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In recent years, the enormous energy consumption of wirelesscommunication systems has aroused universal concerns throughout the world. Hence, energy efficiency has become one of the central topics in today’s wireless communication industry. In this paper, we study energy-efficient resource allocation for Long Term Evolution (LTE) cellular mobile systems. To be applicable in LTE systems, both multiple-input multiple-output (MIMO) orthogonal frequency-division multiple access (OFDMA) radio access network and resource blocks (RBs) for subchannel assignment are considered in this work, functioning as two distinguishing characteristics for LTE resource allocation. In particular, an optimization problem concerning joint RB assignment, and power allocation is formulated to maximize the energy efficiency measured by “bits-per-Joule” metric, under per-user quality-of-service (QoS) requirements in the form of user rate constraints.

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This thesis focuses on single–user MIMO mode in 3GPP LTE downlink ..

We first show that this energy-efficient resource allocation problem can be converted into a more tractable equivalent problem by which the fractional objective of energy efficiency is well settled. With the Lagrange dual method then, we decouple the RB assignment and power allocation on different subchannels using dual decomposition, which greatly simplifies the combinatorial RB assignment, and address the equivalent problem effectively via solving a series of dual optimization problems. Moreover, a computationally efficient but near-optimal algorithm is proposed to perform QoS-aware energy-efficient resource allocation in practice. Simulation results show that our proposed algorithm may not only improve energy efficiency significantly but fully satisfy users’ rate requirements as well. Moreover, with MIMO-OFDMA and RB assignment being considered, the proposed algorithm may be more applicable in LTE systems than most existing schemes on energy-efficient resource allocation.

Performance of MIMO Aware RRM in Downlink OFDMA

Broadband mobile communication has enabled MIMO technology and OFDM technology to become the most promising research direction in the field of wireless mobile communication in the future. OFDMA technology growing up based on OFDM is a multiple-access technology, whose channel design will generate more influence for system capability. OFMDA technology can apply suitable channel design for bringing about high efficiency communication in allusion to different environment. And the channel could select or device a better estimator algorithm by algorithm t- heory to enhance communication reliability ().

in this paper we propose and investigate a cross-layer multiuser scheduling strategy for the support of heterogeneous traffic in the downlink of a MIMO-OFDMA system.
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There are other more technical benefits in the connection. Perhaps the most important is that efficient rate allocation is possible through the use of . It is also possible to share the bandwidth more efficiently through the use of OFDMA (A for access), where users are allocated different parts of the spectrum but the equalization benefits are still obtained. There are also challenges, most inherited from OFDM. These include tighter synchronization requirements and a high peak-to-average-power-ratio. Alternatives such as single carrier frequency domain equalization (SC-FDE) have been suggested to solve this problem but has yet to see commercial success. Thus it appears that MIMO-OFDM will continue its dominance, at least for the next five years.

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In a MIMO system, the receiver must ..

Crux information of the processing of wireless systems is provided by channel parameters . There is to use various demodulations in OFDMA systems for obtaining channel information (). And these algorithms are invented to improve the capability of the system or sum rate (; ). The detection of MIMO-OFDMA signals demands channel estimation to mediate amplitude and phase in a fading channel (). It is very known that these LS, LMMSE and LMMSE-SVD algorithms are often adopted in channel estimation. The simplest algorithm is the LS algorithm, which can partition these received signals in the frequency domain (). The LMMSE channel estimator derives from the MMSE that exploits channel correlation and reduces intra/inter-cell interference in time and freque- ncy domain (). But the disadvantage of the estimator algorithm is that it needs some prior knowledge about the channel frequency correlation and the matrix inversion (). At the moment the paper also introduces a modified LMMSE algorithm using optimal rank reduction by SVD. But there has no too much investigation on the performance of the MIMO-OFDMA systems.

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MIMO-OFDM wireless communications with MATLAB [electronic ..