In a cellular network, direct Device-to-Device (D2D) communication enhances Quality of Service (QoS) in terms of coverage, throughput and amount of power consumed. Since the D2D pairs involve cellular resources for communication, the chances of interference are high. D2D communications demand minimum interference along with maximum throughput and sum rate which can be achieved by employing optimal resources and efficient power allocation procedures. In this research, a hybrid optimization model called Genetic Algorithm-Adaptive Bat Optimization (GA-ABO) algorithm is proposed for efficient resource allocation in a cellular network with D2D communication. Simulation analysis demonstrates that the proposed model involves reduced interference with maximum sum rate and throughput. The performance of the proposed model is compared with the existing Ant Colony Optimization-based resource exchange and GAME (ACO-GAME) theory models, Trader-assisted Resource EXchange mechanism-Radio Access Network (TREX-RAN) and De-centralized Radio Access Network (TREX-DRAN), and greedy CYcle-Complete preferences (CYC) models. The proposed model offers a maximum sum rate of 83 kB/s, which is much better than the existing techniques.

Demand for data-oriented applications increases every day, which increases the data requirements. High-definition videos, virtual applications, etc., involve large volumes of data. To meet the data requirements, cellular service providers have introduced new technologies. However, owing to several applications and connections, the service providers face issues related to security, link and interference management, and resource allocation. The main advantage of 5G is its support for D2D communication that aids in managing traffic offloading [

The significant aspects which impact the D2D performance are broadly analyzed for identifying the research objective. Network architecture, standardization procedures, methods of identifying and selecting neighbors, resource allocation with power control, network spectral efficiency, coverage probability, relaying and security are taken into consideration (

Different modes of communication of D2D are considered. To support mmWave D2D proximity services, the architecture is modified to manage operations like discovering, establishing and maintaining links. Based on Long-Term Evolution (LTE) internetworking, the mmWave D2D networks cover a wide range of transmissions. Another important aspect of this network is identifying neighbors and choosing the most appropriate one for communication. This crucial process initially discovers all the neighbors and selects one based on the best link. Network-centric and device-centric schemes are popular approaches followed in D2D for neighbor discovery. In the case of network-centric approaches, the network is responsible for identifying the neighbor devices. In the case of device-centric neighbor discovery, the devices are accountable. In a denser environment, network-centric schemes perform better than device-centric ones. To reduce communication overhead as well as power consumption, neighbors should be rapidly discovered.

Once neighboring devices are discovered, and the best one is chosen for communication, resources are allocated and power control is effectively done. Since users in a D2D network use the same resources as cellular users, there are high chances for interference. Interference causes energy degradation and affects system efficiency. Hence, appropriate interference management schemes are required. Interference in D2D may be based on network and frequency. When it is based on frequency, it is subdivided into uplink and downlink interferences. In the case of network-based interference, it is divided into homogeneous interference and heterogeneous interference. Cancellation, avoidance and coordination are the major interference management factors. Interference is evaded by preventing cellular users from transmitting data in the D2D user range. In case of interference co-ordination, D2D and cellular user requirements are analyzed, and optimal resources are allocated without any interference. To support interference cancellation, successive and full duplex-based methods can be implemented. Only in-band D2D networks demand interference management schemes.

Traffic reduction at the BS and improved spectral efficiency with increased coverage probability are the other features of D2D. Poisson cluster process, stochastic geometry and probability theory are widely utilized to analyze the spectral efficiency and coverage probability [

A hybrid optimization algorithm for resource allocation in LTE-based D2D communication using the Genetic Algorithm-Adaptive Bat Optimization (GA-ABO) algorithm is proposed.

A simulation analysis of the proposed hybrid optimization model is presented with a detailed discussion.

A detailed analysis of the proposed and traditional resource allocation models is presented, and a comparative analysis is carried out to validate the better performances.

The remaining sections are organized as follows. A literature survey is presented in Section 2 which discusses the features of existing research works in D2D. The proposed hybrid optimization model is presented in Section 3. Section 4 presents the simulation analysis and results, whereas Section 5 summarizes the research work.

An extensive survey of existing D2D approaches is performed based on methodology and features. The primary aim of D2D communication is to reutilize the resources in cellular communication. It helps in improving spectrum management and avoids delay while servicing users. Resource allocation procedure in D2D is the foremost challenge regarding throughput and interference. The D2D resource allocation model presented in [

The dynamic resource block sharing model presented in [

The channel allocation problem in D2D communication reported in [

The D2D model presented in [

The joint optimization model presented in [

Full-duplex D2D resource allocation scheme presented in [

Admission control and resource allocation procedures for D2D communication are presented in [

The spectrum efficiency and capacity of 5G mobile networks are improved using D2D links. However, mm-wave resource allocation and interference management are complex processes. To overcome this, a heuristic algorithm that considers dynamic propagation conditions and provides optimal solutions to improve spectrum efficiency is presented in [

To enhance the sum rate, a weighted bipartite matching algorithm is proposed in [

From the literature review carried out, it is observed that interference management and resource sharing are the main goals to be addressed and are solved by using game theory. The optimization problems are solved using statistical and probability models, and nature-inspired optimization algorithms are not employed in any of the research. By considering this, a hybrid optimization algorithm is presented in this paper to improve the sum rate and throughput in D2D communication.

