflict-prone design, limited degree of freedom and lack of intelligence) hinders the current SON paradigm from meeting the requirements of 5G. The ambitious quality of experience (QoE) requirements and the emerging multifarious vision of 5G, along with the associated scale of complexity and cost, demand a significantly different, if not totally new, approach to SONs in order to make 5G technically as well as financially feasible. This dissertation addresses these limitations of state-of-the-art SONs. It first presents a generic low-complexity optimization framework to allow for the agile, on-line, multi-objective optimization of future mobile cellular networks (MCNs) through only top-level policy input that prioritizes otherwise conflicting key performance indicators (KPIs) such as capacity, QoE, and power consumption. The hybrid, semi-analytical approach can be used for a wide range of cellular optimization scenarios with low complexity. The dissertation then presents two novel, user-mobility, prediction-based, proactive self-optimization frameworks (AURORA and OPERA) to transform mobility from a challenge into an advantage. The proposed frameworks leverage mobility to overcome the inherent reactiveness of state-of-the-art self-optimization schemes to meet the extremely low latency and high QoE expected from future cellular networks vis-à-vis 5G and beyond. The proactiveness stems from the proposed frameworks’ novel capability of utilizing past hand-over (HO) traces to determine future cell loads instead of observing changes in cell loads passively and then reacting to them. A semi-Markov renewal process is leveraged to build a model that can predict the cell of the next HO and the time of the HO for the users. A low-complexity algorithm has been developed to transform the predicted mobility attributes to a user-coordinate level resolution. The learned knowledge base is used to predict the user distribution among cells. This prediction is then used to formulate a novel (i) proactive energy saving (ES) optimization problem (AURORA) that proactively schedules cell sleep cycles and (ii) proactive load balancing (LB) optimization problem (OPERA). The proposed frameworks also incorporate the effect of cell individual offset (CIO) for balancing the load among cells, and they thus exploit an additional ultra-dense network (UDN)-specific mechanism to ensure QoE while maximizing ES and/or LB. The frameworks also incorporates capacity and coverage constraints and a load-aware association strategy for ensuring the conflict-free operation of ES, LB, and coverage and capacity optimization (CCO) SON functions. Although the resulting optimization problems are combinatorial and NP-hard, proactive prediction of cell loads instead of reactive measurement allows ample time for combination of heuristics such as genetic programming and pattern search to find solutions with high ES and LB yields compared to the state of the art. To address the challenge of significantly higher cell outage rates in anticipated in 5G and beyond due to higher operational complexity and cell density than legacy networks, the dissertation’s fourth key contribution is a stochastic analytical model to analyze the effects of the arrival of faults on the reliability behavior of a cellular network. Assuming exponential distributions for failures and recovery, a reliability model is developed using the continuous-time Markov chains (CTMC) process. Unlike previous studies on network reliability, the proposed model is not limited to structural aspects of base stations (BSs), and it takes into account diverse potential fault scenarios; it is also capable of predicting the expected time of the first occurrence of the fault and the long-term reliability behavior of the BS. The contributions of this dissertation mark a paradigm shift from the reactive, semi-manual, sub-optimal SON towards a conflict-free, agile, proactive SON. By paving the way for future MCN’s commercial and technical viability, the new SON paradigm presented in this dissertation can act as a key enabler for next-generation MCNs