• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6A
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• pp.544-549
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• 2007

Carrier-to-noise and interference ratio (CNIR) measurement is important in providing accurate channel quality measurements for orthogonal frequency division multiplexing (OFDM) systems in different bit loading environments. Interference and noise power estimation for CNIR measurement nay be carried out either with known data or without any prior knowledge about the transmitted data. With prior knowledge on transmitted data, better estimation can be achieved. However, this results in huge increase in system load. As for estimation methods without any prior knowledge, poor system performance results under certain circumstances. In this paper, we investigate the effect due to different interference and noise power on decision-directed (DD) CNIR estimation for OFDM systems and propose a new CNIR estimation scheme that provides optimal trade off between the performance and system load.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.3
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• pp.6-12
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• 2011

The fast growing of the number of users requires the development of reliable communication systems able to provide higher data rates. In order to meet those requirements, techniques such as Multiple Input Multiple Out (MIMO) and Orthogonal Frequency Division multiplexing (OFDM) have been developed in the recent years. In order to combine the benefits of both techniques, the research activity is currently focused on MIMO-OFDM systems. In addition, for a fast wireless channel environment, the data rate and reliability can be optimized by setting the modulation and coding adaptively according to the channel conditions; and using sub-carrier frequency, and power allocation techniques. Depending on how accurate the feedback-based system obtain the channel state information (CSI) and feed it back to the transmitter without delay, the overall system performance would be poor or optimal. In this paper, we propose a Signal to Noise Ratio (SNR) estimation algorithm where the preamble is known for both sides of the transciever. Through simulations made over several channel environments, we prove that our proposed SNR estimation algorithm is more accurate compared with the traditional SNR estimation.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.4
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• pp.6-14
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• 2011

The fast growing of the number of users requires the development of reliable communication systems able to provide higher data rates. In order to meet those requirements, techniques such as Multiple Input Multiple Out (MIMO) and Orthogonal Frequency Division multiplexing (OFDM) have been developed in the recent years. In order to combine the benefits of both techniques, the research activity is currently focused on MIMO-OFDM systems. In addition, for a fast wireless channel environment, the data rate and reliability can be optimized by setting the modulation and coding adaptively according to the channel conditions; and using sub-carrier frequency, and power allocation techniques. Depending on how accurate the feedback-based system obtain the channel state information (CSI) and feed it back to the transmitter without delay, the overall system performance would be poor or optimal. In this paper, we propose a Signal to Noise Ratio (SNR) estimation algorithm where the preamble is known for both sides of the transciever. Through simulations made over several channel environments, we prove that our proposed SNR estimation algorithm is more accurate compared with the traditional SNR estimation. Also, We applied AMC on several channel environments using the parameters of IEEE 802.11n, and compared the Throughput performance when using each of the different SNR Estimation Algorithms. The results obtained in the simulation confirm that the proposed algorithm produces the highest Throughput performance.