Tsarin Sadarwa ta Haske Mai Gani (VLC) na NOMA tare da Masu Karɓa Masu Bambance-bambancen Karkata: Nazari da Fahimta

1. Gabatarwa

Bukatar da ba ta ƙarewa don ƙimar bayanai mafi girma shine babban abin motsa bincike a cikin sadarwa. Sadarwar Haske Mai Gani (VLC) tana gabatar da fasaha mai ban sha'awa mai haɗawa da tsarin mitar rediyo (RF), ta yin amfani da yaduwar hasken LED don watsa bayanai. Duk da haka, VLC tana fuskantar ƙalubale na asali kamar iyakancewar bandwidth na LED, Tsangwama Tsakanin Alamomi (ISI), da Tsangwama Tashoshi Guda (CCI) a cikin yanayin masu amfani da yawa. Wannan takarda tana binciken haɗakar Non-Orthogonal Multiple Access (NOMA) tare da Masu Karɓa Masu Bambance-bambancen Karkata (ADRs) don shawo kan waɗannan iyakoki da haɓaka aikin tsarin sosai a cikin hanyoyin sadarwa na VLC na cikin gida.

2. Tsarin Tsarin

An ƙirƙira tsarin da aka gabatar a cikin daidaitaccen yanayin cikin gida don kimanta haɗin gwiwa tsakanin fasahar NOMA da ADR.

2.1 Ƙirar Daki da Tashoshi

An yi siminti na daki mai siffar murabba'i mai girma 8m (tsayi) × 4m (faɗi) × 3m (tsayi). An ƙirƙira bangon da rufin a matsayin masu nuna haske na Lambertian tare da ƙimar nunin haske (ρ) na 0.8. Ana ƙididdige amsawar motsin tashoshi ta gani ta amfani da algorithm mai ƙayyadaddun hasken haske, yana la'akari da duka hanyoyin gani kai tsaye (LOS) da nunin haske (har zuwa wani mataki da aka ƙayyade). Ana iya ƙirƙira ribar tashoshi don hanyar haɗi kamar haka:

$H(0) = \frac{(m+1)A}{2\pi d^2} \cos^m(\phi) T_s(\psi) g(\psi) \cos(\psi)$ don $0 \le \psi \le \Psi_c$

inda $m$ shine matakin Lambertian, $A$ shine yankin mai gano, $d$ shine nisa, $\phi$ da $\psi$ sune kusurwoyin haske da kusurwoyin shiga, $T_s(\psi)$ shine ribar tacewa, $g(\psi)$ shine ribar mai tattarawa, kuma $\Psi_c$ shine Filin Dubawa (FOV) na mai karɓa.

2.2 Ƙirar Mai Karɓa Mai Bambance-bambancen Karkata (ADR)

Babban ƙirƙira shine amfani da ADR mai reshe 4. Kowane reshe ya ƙunshi mai gano hoto mai ƙunƙuntaccen FOV, wanda aka karkata shi zuwa wata hanya ta musamman (misali, sama da kuma a takamaiman kusurwoyin azimuth). Wannan ƙirar tana ba mai karɓa damar haɗa siginonin da aka zaɓa daga reshe tare da mafi ƙarfin ribar tashoshi, yana rage tasirin hayaniyar hasken muhalli, tarwatsawar hanyoyi da yawa, da tsangwama tashoshi guda daga wasu Wuraren Samun dama (APs) yadda ya kamata.

