Scheduling start time in CDMA burst admission

Burst transmission protocols have been proposed in the next generation CDMA cellular systems to support short-time high-speed data communications. The existing burst admission algorithm considers only the current interference condition in the system. The burst transmission request will be rejected if the interference in the system will exceed the acceptable level with the burst admitted. In this paper we propose a new burst admission algorithm where a currently-unacceptable burst request can be assigned to start at a later time when the system interference level is lower. The interference prediction is based on the establishing, updating, and exchanging the load and burst scheduling tables among the neighboring cells. Simulations show that our method can reduce the burst blocking probability and improve the system resource utilization.published_or_final_versio

A study on propagation characteristics and interference of spread spectrum code division multiple access cellular radio systems.

by Kwok Ming Shan.Thesis (M.Phil.)--Chinese University of Hong Kong, 1995.Includes bibliographical references (leaves 102-[109]).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Cellular Radio Systems --- p.3Chapter 1.2 --- Code Division Multiple Access (CDMA) --- p.7Chapter 1.2.1 --- Direct Sequence CDMA (DS-CDMA) --- p.8Chapter 1.2.2 --- Frequency Hopping CDMA (FH-GDMA) --- p.11Chapter 1.2.3 --- Time Hopping CDMA (TH-CDMA) --- p.12Chapter 1.3 --- Propagation Characteristics --- p.12Chapter 1.3.1 --- Signal Strength Prediction - Path Loss --- p.13Chapter 1.3.2 --- Signal Variability --- p.17Chapter 1.3.3 --- Delay Spread --- p.23Chapter 1.3.4 --- Coherence Bandwidth --- p.23Chapter 1.4 --- Power Control in Cellular Radio Systems --- p.24Chapter 1.4.1 --- Centralized Power Control --- p.24Chapter 1.4.2 --- Distributed Power Control --- p.25Chapter 1.4.3 --- CDMA Power Control --- p.29Chapter 2 --- Contributions --- p.39Chapter 3 --- ACI Analysis of the Reverse-Link --- p.41Chapter 3.1 --- Adjacent Cell Interference --- p.42Chapter 3.2 --- Adjacent Cell Interference Analysis --- p.43Chapter 3.2.1 --- Interference Analysis of Hexagonal Cells --- p.43Chapter 3.2.2 --- Interference Analysis of Circular Cell Structure --- p.47Chapter 3.3 --- Closed-form of Adjacent Cell Interference --- p.51Chapter 3.4 --- Generalization to Irregular Cell Structure --- p.54Chapter 3.5 --- Conclusions --- p.57Chapter 4 --- ACI Analysis of Reverse-Link with Log-normal Shadowing --- p.59Chapter 4.1 --- Interference with Shadowing --- p.59Chapter 4.2 --- Conclusions --- p.66Chapter 5 --- ACI Analysis of Microcell --- p.68Chapter 5.1 --- Propagation Characteristics of Microcellular Radio Systems --- p.69Chapter 5.2 --- CDMA Microcellular Radio Systems --- p.70Chapter 5.3 --- Results and Discussions --- p.74Chapter 5.4 --- Conclusions --- p.76Chapter 6 --- Outage Probability Analysis of Imperfect Power Control --- p.77Chapter 6.1 --- Fast Fading of Signal --- p.78Chapter 6.2 --- Imperfect Power Control in CDMA --- p.81Chapter 6.3 --- Conclusions --- p.85Chapter 7 --- Conclusions --- p.88Chapter 8 --- Examples of CDMA Cellular Radio Systems --- p.91Chapter 8.1 --- Qualcomm CDMA system --- p.91Chapter 8.1.1 --- Forward-link --- p.92Chapter 8.1.2 --- Reverse-link --- p.93Chapter 8.1.3 --- Reverse-Link Open-Loop Power Control --- p.94Chapter 8.1.4 --- Reverse-Link Closed-Loop Power Control --- p.95Chapter 8.1.5 --- Forward-Link Power Control --- p.96Chapter 8.2 --- Interdigital Broadband CDMA System --- p.96Appendix --- p.97Chapter A --- Derivation of the PDF of the fast fading signal power --- p.97Chapter B --- Derivation of the Mean-to-standard deviation ratio --- p.98Chapter C --- Acronyms --- p.100Bibliography --- p.10

A Framework for Enhancing the Energy Efficiency of IoT Devices in 5G Network

A wide range of services, such as improved mobile broadband, extensive machine-type communication, ultra-reliability, and low latency, are anticipated to be delivered via the 5G network. The 5G network has developed as a multi-layer network that uses numerous technological advancements to provide a wide array of wireless services to fulfil such a diversified set of requirements. Several technologies, including software-defined networking, network function virtualization, edge computing, cloud computing, and tiny cells, are being integrated into the 5G networks to meet the needs of various requirements. Due to the higher power consumption that will arise from such a complicated network design, energy efficiency becomes crucial. The network machine learning technique has attracted a lot of interest from the scientific community because it has the potential to play a crucial role in helping to achieve energy efficiency. Utilization factor, access latency, arrival rate, and other metrics are used to study the proposed scheme. It is determined that our system outperforms the present scheme after comparing the suggested scheme to these parameters

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

Green Cellular Networks: A Survey, Some Research Issues and Challenges

Energy efficiency in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall environment effects. This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure. In this article, we present a brief survey of methods to improve the power efficiency of cellular networks, explore some research issues and challenges and suggest some techniques to enable an energy efficient or "green" cellular network. Since base stations consume a maximum portion of the total energy used in a cellular system, we will first provide a comprehensive survey on techniques to obtain energy savings in base stations. Next, we discuss how heterogeneous network deployment based on micro, pico and femto-cells can be used to achieve this goal. Since cognitive radio and cooperative relaying are undisputed future technologies in this regard, we propose a research vision to make these technologies more energy efficient. Lastly, we explore some broader perspectives in realizing a "green" cellular network technologyComment: 16 pages, 5 figures, 2 table