Heterogeneous Networks (HetNETs) are considered as an effective solution to improve the coverage and system throughput for future cellular networks. The extremely growing mobile market, together with the arising demand for high data rates, motivate us to open a new spectrum related to millimeter waves (mmwaves) while using beamforming that can serve simultaneously a group of users. In this paper, we formulate an optimization problem for HetNETs multi-user selection in a multi-input-multi-output and orthogonal frequency-division multiple access (MIMO-OFDMA) system, aiming to maximize the total system throughput. We solve the problem by applying a modified version of well-known metaheuristic algorithms. The optimal solution is obtained using an exhaustive search algorithm that provides an ideal solution which is complex to be computed. Greedy zero-forcing dirty-paper gZF-DP and zeroforcing selection ZFS algorithms were selected from literature for the sub-optimal solution. In parallel, a water-filling algorithm has been optimized after adding new power constraint and it has been used for power distribution. Hence, we analyze the throughput performance of our systems using throughput metric. The results show that ZFS outperforms gZF-DP algorithm as it achieves higher total throughput, While gZF-DP outperforms ZFS algorithm in the execution time.
One of the most important issues in the efficient use of radio resource spectrum for multiuser multiple-input/multipleoutput (MU-MIMO) systems is the selection of users to achieve the maximum system throughput. The optimal user device selection algorithm, which requires exhaustive search, is prohibitive due to its high computational complexity. Moreover, fairness among the users cannot generally be achieved with such a scheme. Therefore, we propose to use Jain's fairness index to assure that each user can achieve a required data rate, as in a system with quality of service guarantees. In this paper, we formulate an optimization problem for user selection based on angle-of-arrival (AoA), in a HetNET multiuser aiming to jointly maximize the total system throughput and the spectrum efficiency, notably, using a well-known beamforming technique to eliminate interusers interference. Through computational complexity analysis, the proposed algorithms frequency allocation angular based with fairness FAABF-algorithm and frequency allocation angular based without fairness FAAB-algorithm, that are considered as the best solution for the formulated optimization problem, Indeed, they provide a low complexity. Simulation results validate that the proposed algorithm achieves almost the same system throughput than a capacity-based algorithm under a high SNR regime with a considerable reduction in complexity. Index Terms-Multiuser multiple input multiple output (MU-MIMO), user selection, Jain's fairness, 5G heterogeneous network, beamforming, angle-of-arrival (AOA)
Lack of coordination between network layers limits the performance of most proposed solution for new challenges posed by wireless networks. To overcome such limitations, cross-layer physical and medium access (PHY-MAC) design for multi-input-multi-output orthogonal frequency division multiple access system in heterogeneous networks (HetNETs) is proposed. In this paper, we formulate an optimization problem for hybrid beamforming, in a multiuser HetNET scenario aiming to maximize the total system throughput. Furthermore, analog beamforming is selected from a codebook containing a limited number of candidates for steering vectors. The proposed problem is non-convex and hard to solve. Thus it is relaxed by transforming it into a subtraction form of two convex funcions. Afterward we apply a group of well-known metaheuristic algorithms to calculate the normalized hybrid beamforming vectors. The optimal solution is obtained using an exhaustive search (ES) algorithm that provides an ideal solution, but with high complexity. In addition, zero-forcing-based approach (ZFA), matched filter (MF), and QR-based approach (QR) are applied to get quick sub-optimal solutions. Hence, we analyze the performance of our systems using the throughput metric. The simulation results show that QR algorithm outperforms ZFA and MF in low and middle signal-tonoise ratio (SNR) regime, while ZFA outperforms QR and MF at higher SNRs. Moreover, QR is close to the optimal solution ES.
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