2.3 Ka'idar NOMA da Rarraba Wutar Lantarki

NOMA tana aiki a cikin yankin wutar lantarki. A wurin mai watsawa, ana haɗa siginoni don masu amfani da yawa tare da matakan wutar lantarki daban-daban. Babban ka'ida ita ce a ba da ƙarin wutar lantarki ga masu amfani da ke da mafi ƙarancin yanayin tashoshi. A wurin mai karɓa, ana amfani da Soke Tsangwama na Bi da Bi (SIC): mai amfani da ke da mafi kyawun tashoshi yana ƙididdige siginonin masu amfani da ke da raunana tashoshi kuma ya cire su kafin ya ƙididdige nasa. Ƙimar da mai amfani $i$ zai iya samu a cikin nau'i-nau'i na NOMA na mai amfani 2 ana bayar da ita kamar haka:

$R_i = B \log_2 \left(1 + \frac{\alpha_i P_t |h_i|^2}{\sum_{j>i} \alpha_j P_t |h_i|^2 + N_0 B}\right)$

inda $B$ shine bandwidth, $P_t$ shine jimillar wutar lantarki da ake watsawa, $h_i$ shine ribar tashoshi don mai amfani $i$, $\alpha_i$ shine ƙimar rarraba wutar lantarki ($\alpha_1 + \alpha_2 = 1$, kuma $\alpha_1 > \alpha_2$ idan $|h_1|^2 < |h_2|^2$), kuma $N_0$ shine yawan ƙarfin hayaniyar wutar lantarki.

3. Sakamakon Siminti da Tattaunawa

An yi kwatancen aikin tsarin NOMA-VLC tare da ADR da tsarin tushe ta amfani da mai karɓa guda mai faɗin FOV.

3.1 Ma'auni da Saitin Ayyuka

Babban ma'aunin aiki shine jimillar ƙimar bayanai don masu amfani da yawa a cikin ɗakin. Ana sanya masu amfani a wurare bazuwar, kuma ana inganta rarraba albarkatu (haɗa masu amfani don NOMA da rarraba wutar lantarki) bisa bayanan yanayin tashoshinsu, bin tsarin da marubutan suka yi a baya [36].

3.2 Kwatancen Ƙimar Bayanai: ADR vs. FOV Mai Faɗi

Sakamakon siminti ya nuna fa'ida ta ƙuduri ga tsarin tushen ADR. Amfani da ADRs yana inganta matsakaicin ƙimar bayanai da kusan kashi 35% idan aka kwatanta da tsarin da ke amfani da masu karɓa masu faɗin FOV. An samo wannan ribar ne saboda ikon ADR na zaɓar hanyar sigina mai ƙarfi, wacce ba ta karkace ba, don haka yana ƙara ingantaccen ma'auni na sigina-zuwa-tsangwama-da-hayaniya (SINR) don ƙididdigar NOMA.

3.3 Tasirin Rarraba Albarkatu

Takardar ta nuna cewa ribar aikin ba ta atomatik ba amma tana dogara ne akan rarraba albarkatu mai hankali. Haɗa masu amfani da ke da bambance-bambancen ribar tashoshi (abu mai mahimmanci don ingantaccen NOMA) da rarraba wutar lantarki daidai yana da mahimmanci don cimma cikakkiyar yuwuwar haɗin ADR-NOMA.

Mahimman Fahimtar Aiki

Ƙaruwar Matsakaicin Ƙimar Bayanai Kashi 35% da aka samu ta haɗa ADR mai reshe 4 tare da NOMA a cikin VLC, idan aka kwatanta da na al'ada masu karɓa masu faɗin FOV.

4. Ƙarshe

Wannan aikin ya yi nasara wajen nuna cewa haɗakar Masu Karɓa Masu Bambance-bambancen Karkata tare da Non-Orthogonal Multiple Access wata dabara ce mai ƙarfi don haɓaka ƙarfin aiki da ƙarfin tsarin Sadarwar Haske Mai Gani na cikin gida. Ikon ADR na samar da mafi kyawun shigar tashoshi don tsarin SIC na NOMA kai tsaye yana haifar da ingantaccen ƙimar bayanai, yana ba da hujja mai ƙarfi ga wannan gine-ginen gauraye a cikin hanyoyin sadarwa na gani masu yawan gaske na gaba.

