Abstract
In this paper, the performance of coded systems is considered in the presence of Suzuki fading channels, which is a combination of both short-fading and long-fading channels. The problem in manipulating a Suzuki fading model is the complicated integration involved in the evaluation of the Suzuki probability density function (PDF). In this paper, we calculated noise PDF after the zero-forcing equalizer (ZFE) at the receiver end with several approaches. In addition, we used the derived PDF to calculate the log-likelihood ratios (LLRs) for turbo-coded systems, and results were compared to Gaussian distribution-based LLRs. The results showed a 2 dB improvement in performance compared to traditional LLRs at 10 − 6 of the bit error rate (BER) with no added complexity. Simulations were obtained utilizing the Matlab program, and results showed good improvement in the performance of the turbo-coded system with the proposed LLRs compared to Gaussian-based LLRs.
Highlights
Rayleigh distribution has been widely used in wireless communication as an amplitude distribution for small-scale faded channels [1,2,3,4]
The noise probability density function (PDF) that are derived in Equations (13) and (14) are utilized to calculate the likelihood ratios (LLRs) equations for the coded system, such that b0 = loge p(w I |xI =1) p(w I |xI =−1)
Similar equations can be calculated for the 16-quadrature amplitude modulation (QAM) scheme with 4 LLR levels, such that signals xI and xQ take four values, and such that (−3, −1, +1, +3), with b0, b1, b2, b3 being the soft LLR for the coded system
Summary
Rayleigh distribution has been widely used in wireless communication as an amplitude distribution for small-scale faded channels [1,2,3,4]. Distribution for large-scale faded channels due to shadowing is represented by log-normal distribution [5,6]. Suzuki probability density function (PDF) was introduced in Reference [9] to undertake such a task. In Reference [10], outage probability was addressed for device-to-device (D2D) communications in the environment of Suzuki distribution. Due to the complexity in calculating integrals resulting from this distribution, two nonanalytic approximating approaches were used to derive closed forms for outage probability in the presence of additive white Gaussian noise (AWGN)
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