Mustafa Ismael Salman

Radio Resource Management for Green 3GPP Long Term Evolution Cellular Networks: Review and Trade-offs

Abstract Conventional design of cellular systems aims to maximize the system capacity and spectral efficiency due to sustainable growth of data rate requirements. As the energy consumption becomes relatively high, energy-efficient design for cellular systems is highly required to save energy as well as reducing the undesirable carbon dioxide emitted by these systems. However, reducing the energy consumption will degrade other system performances such as the data rate and quality of service. Therefore, joint optimization for overall system performances should be achieved. In this paper, the energy-efficient radio resource management (RRM) for Long Term Evolution (LTE) systems is addressed. After a brief introduction to LTE radio resource block and LTE frame, different types of energy efficiency metrics are defined to give a better understanding to the energy efficiency perspectives. The energy-efficient approaches related to link adaptation and RRM are explained. The state-of-the-art energy-efficient schedulers are also discussed, and a comprehensive comparison between them is adopted in this paper. Moreover, many trade-offs, challenges, and open issues are addressed to optimize the system performances.

A self-configured link adaptation for green LTE downlink transmission

Green deployment for cellular eNodeBs has been proposed recently to save power and reduce the huge amount of carbon dioxide CO 2 emitted by traditional power-hungry base stations. Green eNodeBs should also be subjected to restrictions on high data rate and quality of service QoS, which both entail a high level of power consumption. In this regard, this paper addresses the trade-off between energy efficiency EE and spectral efficiency SE in both traditional and green long-term evolution eNodeBs without sacrificing the QoS. EE is proved to monotonically increase with SE in traditional macrocells and quasi-concave in green macrocells. Accordingly, a new mapping between channel quality indicator and modulation and coding scheme is proposed to address EE-SE trade-off with the use of a multi-criteria decision-making technique. Then, a self-configured link adaptation SCLA algorithm is developed to ensure that the priority weights related to EE and SE are adapted according to network load with the use of real-time cross-layer optimization. Simulation results show that the proposed SCLA provides a significant gain in EE and 52% reduction of CO 2 while maintaining SE close to the optimal value. Current and next-generation cellular networks require such interactive techniques in order to be self-optimised without complex modifications. Copyright

CQI-MCS Mapping for Green LTE Downlink Transmission

Maximizing the data rate and spectral efficiency are the main targets in LTE cellular systems. However, any increase in data rate or spectral efficiency will result in an undesirable increase in energy consumption. Hence, both energy efficiency (EE) and spectral efficiency (SE) necessitate to be optimized. In this paper, a multi-objective optimization framework is formulated to prove the tradeoff between both EE and SE in LTE downlink transmission. A new mapping algorithm between channel quality indicator (CQI) and modulation and coding scheme (MCS) is proposed by using a multi-criteria decision making technique. The proposed CQI- MCS mapping algorithm will search for the most suitable MCS according to the reported CQI value by considering the tradeoff between SE and EE while keeping block error rate (BLER) below its threshold value. Simulation results have shown that the proposed mapping algorithm can provide an efficient compromise solution compared to the existing 3GPP-LTE mapping. Therefore, the proposed CQI-MCS mapping can optimize the EE and SE based on different mapping values depending on the operator preferences.

Energy efficient transmission for LTE cellular system

With the introduction of Long Term Evolution (LTE) cellular networks, the spectral efficiency should be maximized according to the required high data rate. However, any increase in spectral efficiency will lead to an undesirable increase in power consumption, and thus lower energy efficiency will be obtained. Therefore, a new problem in radio resource allocation is addressed to manage the bandwidth and power resources according to LTE and Green communication requirements. So far, the main objective of the most radio resource allocation algorithms is to increase the data rate without much consideration of the energy or power metrics. Some of them had to minimize the power consumption at a given data rate requirements. In this paper, we propose a multi-objective radio resource function which aims to maximize energy efficiency at a given data rate requirement. This function will consider dynamic subcarrier assignment to assign different subcarriers to different users. A multiuser orthogonal frequency division multiplexing (OFDMA) represents the physical layer of LTE system along with a single transmitting antenna to transmit the data in a frequency flat fading channel. It has been shown that the transmission bandwidth and modulation order have impacts on the energy efficiency.

An Adaptive Threshold Feedback Compression Scheme Based on Channel Quality Indicator (CQI) in Long Term Evolution (LTE) System

Channel quality indicator (CQI) feedback in long-term evolution (LTE) system is an essential technique in describing the instantaneous channel state information. The CQI calculations highly depend on the accuracy of the channel estimation process in order to assign appropriate modulation and coding scheme. However, one of the critical issues affecting the LTE system performance is obtaining the CQI for each transmission period which will inevitably cost many resources. Therefore, an appropriate method for reducing CQI feedback overhead along with accurate channel estimation technique is required to manage the allocated resources and obtains significant improvements in system performance. In this paper, an adaptive threshold feedback compression scheme based on CQI scheme is proposed to obtain better system performance in terms of system throughput and error rate in LTE system. This proposed adaptive scheme dynamically adapts its threshold level to the signal to noise ratio variations, thus increasing the throughput and reducing the CQI feedback overhead. Results show that the proposed CQI based adaptive threshold feedback compression scheme enhances the tradeoff between system throughput and block error rate.

