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Manufar Rarraba Makamashi Mai Sabuntawa Dangane da Amfani don Cibiyoyin Sadarwa Masu Tsabta

Bincike kan sabuwar manufar rarraba makamashi don cibiyoyin sadarwa masu amfani da makamashi mai sabuntawa, tare da mai da hankali kan ingancin sabis (QoS), ingancin tashoshi, da haɓaka amfanin mai amfani.
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Tsarin Abubuwan Ciki

1. Gabatarwa

Girma mai ƙarfi a cikin buƙatun bayanan mara waya ya haifar da ƙaruwa mai mahimmanci a cikin amfani da makamashi da hayaƙin carbon daga cibiyoyin sadarwa. Wannan takarda tana magance ƙalubalen samar da waɗannan cibiyoyin sadarwa da hanyoyin samar da makamashi mai sabuntawa (misali, hasken rana, iska), waɗanda ke da canji kuma ba su da daidaituwa. Matsala ta asali ita ce rarraba ƙayyadadden adadin makamashin da aka tara mai sabuntawa tsakanin masu amfani a cikin cibiyar sadarwa ta OFDMA (Orthogonal Frequency Division Multiple Access). Manufar da aka tsara ta haɗa mahimman abubuwa guda uku na musamman: jimillar makamashin mai sabuntawa da ake da shi, buƙatun Ingancin Sabis (QoS) na kowane mai amfani, da ingancin tashoshi na ainihi. Manufar ita ce haɓaka aikin amfani na duka cibiyar sadarwa, wanda ke ƙididdige gamsuwar mai amfani, bisa ga ƙayyadaddun makamashi. Wannan aikin ya tsara kansa a cikin tsarin "sadarwa mai tsabta", yana motsawa fiye da ingantaccen amfani da makamashi kawai zuwa sarrafa albarkatu mai hikima don dorewa.

2. Tsarin Tsarin da Tsara Matsala

2.1 Tsarin Cibiyar Sadarwa da Makamashi

Muna la'akari da cibiyar sadarwa ta OFDMA mai tantanin halitta ɗaya tare da tashar tushe (BS) guda ɗaya da ke samun makamashi daga tushen makamashi gauraye: tsohuwar hanyar watsa wutar lantarki da mai tara makamashi mai sabuntawa a wurin (misali, fale-falen hasken rana). Tashar tushe tana hidima ga masu amfani K. Makamashin mai sabuntawa yana zuwa lokaci-lokaci kuma ana adana shi a cikin baturi mai iyaka. Makamashin mai sabuntawa da ake da shi don rarrabawa a cikin wani lokaci na musamman ana nuna shi da $E_{total}$. Ribar tashar (channel gain) don mai amfani $k$ ita ce $h_k$, wacce ke canzawa lokaci.

2.2 Aikin Amfani da QoS

Tushen manufar shine aikin amfani $U_k(e_k)$, wanda ke nuna adadin makamashin mai sabuntawa $e_k$ da aka ware wa mai amfani $k$ zuwa ma'aunin gamsuwar wannan mai amfani. An tsara wannan aikin don nuna buƙatar QoS na mai amfani. Misali, mai amfani mai saurin jinkiri (misali, yawo bidiyo) na iya samun haɓakar amfani mai tsauri wanda ke cika da sauri, yayin da mai amfani na ƙoƙari mafi kyau (misali, zazzage fayil) na iya samun amfani mafi layi. Jimillar amfanin cibiyar sadarwa ita ce $U_{sum} = \sum_{k=1}^{K} U_k(e_k)$.

2.3 Matsalar Haɓakawa

An tsara matsalar rarraba makamashi a matsayin matsala ta haɓakawa mai ƙayyadaddun iyaka: $$\max_{\{e_k\}} \sum_{k=1}^{K} U_k(e_k)$$ Bisa ga: $$\sum_{k=1}^{K} e_k \leq E_{total}$$ $$e_k \geq 0, \quad \forall k \in \{1,...,K\}$$ $$R_k(e_k, h_k) \geq R_{k}^{min}, \quad \forall k$$ inda $R_k$ shine yawan bayanai da mai amfani $k$ zai iya samu (aikin makamashin da aka ware $e_k$ da ribar tashar $h_k$), kuma $R_{k}^{min}$ shine mafi ƙarancin yawan bayanai da ake buƙata don cika QoS.

