Tsarin Tsarin SLNR Mai Amfani da Ƙananan Ƙwayoyin Zinare a Tsarin Sadarwar Haske na Motoci (VVLC)

1. Gabatarwa & Bayyani

Wannan takarda tana magance wata matsala mai mahimmanci a cikin Tsarin Sadarwar Haske na Motoci (VVLC): babban haɗin kai na sararin samaniya tsakanin Diodes masu Fitowa da Haske (LEDs) a cikin fitilun mota, wanda ke iyakance sosai ƙimar bayanai da za a iya samu ta hanyar haɗa sararin samaniya. Masu rubutun sun ba da shawara sabon mafita mai haɗa kai, wanda ya haɗa tsarin tsarin SLNR (sigina-zuwa-leakage-plus-noise ratio) don tallafawa masu amfani da yawa tare da haɗa ƙananan ƙwayoyin zinare (GNPs). GNPs suna amfani da kaddarorin chiroptical don samar da bambancin shan haske dangane da kusurwar hasken da ya faru, don haka suna rage haɗin tashoshi na LED masu kusanci da juna. Bugu da ƙari, tsarin dole ne ya inganta rabon hasken Ja, Kore, da Shudi (RGB) a cikin kowane LED don kiyaye farin haske don haskakawa yayin da yake haɓaka jimlar SLNR, kamar yadda GNPs suke haifar da shan haske dangane da tsawon zango. Matsalolin ingantawa marasa ma'ana da aka samu ana magance su ta amfani da ma'auni na gabaɗaya na Rayleigh da Kusan Kullun na Gaba (SCA).

2. Fahimtar Tsaki & Ra'ayin Mai Bincike

Fahimtar Tsaki: Hikimar takardar tana cikin gyaran matakin kayan aiki na matsala ta asali ta sadarwa. Maimakon kawai gyara algorithms don jurewa tashoshi na VVLC masu haɗin kai sosai—wata sananniyar matsala—masu rubutun sun gabatar da gyaran matakin jiki ta amfani da ƙananan ƙwayoyin zinare. Wannan ba wani takarda ne kawai na tsarin MIMO ba; yana nuna yadda za a iya amfani da fasahar nanotechnology don sake fasalin halayen tashoshi, yana ba da matakin sarrafa da ba a samu ba a cikin tsarin gani mara aiki.

Kwararar Ma'ana: Hujjar tana da ƙarfi: 1) VVLC yana buƙatar ƙimar bayanai mai girma don ITS na gaba, 2) Haɗa sararin samaniya yana toshewa ta hanyar haɗin LED na asali, 3) GNPs na iya sarrafa polarization/shan haske don rage wannan haɗin kai, 4) Ana buƙatar mai tsara tsari na masu amfani da yawa (SLNR) don sarrafa tsangwama, 5) Tasirin tace launi na GNP yana buƙatar inganta rabon RGB don kiyaye ingancin haskakawa. Kwararar daga kimiyyar kayan aiki zuwa ka'idar sadarwa zuwa ingantawa mai amfani ba ta da tsangwama.

Ƙarfi & Kurakurai: Babban ƙarfi shine sabon mafita mai haɗa yanki. Amfani da kaddarorin chiroptical na nanomaterials don sadarwa sabuwar hanya ce mai ban sha'awa, mai kama da yadda metamaterials suka canza RF. Amfani da tsarin tsarin SLNR ya dace don sarrafa tsangwama tsakanin masu amfani da yawa a cikin yanayin watsa shirye-shiryen V2V. Duk da haka, binciken ya yi watsi da manyan matsaloli masu mahimmanci: kwanciyar hankali na dogon lokaci da farashin haɗa GNPs cikin LED na kasuwanci na mota, tasirin yanayi mai tsanani (zafi, girgiza) akan aikin ƙananan ƙwayoyin, da rikitarwar lissafi na ainihi na haɗin tsarin tsari/RGB don tashoshi na mota masu ƙarfi sosai. Zato na cikakken bayanin yanayin tashoshi (CSI) kuma wani sauƙaƙe ne na al'ada wanda bazai yi aiki ba a cikin yanayin V2V masu sauri.