5. Nazari na Asali & Fahimtar ƙwararru

Babban Fahimta: Wannan takarda ba game da ƙara mafi kyawun mai karɓa kawai ba ce; ƙwararren hack ne na injiniyanci wanda ke sake tsara kasafin haɗin VLC a mafi raunin matsayinsa—ƙasan hayaniyar mai karɓa—don buɗe cikakkiyar yuwuwar ka'idar NOMA. Marubutan sun gano daidai cewa aikin NOMA yana da matsananciyar matsalar nasarar SIC, wanda ya gaza sosai a cikin tashoshin VLC masu yaduwa, masu hanyoyi da yawa. ADR mai reshe 4 yana aiki azaman tacewa ta sarari, yana ƙirƙirar tashoshi "mai tsabta" don babban mai amfani a cikin nau'i-nau'i na NOMA, yana mai da ribar ka'ida zuwa haɓaka kashi 35% na aiki.

Kwararar Hankali: Hujja tana da kyau: 1) VLC tana buƙatar ingantaccen yanayin yanayi (shiga NOMA). 2) NOMA tana buƙatar bambance-bambancen ribar tashoshi mai ƙarfi (matsala a cikin haske iri ɗaya). 3) ADR ta ƙirƙira wannan bambance-bambancen ta hanyar zaɓar mafi ƙarfin hanyar shiga. 4) Sakamako: SIC yana aiki mafi kyau, jimillar ƙimar yana ƙaruwa. Wannan hanya ce mafi ƙwarewa fiye da kawai ƙara ƙarfin watsawa ko bandwidth, wanda ya dace da yanayin binciken 6G da ke mai da hankali kan yanayin rediyo mai hankali, kamar yadda aka tattauna a cikin farar takardu daga Ƙungiyar Next G.

Ƙarfi & Kurakurai: Ƙarfin yana cikin ingantaccen ribar aiki mai mahimmanci ta amfani da ingantaccen mai karɓa mai sauƙi. Hanyar tana da inganci, ta amfani da ingantattun ƙirar hasken haske da na NOMA. Duk da haka, nazarin yana da guraben guraben da aka lura. Na farko, yana ɗauka cikakken bayanin yanayin tashoshi (CSI) da cikakkiyar SIC—duka suna da kyakkyawan fata a cikin tsarin ainihin lokaci tare da masu amfani masu motsi. Na biyu, ADR mai reshe 4 yana ƙara farashin mai karɓa, girma, da rikitarwar sarrafawa (dabarar zaɓin reshe). Takardar ta yi watsi da wannan ciniki. Idan aka kwatanta da ayyukan farko akan kayan aikin gani masu daidaitawa a cikin sadarwar gani ta sarari (kamar waɗanda daga Lab na MIT Media), wannan hanyar ADR tana tsaye; tana zaɓe amma ba ta tafiyar da ko siffanta katakon ba, tana barin ƙarin aiki akan tebur.

Fahimta Mai Aiki: Ga manajoji samfur da shugabannin R&D, wannan bincike yana ba da cikakkiyar taswirar hanya: Ba da fifiko ga ƙirƙira mai karɓa. Zuba jari a cikin masu gano hoto masu hankali, masu abubuwa da yawa shine mabuɗin bambance samfuran Li-Fi na gaba. Mataki na gaba nan da nan ya kamata a ƙirƙira algorithm na zaɓin reshe na ainihin lokaci kuma a gwada shi a ƙarƙashin yanayin tashoshi masu motsi tare da CSI mara kyau. Bugu da ƙari, bincika dabarun gauraye: haɗa wannan ADR tare da Sparse Code Multiple Access (SCMA) ko dabarun Sa hannu na Low-Density (LDS) da aka bincika a cikin 5G NR, waɗanda zasu iya ba da ciniki mafi kyau na rikitarwa-aiki fiye da cikakken yankin wutar lantarki na NOMA don tashoshin gani.