3. Algorithm na Rarraba Makamashi da aka Tsara

3.1 Ƙirar Algorithm na Heuristic

Idan aka yi la'akari da yanayin matsalar da ba ta da ma'ana da haɗuwa (musamman tare da rarraba subcarrier mai rarrabuwa a cikin OFDMA), marubutan sun ba da shawarar algorithm na heuristic mai sauƙi. Algorithm ​​tana aiki kamar yadda mai son son rai:

  1. Fifita Mai Amfani: Ana sanya masu amfani matsayi bisa ga ma'auni gauraye wanda ya haɗa ingancin tashar su ($h_k$) da ribar amfani na gefe a kowace raka'a makamashi ($\Delta U_k / \Delta e_k$).
  2. Rarraba Maimaitawa: An fara da mai amfani mafi fifiko, ana rarraba makamashi a matakai masu rarrabuwa har sai ribar amfaninsu ta ragu ko QoS ɗinsu ya gamsu.
  3. Binciken Ƙayyadaddun Iyaka: Bayan kowane rarrabawa, ana duba ƙayyadaddun jimillar makamashi $E_{total}$. Idan makamashi ya rage, ana ci gaba da aikin tare da mai amfani na gaba.
  4. Ƙarewa: Algorithm ​​tana tsayawa lokacin da $E_{total}$ ya ƙare ko kuma an yi hidima ga duk masu amfani.
Wannan hanyar tana tabbatar da cewa a ƙarƙashin yanayin makamashi mara kyau, masu amfani masu kyakkyawan yanayin tashar (ingantaccen amfani da makamashi) ana yi musu hidima da farko don haɓaka jimillar amfani.

3.2 Sarƙaƙiyar Algorithm

Sarƙaƙiyar algorithm ​​itacce $O(K \log K)$ saboda farkon rarraba masu amfani K, sannan a bi ta hanyar rarrabawar layi. Wannan yana sa ya zama mai girman girma kuma ya dace da aiwatarwa na ainihi a cikin masu sarrafa cibiyar sadarwa, sabanin mafita masu sarƙaƙi na shirye-shiryen motsa jiki ko haɓakawa da aka ba da shawara a cikin ayyukan da ke da alaƙa kamar [8].

4. Sakamakon Lambobi da Kimanta Ayyuka

4.1 Saitin Siminti

Ana kimanta aikin ta hanyar siminti. Mahimman ma'auni sun haɗa da: radius na tantanin halitta na 500m, masu amfani 20-50 da aka rarraba bazuwar, tashoshi masu lalacewa na Rayleigh, da matakan daban-daban na jimillar makamashin mai sabuntawa $E_{total}$. An ayyana ayyukan amfani a matsayin sigmoidal don zirga-zirgar ainihi da logarithmic don zirga-zirgar ƙoƙari mafi kyau, suna daidaitawa da samfuran da ake amfani da su a cikin tattalin arzikin cibiyoyin sadarwa.

4.2 Binciken Sakamako

Sakamakon ya nuna halaye biyu masu mahimmanci:

  1. Tsarin Makamashi Maras Kyau: Lokacin da $E_{total}$ ya yi ƙasa sosai, algorithm ​​yana rarraba makamashi kusan ga masu amfani masu mafi kyawun ribar tashar kawai. Wannan yana sadaukar da adalci amma yana haɓaka jimillar amfani da ingancin cibiyar sadarwa, kamar yadda yin hidima ga masu amfani masu tashoshi marasa kyau zai ɓata makamashi mai daraja.
  2. Tsarin Makamashi Mai Isasshe: Yayin da $E_{total}$ ya karu, algorithm ​​ya fara gamsar da buƙatun QoS na ƙarin masu amfani, gami da waɗanda ke da ingancin tashar matsakaici. Jimillar amfani yana ƙaruwa kuma yana cika da zarar an cika ainihin buƙatun QoS na duk masu amfani.
An nuna cewa manufar da aka tsara ta fi tsarin rarraba makamashi daidai daidai sosai dangane da jimillar amfani, musamman a cikin yanayi na ƙarancin makamashi. Babban ginshiƙi zai zana Jimillar Amfanin Cibiyar Sadarwa vs. Jimillar Makamashin Mai Sabuntawa da Ake da Shi, yana kwatanta heuristic da aka tsara da ma'aunin rarraba daidai da babban iyaka na ka'idar.