Approximate Linear Minimum Mean Square Error estimation based on Channel Quality Indicator feedback in LTE systems

The fast fading channel produced by the fast user mobility requires a powerful channel estimation to report the most accurate channel status. Such estimation techniques are usualy suffer from large number of computational processes, and thus, their complexity needs to be minimized. However, the calculation reliability of channel coefficients depends mainly on the accuracy of the channel estimation model. Therefore, obtaining a joint optimized solution for channel estimation error, feedback overhead, and complexity is very crucial. In this paper, two different channel estimation schemes; Linear Minimum Mean Square Error (LMMSE) and Approximate Linear Minimum Mean Square Error (ALMMSE) are used to calculate Channel Quality Indicator (CQI) and Precoding Matrix Indicator (PMI) in the 3GPP-LTE fast fading channel. It is found that, by using a low-complexity ALMMSE, the estimation error is reduced with relatively small reduction in throughput. Therefore, the proposed method is recommended to be used when the network is not fully loaded for better tradeoff concerning MSE and throughput taking into account the fixed and mobility scenarios, and thus, reliable transmission will be targeted.

Energy- and Spectral-Efficient Wireless Cellular Networks

The limited spectrum resources and the negative impacts of carbon dioxide emission resulted from inefficient use of wireless technologies have led to the development of green radio. Both the energy and spectral efficiencies should be considered together to meet green radio requirements. In this paper, we investigate the trade-off between energy efficiency and spectral efficiency through different approaches. Cognitive radio is a paradigm-shift technology which is used to increase both the energy and spectral efficiencies. Some efficient spectrum sensing techniques are considered in terms of energy and time consuming. Furthermore, it can be shown that the power control strategies can play a key role in avoiding interference between cognitive and primary users, and hence it can also enhance both the energy and spectral efficiencies. In addition to cognitive radio, a new infrastructure for deploying the cellular base stations which is a heterogeneous infrastructure of macro-, pico-, and femto-cells is proposed to overcome the energy and bandwidth constraints. Further details related to hardware-constraints in a green base station have also been covered.

Review of Channel Quality Indicator Estimation Schemes for Multi-User MIMO in 3GPP LTE/LTE-A Systems

Multiple-in multiple-out (MIMO) in long-term evolution (LTE) is an essential factor in achieving high speed data rates and spectral efficiency. The unexpected growth in data rate demand has pushed researchers to extend the benefits of multi-user MIMO. The multi-user MIMO system can take full advantage of channel conditions by employing efficient adjustment techniques for scheduling, and by assigning different modulation and coding rates. However, one of the critical issues affecting this feature is the appropriate estimation of channel quality indicator (CQI) to manage the allocated resources to users. Therefore, an accurate CQI estimation scheme is required for the multi-user MIMO transmission to obtain significant improvements on spectral efficiency. This paper presents overviews of multi-user MIMO in LTE/LTE-advanced systems. The link adaptation, scheduling process, and different factors that affect the reliability of CQI measurements are discussed. State-of-the-art schemes for the post-processing CQI estimation, and the comparisons of various CQI estimation schemes to support multi-user MIMO are also addressed.

A channel quality indicator (CQI) prediction scheme using feed forward neural network (FF-NN) technique for MU-MIMO LTE system

In Multi User-Multiple-in Multiple-Out - Long Term Evolution (MU-MIMO-LTE) networks, Channel Quality indicator (CQI) plays a vital role. CQI is crucial in describing the channel information to assign appropriate modulation and coding scheme (MCS). However, obtaining CQI values for each transmission time interval (TTI) inevitably entails use and can lead to an undesirable degradation in spectral efficiency (SE) as well as increasing the error rate. Therefore, providing an accurate and reliable CQI with low overhead is an intricate task. In this paper, a CQI prediction scheme using Feed Forward-Neural Network (FF-NN) algorithm for MU-MIMO-LTE Advanced systems is proposed. Initially, a channel model for MU-MIMO-LTE advanced network is carried out. Through this model, CQI is predicted and the obtained values are compressed using a feedback compression technique. Finally, the proposed technique makes use of FF-NN algorithm to train and achieve enhanced CQI values. Further, an enhanced and accurate CQI values are acquired. Results show that the system SE of single user (SU)-MIMO proportionally increases with the SNR values at the cost of BER. Therefore, a MU-MIMO CQI prediction scheme is recommended to improve the tradeoff between BER and SE.