Abstract This study presents an innovative fractional order Rayleigh fading model that can be used for channel capacity estimation in the presence of additive white generalized Gaussian noise. The proposed model assumes that the real and imaginary parts of channel gains are generalized Gaussian random variables, which makes it possible to consider the traditional Rayleigh fading model as a special case of fractional order Rayleigh fading. Compared to the Rayleigh model, the fractional order Rayleigh fading model offers a more precise representation of new real‐world communication, such as integrating terrestrial and underwater networks in sixth‐generation communications channels. The probability density function of the channel gain with additive white generalized Gaussian noise is analyzed here. Furthermore, the ergodic and outage capacities of the channel are determined, taking into account the assumption that the channel state information is only available at the receiver. The ergodic capacity is calculated using Meijer's G‐functions, resulting in a closed‐form expression. Numerical simulations demonstrate the superiority of the fractional order Rayleigh fading model over the Rayleigh channel. Moreover, the impact of ergodic and outage capacities under diverse channel characteristics is assessed.

In this paper, a novel framework for dynamic multiple access technology selection among orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) techniques is proposed. For this setup, a joint resource allocation problem is formulated in which a new set of access technology selection parameters along with power and subcarrier are allocated for each user based on each user's channel state information. Here, a novel utility function is defined to take into account the rate and costs of access technologies. This cost reflects both the complexity of performing successive interference cancellation and the complexity incurred to guarantee a desired bit error rate. This utility function can inherently capture the tradeoff between OMA and NOMA. Due to the non-convexity of the proposed resource allocation problem, a successive convex approximation is developed in which a two-step iterative algorithm is applied. In the first step, called access technology selection, the problem is transformed into a linear integer programming problem, and then, in the second step, a nonconvex problem, referred to power allocation problem, is solved via the difference-of-convex-functions (DC) programming. Moreover, the closed-form solution for power allocation in the second step is derived. For diverse network performance criteria such as rate, simulation results show that the proposed new dynamic access technology selection outperforms single-technology OMA or NOMA multiple access solutions.

In this study, the physical layer resource allocation in orthogonal frequency‐division multiple access (OFDMA) systems is studied by considering the non‐linear effects of power amplifier (PA). The non‐linearity produces cross‐correlation among the subcarriers and results in deteriorating the OFDMA subcarriers orthogonality. Hence, the signal‐to‐interference ratio (SIR) of the output signal of PA for OFDMA signal with different power scaling factors for subcarriers is derived. Then, the theoretical SIR is verified by simulation result. Next, the optimisation problem is designed to maximise the total achievable downlink rate of all users by assigning subcarriers and power scaling factors. This non‐convex problem is solved by comprehensive learning particle swarm optimisation. The simulation results show that when PA is non‐linear, better total rate is achieved by considering non‐linearity in resource allocation compared with the conventional resource allocation techniques.

This study concerns two‐hop transmission over relay‐assisted block fading channels, assuming there is no direct link between transmission ends and the communication is carried out through using a relay. It is assumed that the channel gains from source‐to‐relay and relay‐to‐destination are known at the relay, while the source is unaware of channel gains. In this case, it is demonstrated that the best signalling method is using a multi‐layer code at the first hop, while using a single‐layer code at the second hop. Accordingly, the decode‐and‐forward (DF) and amplify‐and‐forward (AF) strategies at the relay are investigated, where for DF strategy under two special cases of peak power and average power constraints, the optimal power allocation policy across coding blocks are devised. Moreover, for AF strategy the optimal weight function maximising the average signal‐to‐noise ratio at the destination is derived. The simulation results for Rayleigh fading environment demonstrate the superiority of DF over AF in terms of the average achievable rate. More specifically, it is demonstrated that the broadcast approach in DF strategy under average power constraint closely follows the so‐called broadcast cutset upper bound, thereby providing favourable results in such network.

The nonlinear behavior of power amplifier (PA) in orthogonal frequency-division multiplexing (OFDM)-based cognitive radio (CR) system introduces in-band and adjacent channel interferences. The power in the adjacent channels is an important issue in the CR because it can act as interference to primary users. In this paper, we derive a closed-form expression for the leakage power at adjacent channels when CR devices use OFDM modulation. Moreover, the PA nonlinearity creates in-band distortion that produces intercarrier interference and reduces the secondary system capacity. To control this effect, we derive the optimum power scaling factor for the input signal that maximizes the secondary user rate. The optimization process is executed by considering nonlinear effects on signal-to-interference-and-noise ratio under the constraints of the powers in the adjacent channels. The power in the adjacent channels should not exceed the interference temperature limit. The analytical results are verified by simulation studies.