Discrete bit-loading for OFDM systems under BER-constraint and imperfect CSI

In this paper, a low complexity discrete bit loading is proposed for OFDM systems over a fading channel and imperfect channel state information (CSI). The available CSI at the transmitter can be partially known due to imperfection in channel estimation, interferences or the Doppler spread. These imp...

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Vydáno v:International journal of electronics letters Ročník 10; číslo 3; s. 283 - 295
Hlavní autoři: Ait Saadi, Hocine, Dahmani, Samir, Maamoun, Mountassar
Médium: Journal Article
Jazyk:angličtina
Vydáno: Abingdon Taylor & Francis 03.07.2022
Taylor & Francis Ltd
Témata:
Algorithms
Bit error rate
bit-loading
Complexity
constellation
CSI
Defects
fading channel
Iterative methods
OFDM
Subcarriers
ISSN:2168-1724, 2168-1732
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Shrnutí:In this paper, a low complexity discrete bit loading is proposed for OFDM systems over a fading channel and imperfect channel state information (CSI). The available CSI at the transmitter can be partially known due to imperfection in channel estimation, interferences or the Doppler spread. These imperfections increase the bit error rate (BER) for each subchannel. Uniform power allocation and finite granularity for constellation size are used to maximise spectral efficiency subject to a target average BER. The proposed bit loading algorithm, starts by loading all the subcarriers with an initial bit vector obtained using the available CSI and under constraint of the target BER and the maximum number of bits allowed. Then, we introduce the errors on the CSI in the new formula of the average BER calculated initially by using all the subcarriers indexes of the initial bit vector. Iteratively, only the subcarriers, which violate the constraint on the average BER, are used for the updating; they are unloaded until reaching the final bit vector. Therefore, the set of concerned sub-carriers decreases after each iteration, this results in a significant reduction in the computational complexity.
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ISSN:2168-1724
2168-1732
DOI:10.1080/21681724.2021.1908610