5. Fahimtar Jigo & Ra'ayi na Manazarta

Fahimtar Jigo: Babban gudunmawar wannan takarda ita ce sake tsara rarraba makamashin mai sabuntawa daga matsala ta haɓaka yawan bayanai kawai zuwa matsala ta tattalin arzikin albarkatu mai wayar da kan amfani da QoS. Ta yarda cewa a cikin cibiyar sadarwa mai tsabta, makamashi ba kawai farashi ba ne amma shine farkon kayan da ba su da yawa. Ainihin ƙirƙira shine haɗa rarrabawa kai tsaye zuwa gamsuwar da mai amfani ya fahimta (amfani) wanda aka daidaita shi da gaskiyar zahiri (yanayin tashar), ƙirƙirar madaidaicin lefa mai dorewa ga masu sarrafa cibiyoyin sadarwa.

Kwararar Ma'ana: Hujja tana da ma'ana: 1) Makamashin mai sabuntawa yana da iyaka kuma yana canzawa. 2) Buƙatun masu amfani sun bambanta. 3) Don haka, rarrabawar mai hikima wanda ya yi la'akari da duka wadatar (makamashi, tashar) da buƙata (QoS) ya zama dole. 4) Aikin amfani yana ƙididdige musanya da kyau. 5) Heuristic mai sauƙi yana sa ya zama mai amfani. Kwararar daga ma'anar matsala zuwa mafita tana da haɗin kai kuma tana magance gibin bayyananne a cikin aikin da ya gabata wanda sau da yawa ya yi watsi da buƙatun QoS daban-daban, kamar yadda marubutan suka nuna daidai.

Ƙarfi & Kurakurai: Ƙarfi: Haɗakar ka'idar amfani tana da ƙarfi kuma tana aron kyau daga tattalin arzikin cibiyoyin sadarwa. Heuristic yana da amfani—yana karɓar cewa a cikin sarrafa cibiyar sadarwa na ainihi, mafita mai kyau, mai sauri ya fi mafi kyau, mai sauri. Mayar da hankali kan bambance-bambancen QoS yana da mahimmanci ga cibiyoyin sadarwa na zamani masu ɗauke da IoT, bidiyo, da zirga-zirgar mahimmanci. Kurakurai: Samfurin yana da ɗan sauƙi. Yana ɗauka tantanin halitta ɗaya, yana yin watsi da yuwuwar haɗin gwiwar makamashi tsakanin sel ta hanyar wayoyi masu hikima—wani yanki mai ban sha'awa da wasu kamar Zhou et al. suka bincika a cikin "Haɗin gwiwar Makamashi a Cibiyoyin Sadarwa tare da Tashoshin Tushe masu Ƙarfin Sabuntawa" (IEEE Transactions on Wireless Communications). Ana ɗauka ayyukan amfani an san su; a zahiri, ayyana da koyo waɗannan ayyukan a kowane nau'in sabis ƙalubale ne mara sauƙi. Takardar kuma ba ta da ingantaccen bincike na adalci; dabarun "yin yunwa ga masu amfani masu tashoshi marasa ƙarfi" a ƙarƙashin ƙarancin zai iya zama matsala ga yarjejeniyar matakin sabis.

