In current cellular systems, the performance of active users' devices at the cell edge suffers from the poor link quality. However, these connections also requires more resource blocks and transmission power. In order to reduce the number of resource blocks and transmission power, this paper discusses device to device communication in downlink and Uplink cases of cellular communication systems. In order to optimize the connections of different network users, which means finding the best user’ s connection to a base station (minimum power consumption), which may be established through communication with other users or direct connection with the base station, and to minimize the total transmission power, different optimization methods such as gravitational search optimization, particle swarm optimization, genetic optimization algorithm and distributed strategy based on Q learning and softmax decision making methods are used. The numerical results show a power reduction of around 30 percent for these distributed communications with less computational complexity using the Q learning method compared to the case in which all users traditionally connect through the base station in a centralized way with high computational complexity.

In massive Multiple Input Multiple Output (MIMO) or large scale MIMO systems, Uplink detection at the Base Station (BS) is a challenging problem due to significant increase of the dimensions in comparison to ordinary MIMO systems. In this letter, a novel iterative method is proposed for detection of the transmitted symbols in Uplink multiuser massive MIMO systems. Linear detection algorithms such as minimum-mean-square-error (MMSE) and zero-forcing (ZF), are able to achieve the performance of the near optimal detector, when the number of base station (BS) antennas is enough high. But the complexity of linear detectors in Massive MIMO systems is high due to the necessity of the calculation of the inverse of a large dimension matrix. In this paper, we address the problem of reducing the complexity of the MMSE detector for massive MIMO systems. The proposed method is based on Gram Schmidt algorithm, which improves the convergence speed and also provides better error rate than the alternative methods. It will be shown that the complexity order is reduced from to, where is the number of users. The proposed method avoids the direct computation of matrix inversion. Simulation results show that the proposed method improves the convergence speed and also it achieves the performance of MMSE detector with considerable lower computational complexity.

Massive multiple-input multiple-output is a promising technology in future communication networks where a large number of antennas are used. It provides huge advantages to the future communication systems in data rate, the quality of services, energy efficiency, and spectral efficiency. Linear detection algorithms can achieve a near-optimal performance in large-scale MIMO systems, due to the asymptotic orthogonal channel property. But, the performance of linear MIMO detectors degrades when the number of transmit antennas is close to the number of receive antennas (loaded scenario). Therefore, this paper proposes a series of detectors for large MIMO systems, which is capable of achieving promising performance in loaded scenarios. The main idea is to improve the performance of the detector by finding the hidden sparsity in the residual error of the received signal. At the first step, the conventional MIMO model is converted into the sparse model via the symbol error vector obtained from a linear detector. With the aid of the compressive sensing methods, the incorrectly detected symbols are recovered and performance improvement in the detector output is obtained. Different sparse recovery algorithms have been considered to reconstruct the sparse error signal. This study reveals that error recovery by imposing sparse constraint would decrease the bit error rate of the MIMO detector. Simulation results show that the iteratively reweighted least squares method achieves the best performance among other sparse recovery methods.

Performance improvement of Uplink of analog wireless communication systems employing spatial diversity Signal attenuation is one of the most important problems in wireless communication systems. The message conveyed by the transmitted waveform will not be recovered correctly if this attenuation is such that the SNR in the receiver is less than a specific threshold. Channel fading which results from receiving many non-coherent reflected versions of transmitted signal in the receiver, is one of the sources of this signal degradation. Fading may result in severe changes in the strength of the received signal in short time intervals. Diversity techniques are the most powerful tools to combat degrading effects of wireless fading, by using two or more independent communication channels. Diversity techniques are mainly designed for digital communications, therefore employing them in analog systems such as FM radios is a challenging issue. In this study, spatial diversity in receiver is proposed in order to making the current VHF wireless systems smart against channel fading. Based on this idea, three different applicable methods have been proposed for traditional analog FM repeating systems which can be implemented with little changes in the current hardware system. Simulation results show the improvement in reliability and performance of the systems using these methods.

One proposed approach in fifth-generation wireless communication to support more users is the dynamic use of orthogonal and non-orthogonal multiple access schemes. In this research, a dynamic orthogonal and non-orthogonal multiple access system is proposed to maximize the energy efficiency (EE), and several schemes are presented for allocation of sub-channels and power. Due to the complexity of the proposed resource allocation problem and its non-convexity property, it is not possible to find a global solution. Hence, the main problem is divided into two sub-problems which are sub-channels and power allocation. In the first step, the subchannel allocation problem is solved and its output is sub-channel allocation for all active users and determining the access mode for each sub-carrier. The second step is the power allocation sub-problem which is converted into a quasi-convex sub-problem by using the difference of convex functions algorithm iteratively, and ultimately. Then, the bisection method is applied for solving the quasiconvex sub-problem. Also, the KKT equations are provided for the feasibility problem of the bisection method. Finally, in the simulation section, the maximum EE versus the maximum power for each user is calculated. Besides, the impact of user’ s presence at the cell edge on the EE is discussed. According to the simulation results, our proposed resource allocation approach can improve the sum rate and EE of the system compared to the heuristic approach of the previous literature.