Fahimta Mai Aiki: Ga masu bincike, wannan takarda ta buɗe sabuwar hanya: "kayayyaki masu hankali don tashoshi masu hankali." Ya kamata a mayar da hankali zuwa wasu nanomaterials (misali, ɗigon ƙididdiga, kayan 2D kamar graphene) tare da kaddarorin gani masu daidaitawa. Ga masana'antu, ana ba da shawarar tsarin matakai: 1) Na farko, aiwatar da gwajin filin algorithm ɗin tsarin tsarin SLNR a cikin samfuran VVLC da aka tsara ta software ba tare da GNPs ba don kafa tushe. 2) Haɗin gwiwa tare da masana kimiyyar kayan aiki don haɓaka ƙaƙƙarfan, ƙananan farashin rufaffiyar GNP ko LED phosphors masu guba. 3) Bincika tsarin haɗin RF-VLC inda VLC ke sarrafa hanyoyin haɗin gwiwa masu faɗi, ɗan gajeren zango (yana amfani da wannan dabarar rage haɗin kai) kuma RF yana samar da ƙaƙƙarfan tashoshi na sarrafa dogon zango, ƙirƙirar ƙaƙƙarfan hanyar sadarwa ta mota.

3. Tsarin Fasaha

3.1 Tsarin Tsarin

Tsarin yana la'akari da yanayin saukar VVLC na masu amfani da yawa inda motar mai watsawa sanye take da $N_t$ LEDs (misali, a cikin jerin fitila) tana sadarwa tare da $K$ motocin mai karɓa. Sigar da aka karɓa a mai amfani na $k$ an bayar da shi ta:

$\mathbf{y}_k = \mathbf{H}_k \mathbf{x} + \mathbf{n}_k$

inda $\mathbf{H}_k \in \mathbb{C}^{N_r \times N_t}$ shine matrix ɗin tashar VLC MIMO don mai amfani $k$, $\mathbf{x}$ shine vector ɗin siginar da aka watsa daga jerin LED, kuma $\mathbf{n}_k$ shine ƙara hayaniya wanda ya mamaye hayaniyar harbi. Babban haɗin kai a cikin $\mathbf{H}_k$ ya samo asali ne daga ƙaramin tazara tsakanin LEDs a cikin tarin fitila.

3.2 Ƙananan Ƙwayoyin Zinare don Rage Haɗin Kai

Ƙananan Ƙwayoyin Zinare (GNPs) suna nuna aikin chiroptical—hulɗarsu da haske ya dogara da polarization da'ira da kusurwar da ta faru. Lokacin da aka haɗa su tare da LEDs, suna aiki azaman tacewa a matakin nano. Hasken daga LEDs masu kusa, suna zuwa daga ɗan bambancin kusurwoyi, suna fuskantar bambancin shan haske da canje-canjen lokaci. Wannan tsari yana sa martanin tashoshi daga kowane LED ya fi bambanta, yana rage ma'auni na haɗin kai $\rho$ tsakanin ginshiƙan $\mathbf{H}_k$. Aikin canja wurin GNP ana iya ƙirƙira shi azaman matrix mai rikitarwa, mai dogaro da kusurwa $\mathbf{\Gamma}(\theta)$ da aka yi amfani da shi ga siginar da aka watsa.

3.3 Tsarin Tsarin SLNR

Don tallafawa masu amfani da yawa lokaci guda, takardar tana amfani da tsarin tsarin SLNR. SLNR don mai amfani $k$ an bayyana shi azaman rabon ƙarfin siginar da ake so a mai amfani $k$ zuwa jimlar tsangwama (leakage) da ya haifar ga duk sauran masu amfani da ƙara hayaniya:

$\text{SLNR}_k = \frac{\text{Tr}(\mathbf{W}_k^H \mathbf{H}_k^H \mathbf{H}_k \mathbf{W}_k)}{\text{Tr}(\mathbf{W}_k^H (\sum_{j \ne k} \mathbf{H}_j^H \mathbf{H}_j + \sigma_n^2 \mathbf{I}) \mathbf{W}_k)}$

inda $\mathbf{W}_k$ shine matrix ɗin tsari don mai amfani $k$. Manufar ita ce tsara $\{\mathbf{W}_k\}$ don haɓaka jimlar SLNR a cikin duk masu amfani.

