Energy and Spectral Efficiency Balancing Algorithm for Energy Saving in LTE Downlinks

In wireless network communication environments, Spectral Efficiency (SE) and Energy Efficiency (EE) are among the major indicators used for evaluating network performance. However, given the high demand for data rate services and the exponential growth of energy consumption, SE and EE continue to elicit increasing attention in academia and industries. Consequently, a study of the trade-off between these metrics is imperative. In contrast with existing works, this study proposes an efficient SE and EE trade-off algorithm for saving energy in downlink Long Term Evolution (LTE) networks to concurrently optimize SE and EE while considering battery life at the Base Station (BS). The scheme is formulated as a Multi-objective Optimization Problem (MOP) and its Pareto optimal solution is examined. In contrast with other algorithms that prolong battery life by considering the idle state of a BS, thereby increasing average delay and energy consumption, the proposed algorithm prolongs battery life by adjusting the initial and final states of a BS to minimize the average delay and the energy consumption. Similarly, the use of an omni-directional antenna to spread radio signals to the user equipment in all directions causes high interference and low spatial reuse. We propose using a directional antenna instead of an omni-directional antenna by transmitting signals in one direction which results in no or low interference and high spatial reuse. The proposed scheme has been extensively evaluated through simulation, where simulation results prove that the proposed scheme is efficiently able to decrease the average response delay, improve SE, and minimize energy consumption.Comment: 19 page

An adaptive call admission control with bandwidth reservation for downlink LTE networks

In recent years, consumers of 4G cellular networks have increased exponentially as they discover that the service is user-friendly. Due to the large users and their frequent demands, it is necessary to use the limited network resources that guarantee the eminent standard quality of service (QoS). Call admission control (CAC) scheme has a major impact in assuring QoS for different users with various QoS requirements in 4G networks. Recently, the reservation-based scheme and bandwidth degradation schemes were proposed with the aim to provide effective use of network resources and assure QoS requirements to admitted calls. However, in spite of these several objectives, these schemes are not efficient as a result of the modeling and approximation method that starve the best effort (BE) traffic. The dynamic threshold value approach adjusts handoff call and new call based on time-varying conditions resulted in a waste of network resources, where bandwidth are reserved for handoff call, but at the network environment, there is little or no handoff calls. In this paper, we propose a novel CAC scheme to provide effective use of network resources and avoid the starvation of BE traffic. The scheme introduces an adaptive threshold value, which adjusts the network resources under heavy traffic intensity. In addition, we proposed reservation and degradation approach to admit many users when there is a limited number of bandwidth, which also achieved effective utilization of network resources. Simulation results show that the proposed scheme significantly outperforms the reservation-based scheme and bandwidth degradation schemes in terms of admitting many calls and guaranteeing QoS to all the traffic types in the network. Numerical results imitate to experimental results with insignificant differences

Efficient radio resource management algorithms for downlink long term evolution networks

The increasing demand for wireless network services, particularly for downlink broadband communication has triggered the evolution of cellular networks. The Third Generation Partnership Project (3GPP) introduced the Long Term Evolution (LTE) in response to the forthcoming fourth-generation (4G) cellular networks. LTE is a very complex and large standard. Its performance is dependent on the large range of elements. One of the key essential elements is Radio Resource Management (RRM). RRM has a great impact on the system performance due to many problematic aspects such as packet scheduling, Call Admission Control (CAC) and Energy Efficiency (EE). With the aim to meet the LTE QoS requirements (i.e. Quality of Service (QoS), fairness provisioning, minimal delay, packet loss, and throughput maximization), the objective of scheduling algorithm is critical to use limited available spectrum. As long as choosing an appropriate scheduling algorithm is not standardized by the 3GPP specification for LTE, vendors are free to adopt, configure and implement their own algorithms depending on the problems of the system. Nevertheless, achieving all the intended objectives simultaneously is difficult. Each problem solved can lead to additional ones. For instance, radio resource algorithms intended to maximize system throughput are not appropriate for handling guaranteed bit rate traffic. Hence, the major problem is developing a scheduling algorithm which creates a trade-off between the system performances. It is imperative to note that, in spite of the network-wide control schemes to ease transmission order, mobile data content overwhelms the available bandwidth for each node in many high traffic times. According to this premise, it is understandable that the transmission order is an inevitable issue in LTE mobile networks. Therefore, this thesis examines the efficient resource scheduling algorithms to be resistant to the unpredicted transmission order patterns. Firstly, a QoS channel quality identifier algorithm is proposed, to support the transmission order of users while considering the QoS requirements as well as the channel condition. The algorithm is based on the idea of the optimization problem in which resource allocation problem is formulated as an optimization problem. Optimal priority algorithm uses minimum data rate to guarantees resource allocation to users but increases the average delay and deteriorate the network performance. Therefore, the proposed algorithm minimizes the average delay and improves the network performance. In addition to network deterioration, the admitting of users to the network environment contributes to the ineffective use of resources. Thus, we proposed a call admission control algorithm that admits users to utilize available resources. It adaptively defines how users should be admitted, by considering the network conditions. Furthermore, to deal with the energy consumption problem and provide a trade-off between spectral and energy efficiency, we proposed a spectral and energy efficiency trade-off algorithm. Unlike other algorithms that prolong the battery lifetime by considering the idle state of the base station, thus increasing the average delay and increases the energy consumption. Our algorithms prolong the battery life by adjusting the base station using initial and final states. Consequently, minimizes the average delay as well as low energy consumption. Similarly, the use of omnidirectional antenna to spread radio signals to UEs in all directions causes high interference and low special reuse. We proposed the used of the directional antenna to replaces the omnidirectional antenna by transmitting signals in one direction 600 and 1200 which resulted in no or less interference as well as high spatial reuse. Substantial simulations have been extensively carried out to evaluate the performance of the proposed algorithms compared with the existing RRM algorithms. The findings demonstrate that the proposed algorithms have shown significant improvements, which includes: lowering delay, minimizes packet loss, improve fairness, and increases the throughput of the system in the proposed QoS channel quality indicator algorithm. Secondly, the proposed call admission control algorithm improved the resource utilization algorithm thus reducing the call block, call dropped, call degradation. This has further enabled the improvement of data throughput. Lastly, reducing the amount of energy consumed and lowering delay is shown in the proposed spectral-energy efficiency algorithm. Overall, the research has shown promising support and improvements to LTE networks scheduling algorithms and to associated challenges in wireless communication paradigm. Likewise, it would be valuable if the proposed scheduling algorithms are evaluated on anticipated networks covering a large number of users in further research