The non-orthogonal access schemes are one of the multiple access techniques that are candidates to become an access technique for the next generation access radio. Power-domain non-orthogonal multiple-access (NOMA) is among these promising technologies. Improving the network capacity by providing massive connectivity through sharing the same spectral resources is the main advantage that this technique offers. The NOMA technique consists of exploiting the power domain which multiplex multiple users on the same resources applying a superposition coding then separating the multiplexed users at the receiver side. Due to the non-orthogonality access technique, the main disadvantage of NOMA is the presence of interferences between users. That is why this scheme is based on a successive interference cancelation (SIC) detector that separates the multiplexed signals at the receiver. In this paper, an embedded system is considered for designing and implementation of the power-NOMA For two users. The implementation is realized by employing a Zynq FPGA (Field programmable gate array) device through the Zybo-Z7 board using MATLAB/Simulink environment and Xilinx System Generator. The features offered by this device, hemps to consider the design of an Uplink and a downlink scenario over Rayleigh fading channel in additive white Gaussian noise (AWGN) environment

In this paper we investigate the sub-channel assignment and power control to maximize the total sum rate in the Uplink of two-cell network. It is assumed that there are some sub-channels in each cell which should be allocated among some users. Also, each user is subjected to a power constraint. The underlying problem is a nonconvex mixed integer non-linear optimization problem which does not have a trivial solution. To solve the problem, having fixed the consumed power of each user, and assuming low co-channel interference region, the sub-channel allocation problem is reformulated into a more mathematically tractable problem which is shown it can be tackled through the so-called Hungarian algorithm. Then, the consumed power of each user is reformulated as a quadratic fractional problem which can be numerically derived. Numerical results demonstrate the superiority of the proposed method in low SNR region as compared to existing works addressed in the literature.

With the rapid deployment of users and increasing demands for mobile data, communication networks with high capacity are needed more than ever. Furthermore, there are several challenges, such as providing efficient coverage and reducing power consumption. To tackle these challenges, using unmanned aerial vehicles (UAVs) would be a good choice. This paper proposes a scheme for Uplink non-orthogonal multiple access (NOMA) in UAV communication systems in the presence of granted and grant-free users. At first, the service area users, including granted and grant-free users, are partitioned into some clusters. We propose that the hover location for each cluster is determined considering the weighted mean of users’,locations. We aim to allocate transmission power and form NOMA pairs to maximize the energy efficiency in each cluster subject to the constraints on spectral efficiency and total transmission power. To this end, the transmission powers of each possible pair are obtained, and then Hungarian matching is used to select the best pairs. Finally, finding the flight path of the UAV is modeled by the traveling salesman problem (TSP), and the genetic algorithm method obtains its solution. The results show that the increasing height of the UAV and density of users increases the spectral and energy efficiencies and reduces the outage probability. Also, considering the quality of service (QoS) of granted users for determining the UAV's hover location enhances the transmission's performance.

In this paper, a distributed pilot-based power control algorithm is proposed that controls the transmitted power of each user in the Uplink direction base on pilot’ s measurement in the downlink direction to address the SINR balancing and antennas selection in a multi-user massive MIMO system. In the proposed algorithm, each user chooses a set of antennas of all BSs as their home group antennas and based on their received pilot power, adjust their transmitting power by solving a polynomial equation. The algorithm is performed recursively and after several repetitions, the SINR values of all users converge to the same value in their home group antennas. The simulation results illustrate the improvement in energy efficiency by choosing proper antennas selection and power adjustment.

Decoupling the Uplink and downlink user association improves the throughput of heterogeneous networks (HetNets) and balances the traffic load of macro-and small-base stations. Recently, fiber-wireless HetNets (FiWi-HetNets) have been considered as viable solutions for access networks. To improve the accuracy of user association and resource allocation algorithms in FiWi-HetNets, the capacity limitation of various backhaul technologies must be considered. In this paper, we investigate the backhaul-aware decoupled Uplink/downlink (UL/DL) user association, subcarrier allocation, and power control optimization problem in FiWi-HetNets. In our system model, fiber and millimeter wave (mmWave) links are used as backhaul of base stations, and the backhaul capacity limitation and minimum required transmission rate (R_min) are modeled in the optimization problem. As the formulated optimization problem is non-convex, we present a heuristic algorithm to divide the main problem into two sub-problems that are solved iteratively. The proposed algorithms are evaluated through exhaustive simulations. The results indicate that decoupling UL/DL user association improves the sum rate of FiWi-HetNets. Besides, we evaluate the effect of backhaul capacity limitation and R_min on the sum rate of FiWi-HetNets. The effect of upgrading fiber backhaul technology is also investigated to evaluate the role of fiber backhaul on the sum rate of the radio access network.