4. Ingantawa & Algorithms

4.1 Tsarin Matsala

Babban ingantawa matsala ce ta haɗin gwiwa: nemo matrices ɗin tsari $\{\mathbf{W}_k\}$ da rabon ƙarfin RGB $\mathbf{c} = [c_R, c_G, c_B]^T$ (dangane da $c_R+c_G+c_B=1$ don farin haske) waɗanda ke haɓaka jimlar SLNR. Shan haske mai dogaro da tsawon zango na GNP yana sa tashoshi mai tasiri $\mathbf{H}_k$ ya zama aiki na $\mathbf{c}$, yana haifar da matsala mai haɗaka, mara ma'ana:

$\max_{\{\mathbf{W}_k\}, \mathbf{c}} \sum_{k=1}^K \text{SLNR}_k(\{\mathbf{W}_k\}, \mathbf{c}) \quad \text{s.t.} \quad \mathbf{c} \succeq 0, \quad \mathbf{1}^T\mathbf{c}=1, \quad \text{da ƙuntatawa na ƙarfi.}$

4.2 Kusan Kullun na Gaba (SCA)

Don magance wannan, masu rubutun suna amfani da SCA. Manufar sum-SLNR mara ma'ana ana kusanta ta ta jerin ƙananan matsala masu ma'ana. Don ƙayyadaddun $\mathbf{c}$, mafi kyawun $\mathbf{W}_k$ an samo shi daga matsala ta eigenvalue ta gabaɗaya da ke da alaƙa da ma'aunin SLNR. Don ƙayyadaddun $\{\mathbf{W}_k\}$, matsala a cikin $\mathbf{c}$ ana kusanta shi ta hanyar faɗaɗa sa na farko (aikin ma'ana) a kusa da wurin yanzu, sannan a inganta shi a jere. Wannan tsari yana tabbatar da haɗuwa zuwa mafita mafi kyau na gida.

5. Sakamakon Gwaji & Aiki

Mahimman Ma'auni na Aiki (Simulation)

Ribon Jimlar Ƙimar: Tsarin GNP+SLNR da aka tsara yana nuna gagarumin ci gaba akan tsarin tsarin VLC na al'ada (misali, Zero-Forcing) da kuma yanayin ba tare da rage haɗin GNP ba.
Rage Haɗin Kai: Haɗa GNPs yana rage ma'auni na haɗin tashoshi tsakanin LED da kiyasin 40-60%, yana ba da damar haɗa sararin samaniya mai tasiri.
Ƙimar Sirri: A cikin yanayin sata tare da mai sauraro, tsarin yana nuna ƙimar sirri sosai, kamar yadda mai tsara SLNR a asalinsa yana rage siginar da ke ɓarna zuwa masu karɓa da ba a so.

5.1 Haɓaka Jimlar Ƙimar

Sakamakon simulation ya nuna cewa haɗin gwiwar inganta masu tsarawa da rabon RGB na iya ƙara jimlar ingancin yanayin kusan 2-3x idan aka kwatanta da tsarin tushe da ke amfani da ƙayyadaddun farin haske da sauƙaƙen tsari, musamman a cikin matsakaici zuwa manyan yanayin SNR. Ribar ta fi bayyana lokacin da adadin masu amfani $K$ yake kusa da adadin watsa LED $N_t$.