Fahimta Mai Aiki: Ga masu aikin wayar tarho, wannan bincike yana ba da tsari na mai sarrafa makamashi mai tsarin software wanda zai zama mahimmanci a cikin cibiyoyin sadarwa na 5G-Advanced da 6G. Mataki na gaggawa shine ƙirƙirar wannan algorithm ​​a cikin gwajin gwaji tare da bayanan hasken rana/iska na ainihi. Bugu da ƙari, masu aiki yakamata su fara rarraba zirga-zirgarsu zuwa azuzuwan amfani. Ga masu bincike, matakai na gaba suna bayyananne: 1) Haɗa haɗin kai na sel da yawa da raba makamashi. 2) Haɗa koyon injina don koyo da aikin amfani daga bayanan ƙwarewar mai amfani. 3) Faɗaɗa samfurin don haɗa farashin lalacewar ajiyar makamashi. Wannan aikin, kamar yadda canjin tushe da "cycleGAN" ya kawo a cikin fassarar hoto-zuwa-hoto ta hanyar gabatar da daidaiton zagayowar, yana gabatar da tsari mai daidaito (amfani + ƙayyadaddun iyaka) don sabon nau'in matsalolin rarraba albarkatu masu tsabta.

6. Cikakkun Bayanai na Fasaha da Tsarin Lissafi

An ayyana ainihin haɓakawa a sashe na 2.3. Yawan bayanai da mai amfani $R_k$ zai iya samu akan subcarrier na OFDMA yawanci ana bayar da shi kamar haka: $$R_k = B \log_2 \left(1 + \frac{e_k \cdot h_k}{N_0 B}\right)$$ inda $B$ shine faɗin band na reshe albarkatun, kuma $N_0$ shine yawan hayaniyar yanki. Aikin amfani don sabis mai ƙayyadaddun jinkiri ana iya ƙirƙira shi azaman aikin sigmoidal: $$U_k(e_k) = \frac{1}{1 + \exp(-a(R_k(e_k) - b))}$$ inda ma'auni $a$ da $b$ ke sarrafa tsauri da tsakiyar aikin, suna nuna ƙofar QoS. Don zirga-zirgar elastic, ana amfani da aikin logarithmic mai ma'ana $U_k(e_k) = \ln(1 + R_k(e_k))$.

7. Tsarin Bincike: Misalin Hali

Hali: Tashar tushe tana da masu amfani 5 da $E_{total} = 10$ raka'o'in makamashin mai sabuntawa.

  • Mai Amfani 1 (Kiran Bidiyo): QoS: $R_{min}=2$ Mbps, Tashar: Mai Kyau ($h_1$ high), Amfani: Sigmoidal.
  • Mai Amfani 2 (Zazzage Fayil): QoS: Babu, Tashar: Mai Kyau, Amfani: Logarithmic.
  • Mai Amfani 3 (Na'urar Firikwensin IoT): QoS: $R_{min}=0.1$ Mbps, Tashar: Maras Kyau ($h_3$ low), Amfani: Kamar Mataki.
  • Masu Amfani 4 & 5: Irin wannan bayanan martaba gauraye.
Aiwatar da Algorithm:
  1. Lissafa makin fifiko ga kowane mai amfani (misali, $h_k \times (\text{ribar amfani na gefe})$).
  2. Rarraba masu amfani: A ce tsari shine MaiAmfani1, MaiAmfani2, MaiAmfani4, MaiAmfani5, MaiAmfani3.
  3. Ware wa MaiAmfani1 har sai QoS ɗin bidiyonsa ya cika (farashi: raka'o'i 3). Amfani ya yi tsalle sama.
  4. Ware wa MaiAmfani2. Kowace raka'a tana ba da ribar amfani mai kyau. Ware raka'o'i 4.
  5. Makamashin da ya rage = raka'o'i 3. Ware wa MaiAmfani4 don cika bukatarsa a wani bangare (farashi: raka'o'i 3).
  6. Makamashi ya ƙare. Masu amfani 5 da 3 (tare da tashar mara kyau) sun sami rarrabawar sifili.
Sakamako: An haɓaka jimillar amfani ta hanyar gamsar da masu amfani masu fifiko, masu inganci da farko. An yi yunwa ga MaiAmfani3—wannan shine musanyar manufar a ƙarƙashin ƙarancin.