This section presents the proposed hybrid optimization for efficient resource allocation in a cellular network supporting D2D communication. A hybrid optimization model called Genetic Algorithm-Adaptive Bat Optimization (GA-ABO) algorithm is proposed to enhance the performance of D2D communication. In the proposed optimization algorithm, the system model is initially defined followed by detailed steps for resource allocation. Consider a single-cell dynamic system for analysis that has BS at the center. Users in the cell (

As resources are reused, interference management in D2D communication is considered as a significant factor which introduces interference between cellular and D2D pairs. If a D2D pair utilizes the cellular user resource, then the Signal to Interference and Noise Ratio (SINR) for cellular and D2D pairs is expressed as shown in

The data rate for cellular users when there is no interference in the D2D links is obtained based on the maximum power.

Throughput maximization and sum rate enhancement are the objectives with minimum QoS target for cellular users.

GA and ABO algorithms are incorporated in the proposed work for efficient resource allocation. GA is an iterative optimization procedure that is derived based on biological metaphors to obtain a new solution in the search space. It encodes the solution, which is similar to a data structure. A set of random solutions are initialized. By using a fitness function, the performance of every individual is evaluated. In every iteration, better solutions are chosen for the next generation, and new solutions are obtained by combining the parents by crossover or modifying the solutions through mutation. These solutions replace weaker solutions so that progressive development toward a better solution is possible. The main advantage of GA is the elimination of weaker candidates and the improvement of optimal solutions. In the conventional GA, the length of the chromosomes is fixed based on the number of D2D transmitters. But in the case of proposed approach, every chromosome handles a dynamic subcarrier. The collection of chromosomes is termed as individuals, and the chromosomes denote subcarriers. An orthogonal resource allocation procedure is employed for cellular users, wherein the number of users and subcarriers are equal.

Evaluation of fitness function in GA is essential as it defines how close the obtained solution is to the optimal solution. The fitness value minimizes the data rate for the D2D transmitter. The fitness function is formulated as follows

ABO algorithm is used in enhancing the genetic model’s optimal solution. The ABO model optimizes ‘

Hybrid optimization algorithm for D2D network resource allocation is evaluated through simulation analysis performed using Network simulator NS-3.

Parameter | Value |
---|---|

Number of cellular users | 40 |

Number of D2D pairs | 40 |

Channel bandwidth | 10 Mhz |

Network size | 1000 m × 1000 m |

Maximum transmission powers | 23 dBm |

Base station coverage range | 500 m |

D2D transmitter’s coverage range | 10–50 m |

Mutation rate | 0.04 |

Population size | 50 |

Crossover rate | 0.3 |

Total iterations | 500 |

Noise power density | −110 dBm/Hz |

Similarly, the average interference is analyzed based on the total number of resource blocks. The total Resource Block Groups (RBGs) are dynamically varied, and the interference of D2D pairs is measured (

In addition to average interference, the sum rate of the proposed model and existing models are compared and analyzed based on the total number of users and D2D pairs.

Similarly, the sum rate for the proposed model and existing models are compared and analyzed for D2D pairs.

From the simulation analysis, it is evident that the hybrid optimization algorithm offers improved resource allocation. The results demonstrate better performance of the proposed model in terms of maximum sum rate and minimum interference. The model can be used in real-time LTE applications.

A hybrid optimization model D2D communication is presented in this research work using the Genetic Algorithm-Adaptive Bat Optimization (GA-ABO) algorithm. Resource exchange mechanism plays a dominant role in ensuring the consistency of D2D pairs in D2D communication, as cellular user’s resources are used for direct communication. The existing approaches presented for D2D communication focus on resource allocation through a simple statistical process. However, the performance is improved by incorporating optimization algorithms into the resource allocation process. Based on this, the proposed hybrid optimization algorithm improves the sum rate and throughput, and minimizes the interference level. The results obtained through simulation analysis of the proposed model are compared with existing models based on average interference, throughput and sum rate. For a maximum sum rate of 94 kB/s, the proposed model exhibits better performance than the existing approaches. Further, it is planned to extend this research by incorporating deep learning techniques for better performance.

The authors received no specific funding for this study.

The authors declare that they have no conflicts of interest to report regarding the present study.