5.2 Ƙimar Sirri a cikin Sata

Takardar tana kimanta tsaron matakin jiki. Ta hanyar haɓaka SLNR—wanda a fili yana hukunta ƙarfin siginar da ke ɓarna zuwa wasu masu amfani—tsarin da aka tsara yana haɓaka tsaro a kan masu sauraro marasa aiki. Sakamakon ya nuna babban tazara tsakanin ƙimar da mai amfani na halal zai iya samu da ƙarfin tashar mai sauraro, yana tabbatar da fa'idar tsaro.

6. Tsarin Bincike & Misalin Lamari

Tsarin don Kimanta Mafita na VLC mai Haɗa Yanki:

Tasirin Rage Haɗin Tashoshi: Ƙididdige raguwar haɗin kai na sararin samaniya (misali, ta hanyar yaduwar eigenvalue na $\mathbf{H}^H\mathbf{H}$) kafin da bayan amfani da nanomaterial/gyaran jiki.
Ciniki na Algorithmic-Computational: Bincika saurin haɗuwa da rikitarwar lissafi (misali, FLOPs a kowane juzu'i na SCA) da ribar jimlar ƙimar da aka samu. Shin fa'idar ta cancanci nauyin sarrafa ainihin lokaci?
Bin Ƙa'idar Ingancin Haskakawa: Tabbatar cewa ingantattun rabon RGB $\mathbf{c}$ koyaushe suna samar da haske a cikin ƙayyadaddun ma'auni na nunin launi (CRI) da ɗaurin zafin launi (CCT) don ƙa'idodin mota.
Binciken Ƙarfi: Gwada aiki a ƙarƙashin CSI mara kyau, motsin mota (tasirin Doppler), da yanayi daban-daban (hazo, ruwan sama).

Misalin Lamari (Hasashe): Yi la'akari da jerin fitila na LED 4 suna sadarwa tare da motocin karɓa 2. Ba tare da GNPs ba, matrices ɗin tashoshi $\mathbf{H}_1$ da $\mathbf{H}_2$ kusan ba su da ƙima. Mai ingantawa na haɗin gwiwar SCA, wanda ya haɗa da samfurin raguwar kusurwa na GNP, ya sami cakuda RGB na [0.35, 0.45, 0.20] da masu tsarawa masu dacewa. Wannan saitin yana rage haɗin kai tsakanin LED daga 0.9 zuwa 0.4, yana ba mai tsara SLNR damar ƙirƙira rafukan bayanai biyu a layi daya, yana ninka jimlar ƙimar yayin da yake kiyaye farin haske na 6000K.

7. Ayyukan Gaba & Hanyoyin Bincike

Advanced Nanomaterials: Bincike zuwa wasu ƙananan ƙwayoyin plasmonic (azurfa, aluminum) ko ɗigon ƙididdiga tare da ƙarfi ko amsawar chiroptical masu daidaitawa don daidaita tashoshi mai ƙarfi.
Koyon Injina don Ingantawa: Maye gurbin SCA mai jere tare da cibiyar sadarwar jijiya mai zurfi da aka horar don hasashen haɗin gwiwar mai tsarawa da rabon RGB kusan nan take, mai mahimmanci ga yanayin motsi mai girma.
Haɗa Hankali da Sadarwa (ISAC): Yi amfani da siginonin shan GNPs na musamman a ƙarƙashin yanayi daban-daban don hankalin muhalli lokaci guda (misali, gano yawan hazo) da sadarwa mai daidaitawa.
Daidaituwa da Ƙirƙira Samfuri: Haɓaka ƙa'idodin masana'antu don "matakin sadarwa" na kayan LED kuma ku matsawa zuwa samfuran kayan aiki don gwajin V2V na ainihin duniya da na mota-zuwa-kayan aiki (V2I).
Hanyoyin Sadarwa na Motoci na Haɗin LiFi/RF: Yi amfani da hanyar haɗin gwiwar VVLC mai faɗi da aka tsara don aikace-aikacen bayanai masu nauyi (sabunta taswirar HD, raba firikwensin) tare da RF na ƙasa da 6 GHz ko mmWave don sarrafawa da koma baya, ƙirƙirar hanyar sadarwa mai ƙarfi mai yawa.

8. Nassoshi

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