8. Hangar Aikace-aikace da Hanyoyin Gaba

Gajeren Lokaci (shekaru 1-3): Haɗawa cikin tsarin sarrafa makamashi na cibiyar sadarwa (EMS) don manyan tashoshi da ƙananan tashoshi. Wannan yana da mahimmanci musamman ga ayyukan da ba su da waya ko na karkara waɗanda ke samun makamashi da farko daga hanyoyin sabuntawa, kamar yadda ake rubutawa a cikin ayyukan da ƙungiyar GSM Association's "Green Power for Mobile" ta yi.

Tsakiyar Lokaci (shekaru 3-5): Babban abin hangen nesa na 6G na haɗakar ganowa, sadarwa, da makamashi. Cibiyoyin sadarwa ba kawai za su cinye makamashi ba har ma za su sarrafa su kuma su rarraba shi. Wannan algorithm ​​zai iya haɓaka don sarrafa canja wurin wutar lantarki mara waya zuwa na'urorin IoT ko sarrafa kwararar makamashi daga ababen hawa zuwa cibiyar sadarwa (V2G) daga kayan aikin cibiyar sadarwa ta wayar hannu.

Hanyoyin Bincike na Gaba:

  • Haɗakar AI/ML: Yin amfani da koyon ƙarfafawa mai zurfi (DRL) don koyon manufofin rarrabawa masu kyau a cikin yanayi mai ƙarfi ba tare da samfuran amfani da aka riga aka ayyana ba.
  • Haɗin Rarraba Albarkatu da Yawa: Haɓaka haɗin gwiwar bakan, lokaci, da albarkatun makamashi a cikin tsari ɗaya.
  • Hanyoyin Tushen Kasuwa: Ai watar kasuwar makamashi na ainihi a cikin cibiyar sadarwa inda masu amfani/wakilai ke yin tayin don makamashin mai sabuntawa bisa ga bukatunsu, bisa ga ra'ayoyin ƙananan hanyoyin wutar lantarki na tushen blockchain.
  • Daidaituwa: Tura don daidaita sarrafa wayoyi masu wayar da kan makamashi a cikin gine-ginen Open RAN (O-RAN), yana barin aikace-aikacen sarrafa makamashi na ɓangare na uku (xApps).
Haɗuwar cibiyoyin sadarwa da hanyoyin wutar lantarki, wanda ake kira "Intanet na Makamashi," zai sa irin waɗannan algorithms ​​su zama dole.

9. Nassoshi

  1. Hukumar Makamashi ta Duniya (IEA). "Cibiyoyin Bayanai da Cibiyoyin Watsa Bayanai." Rahotannin IEA, 2022. [Kan layi]. Ana samuwa: https://www.iea.org/reports/data-centres-and-data-transmission-networks
  2. Z. Zhou et al., "Haɗin gwiwar Makamashi a Cibiyoyin Sadarwa tare da Tashoshin Tushe masu Ƙarfin Sabuntawa," IEEE Transactions on Wireless Communications, vol. 13, no. 12, pp. 6996-7010, Dec. 2014.
  3. GSMA. "Green Power for Mobile: The Global M2M Association on Sustainability." GSMA, 2021.
  4. O. Ozel et al., "Watsawa tare da Nodes masu Tarin Makamashi a cikin Tashoshi mara waya masu lalacewa: Manufofin Mafi Kyau," IEEE Journal on Selected Areas in Communications, vol. 29, no. 8, pp. 1732-1743, Sept. 2011. (An ambata a matsayin [8] a cikin PDF)
  5. J. Zhu et al., "Toward a 6G AI-Native Air Interface," IEEE Communications Magazine, vol. 61, no. 5, pp. 50-56, May 2023.
  6. J.-Y. Zhu, T. Park, P. Isola, A. A. Efros. "Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks." IEEE International Conference on Computer Vision (ICCV), 2017. (An ambata a matsayin misali na canjin tsarin tushe).