6. Cikakkun Bayanai na Fasaha

Aikin tsarin yana dogara ne akan ƙirar tashoshi da tsarin ƙididdigar NOMA. Ƙarfin gani da reshe na $k$ na ADR ya karɓa daga LED na $j$ shine:

$P_{r,(j,k)} = H_{j,k}(0) * P_{t,j}$

Mai karɓa yana zaɓar reshe $k^*$ tare da mafi girman SNR: $k^* = \arg\max_k (\sum_j P_{r,(j,k)}^2 / N_0)$. Don nau'i-nau'i na NOMA na ƙasa tare da masu amfani $U_1$ (tashoshi mara ƙarfi) da $U_2$ (tashoshi mai ƙarfi), siginar da aka watsa ita ce $x = \sqrt{\alpha P_t}s_1 + \sqrt{(1-\alpha)P_t}s_2$, inda $s_1, s_2$ suke siginonin mai amfani. $U_2$ yana ƙididdige $s_1$ da farko, ya cire shi, sannan ya ƙididdige $s_2$. $U_1$ yana ɗaukar $s_2$ a matsayin hayaniya kuma yana ƙididdige $s_1$ kai tsaye. ADR yana inganta $|h_i|^2$ don mai amfani da aka zaɓa, yana ƙara hujja na aikin $\log_2$ a cikin ma'aunin ƙimar kai tsaye.

7. Sakamakon Gwaji & Bayanin Ginshiƙi

Yayin da abin da aka ba da na PDF bai ƙunshi siffofi bayyanannu ba, ana iya ganin sakamakon da aka bayyana ta hanyar manyan ginshiƙi guda biyu:

Ginshiƙi 1: Aikin Rarraba na Jimillar (CDF) na Ƙimar Bayanai na Mai Amfani. Wannan ginshiƙi zai nuna lanƙwasa biyu: ɗaya don tsarin mai karɓa mai faɗin FOV ɗaya kuma don tsarin ADR. Lanƙwasa ADR za a canza shi sosai zuwa dama, yana nuna cewa ga kowane ƙima mai yuwuwa (misali, kashi 50% na masu amfani), ƙimar bayanai da za a iya samu ta fi girma. Tazarar da ke tsakanin lanƙwasan tana wakiltar ribar matsakaicin ~35%.

Ginshiƙi 2: Jimillar Ƙimar vs. Yawan Masu Amfani. Wannan ginshiƙi zai zana jimillar ƙarfin tsarin yayin da adadin masu amfani ke ƙaruwa. Layin NOMA+ADR zai nuna mafi ƙanƙanta gangare da mafi girman matakin fiye da layin NOMA+Wide-FOV, yana nuna mafi kyawun ƙima da ingancin masu amfani da yawa. Layi na uku don al'adar Orthogonal Multiple Access (OMA) kamar TDMA zai kasance ƙasa da duka biyun sosai, yana nuna fa'idar ingantaccen yanayin yanayi na NOMA.

8. Tsarin Nazari: Misalin Lamari

Yanayi: Kimanta tsarin VLC don wurin aiki mai yawan gaske na cikin gida (misali, buɗaɗɗen ofis tare da tashoshi aiki 20).

Aikace-aikacen Tsarin:

Bayanan Tashoshi: Yi amfani da software mai bin hasken haske don ƙirƙira ɗakin tare da kayan aikin LED akan rufin. Ƙididdige matrix ribar tashoshi $H$ don kowane wurin mai amfani mai yuwuwa zuwa duka ƙirar FOV mai faɗi da reshe da yawa na ADR.
Haɗa Masu Amfani don NOMA: Ga kowane tazara na tsarawa, sanya masu amfani bisa ribar tashoshinsu daga reshen ADR da aka zaɓa. Ƙirƙiri nau'i-nau'i na NOMA ta hanyar haɗa mai amfani tare da tashoshi mai ƙarfi da mai amfani tare da tashoshi mara ƙarfi.
Ingantaccen Rarraba Wutar Lantarki: Warware ƙimar ƙimar wutar lantarki $\alpha_i$ waɗanda ke haɓaka jimillar ƙimar, bisa ga ƙuntatawa: $\sum \alpha_i = 1$, $\alpha_i > 0$, da ƙananan buƙatun ƙimar $R_i \ge R_{min}$. Wannan matsala ce ta ingantaccen warwarewa wacce za a iya warware ta ta hanyar daidaitattun algorithms.
Hasashen Aiki: Shigar da ingantattun sigogi cikin ma'aunin ƙimar $R_i$ don ƙididdige ƙimar bayanai da aka hasashe ga kowane mai amfani da jimillar ƙimar tsarin. Kwatanta sakamakon ƙirar ADR da na tushen FOV mai faɗi.

