Using Genetic Algorithm with frequency hopping in device to device communication (D2DC) interference mitigation

Lee, Yang-Han; Lo, Chi‐Wen; Chin, Le-Pong; Hsu, Heng-Iang; Tseng, Hsien‐Wei; Jan, Yih-Guang; Song, Ting-Chen

doi:10.1109/ispacs.2012.6473480

Cited by 13 publications

(3 citation statements)

References 9 publications

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“…For instance, K-Means algorithm was adopted by [12] using the interference value as the input data and criterion to cluster the UEs. A combination of K-Means algorithm and Genetic Algorithm (GA) was proposed by [13]. LEACH and the variants were utilized and have been also adopted in literatures [14,15].…”

Section: Literature Review Of Related Workmentioning

confidence: 99%

Cluster formation in device-to-device (D2D) communications to ensure quality of service & minimize cluster head power consumptions

Ezeh,

Ezenugu,

Okorogu

et al. 2024

Preprint

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The research proposed a clustering formation approach that ensures that the chosen cluster head (CH) in D2D communication consumes minimal energy and that the cluster members (CMs) are offered good quality of service. In addition, the study investigated various factors influencing power consumptions of User Equipment (UE) in Device to Device (D2D) Communication. Network and geographic data of the UE were collected within 200m diameter (100m radius) around the chosen base station (BS). A term Hardware Sensing Factor (a weighting factor) was formulated from the collected network data. The HSF and the distance between the UE and the base station were utilized as input data to Self Organizing Map (SOM), an unsupervised machine learning algorithm, to form clusters of the UE. A UE with highest value of HSF and minimal distance to the BS is chosen as the Cluster Head (CH) for each cluster. It was shown that the power consumption of the UE increases as the signal attenuation (which depends on distance) increases. In addition, for every transmission/reception between the Cluster Member (CM) and the BS through the CH, the CH consumes about 2.5% more than the CM. Also, in addition to the effects of signal attenuation, the power consumption of the CH is largely dependent on the number of CMs associated with the CH. Furthermore, it is more energy efficient for the CMs to communicate with the CH than communicate with the BS, especially for edge cell UE.

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Section: Literature Review Of Related Workmentioning

confidence: 99%

Cluster formation in device-to-device (D2D) communications to ensure quality of service & minimize cluster head power consumptions

Ezeh,

Ezenugu,

Okorogu

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Besides, source allocation is another research hotspot in D2D communication. In [5], a fair resource allocation problem for D2D communications was studied in orthogonal frequency division multiple access-(OFDMA-) based wireless cellular networks. In [6], a genetic algorithm (GA) with frequency hopping technique was proposed to optimally select the number of frequency channels required in the system and then allocate these frequency channels to the UE clusters for D2D communication.…”

Section: Introductionmentioning

confidence: 99%

Balancing Long Lifetime and Satisfying Fairness in WBAN Using a Constrained Markov Decision Process

Yin

Cen

et al. 2015

International Journal of Antennas and Propagation

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As an important part of the Internet of Things (IOT) and the special case of device-to-device (D2D) communication, wireless body area network (WBAN) gradually becomes the focus of attention. Since WBAN is a body-centered network, the energy of sensor nodes is strictly restrained since they are supplied by battery with limited power. In each data collection, only one sensor node is scheduled to transmit its measurements directly to the access point (AP) through the fading channel. We formulate the problem of dynamically choosing which sensor should communicate with the AP to maximize network lifetime under the constraint of fairness as a constrained markov decision process (CMDP). The optimal lifetime and optimal policy are obtained by Bellman equation in dynamic programming. The proposed algorithm defines the limiting performance in WBAN lifetime under different degrees of fairness constraints. Due to the defect of large implementation overhead in acquiring global channel state information (CSI), we put forward a distributed scheduling algorithm that adopts local CSI, which saves the network overhead and simplifies the algorithm. It was demonstrated via simulation that this scheduling algorithm can allocate time slot reasonably under different channel conditions to balance the performances of network lifetime and fairness.

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“…An interference mitigation scheme based on greedy coloring was lately designed in [9], according to the derived neighbor distance, to mitigate the interference among the D2D pairs with a guaranteed QoS. In [10], the authors devised a novel scheme by using the K-Means method to group the UEs into clusters and then optimized the frequency-hopping based interference mitigation scheme with a genetic algorithm.…”

mentioning

confidence: 99%

Interference mitigation scheme by antenna selection in device-to-device communication underlaying cellular networks

Wang

Jin

et al. 2016

J. Commun. Netw.

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In this paper, we investigate an interference mitigation scheme by antenna selection in device-todevice (D2D) communication underlaying downlink cellular networks. We first present the closed-form expression of the system achievable rate and its asymptotic behaviors at high signal-to-noise ratio (SNR) and the large antenna number scenarios. It is shown that the high SNR approximation increases with more antennas and higher ratio between the transmit SNR at the BS and the D2D transmitter. In addition, a tight approximation is derived for the rate and we reveal two thresholds for both the distance of the D2D link and the transmit SNR at the BS above which the underlaid D2D communication will degrade the system rate. We then particularize on the small cell setting where all users are closely located. In the small cell scenario, we show that the relationship between the distance of the D2D transmitting link and that of the D2D interfering link to the cellular user determines whether the D2D communication can enhance the system achievable rate. Numerical results are provided to verify these results.

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Using Genetic Algorithm with frequency hopping in device to device communication (D2DC) interference mitigation

Cited by 13 publications

References 9 publications

Cluster formation in device-to-device (D2D) communications to ensure quality of service & minimize cluster head power consumptions

Cluster formation in device-to-device (D2D) communications to ensure quality of service & minimize cluster head power consumptions

Balancing Long Lifetime and Satisfying Fairness in WBAN Using a Constrained Markov Decision Process

Interference mitigation scheme by antenna selection in device-to-device communication underlaying cellular networks

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Using Genetic Algorithm with frequency hopping in device to device communication (D2DC) interference mitigation

Cited by 13 publications

References 9 publications

Cluster formation in device-to-device (D2D) communications to ensure quality of service &amp; minimize cluster head power consumptions

Cluster formation in device-to-device (D2D) communications to ensure quality of service &amp; minimize cluster head power consumptions

Balancing Long Lifetime and Satisfying Fairness in WBAN Using a Constrained Markov Decision Process

Interference mitigation scheme by antenna selection in device-to-device communication underlaying cellular networks

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Product

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Cluster formation in device-to-device (D2D) communications to ensure quality of service & minimize cluster head power consumptions

Cluster formation in device-to-device (D2D) communications to ensure quality of service & minimize cluster head power consumptions