Wannan tsarin yayi daidai da hanyar da aka nuna a cikin takardar kuma yana ba da tsari na tsari don ƙididdige fa'idar ADR a cikin takamaiman turawa.

9. Aikace-aikace na Gaba & Jagorori

Tsarin ADR-NOMA-VLC yana da madaidaicin hanyoyi masu ban sha'awa:

Sadarwa Mai Dogaro Mai Ƙarfi da Jinkiri (URLLC) don IoT na Masana'antu: A cikin masana'antu masu hankali, ADRs na iya samar da ingantattun hanyoyin haɗi don sarrafa na'ura ta hanyar rage tsangwama daga kayan aiki masu motsi da saman nunin haske.
Sadarwar Gani ta Ƙarƙashin Ruwa: Yanayin tarwatsawa a ƙarƙashin ruwa yayi kama da VLC na cikin gida mai yaduwa. ADRs na iya taimakawa ware babbar hanyar LOS a cikin ruwa mai ɗimbin yawa, yana ba da damar NOMA don hanyoyin sadarwa na ƙarƙashin ruwa masu yawan amfani.
Haɗa Hankali da Sadarwa (ISAC): Za a iya amfani da reshe da yawa na ADR don ƙididdige kusurwar isowa, yana ba da damar gano wurin na'ura tare da sadarwa—siffa mai mahimmanci don gine-ginen gine-gine masu hankali na gaba.
Hanyoyin Bincike: Aikin gaba dole ne ya matsa zuwa ADRs masu daidaitawa ta amfani da ruwan crystal ko tsarin micro-electromechanical (MEMS) don tafiyar da katako mai ƙarfi. Bugu da ƙari, haɗa koyon inji don haɗa mai amfani na ainihin lokaci, mai ƙarfi da rarraba wutar lantarki a cikin yanayin motsi shine muhimmin mataki na gaba don canzawa daga siminti zuwa turawa.

10. Nassoshi

Aljohani, M. K., da sauransu. (2022). Tsarin Sadarwa ta Haske Mai Gani na NOMA tare da Masu Karɓa Masu Bambance-bambancen Karkata. Jarida/Taron Tushe.
Zeng, L., da sauransu. (2017) Babban Ƙimar Bayanai Multiple Input Multiple Output (MIMO) Sadarwar Wireless ta Gani ta Amfani da Hasken LED Fari. IEEE Jarida akan Zaɓaɓɓun Yankuna na Sadarwa.
Ding, Z., da sauransu. (2017) Bincike akan Non-Orthogonal Multiple Access don Hanyoyin Sadarwa na 5G: Ƙalubalen Bincike da Yanayin Gaba. IEEE Jarida akan Zaɓaɓɓun Yankuna na Sadarwa.
Kahn, J. M., & Barry, J. R. (1997). Sadarwar Infrared mara waya. Proceedings of the IEEE.
Ƙungiyar Next G. (2023). Rahoton Fasaha na 6G. ATIS.
Daidaitaccen IEEE don Gida da Manyan Hanyoyin Sadarwa–Sashi na 15.7: Sadarwar Gani mara waya ta Gajeren Zango ta Amfani da Haske Mai Gani. (2018). IEEE Std 802.15.7-2018.
Wang, Q., da sauransu. (2020). Koyon Zurfi don Mafi Kyawun Rarraba Wutar Lantarki ta NOMA a cikin Sadarwar Haske Mai Gani. Wasiƙun Sadarwa na IEEE Wireless.