国家自然科学基金(61872406,61472094)
浙江省重点研发计划项目(2018C1059)
[1] Li Y, Jiang T, Sheng M. QoS-Aware Admission Control and Resource Allocation in Underlay Device-to-Device Spectrum-Sharing Networks. IEEE J Sel Areas Commun, 2016, 34: 2874-2886 CrossRef Google Scholar
[2] Meng L, Hua J, Lin M. Accurate joint estimation of Doppler shift and SNR in mobile communications with high vehicle speed. Sci Sin-Inf, 2017, 47: 1705-1714 CrossRef Google Scholar
[3] Ansari R I, Chrysostomou C, Hassan S A. 5G D2D Networks: Techniques, Challenges, and Future Prospects. IEEE Syst J, 2018, 12: 3970-3984 CrossRef ADS Google Scholar
[4] Xue L, Peng J, Guan X. Integrated security of cyber-physical vehicle networked systems in the age of 5G. Sci Sin-Inf, 2019, 49: 1640-1658 CrossRef Google Scholar
[5] Cheng N, Zhou H, Lei L. Performance Analysis of Vehicular Device-to-Device Underlay Communication. IEEE Trans Veh Technol, 2017, 66: 5409-5421 CrossRef Google Scholar
[6] Ren Y, Liu F, Liu Z. Power Control in D2D-Based Vehicular Communication Networks. IEEE Trans Veh Technol, 2015, 64: 5547-5562 CrossRef Google Scholar
[7] Sun W, Yuan D, Strom E G. Cluster-Based Radio Resource Management for D2D-Supported Safety-Critical V2X Communications. IEEE Trans Wireless Commun, 2016, 15: 2756-2769 CrossRef Google Scholar
[8] Sun W, Strom E G, Brannstrom F. Radio Resource Management for D2D-Based V2V Communication. IEEE Trans Veh Technol, 2016, 65: 6636-6650 CrossRef Google Scholar
[9] Sun P, Shin K G, Zhang H. Transmit Power Control for D2D-Underlaid Cellular Networks Based on Statistical Features. IEEE Trans Veh Technol, 2017, 66: 4110-4119 CrossRef Google Scholar
[10] Chen Q, Wu F, Leng S, et al. Degree of link dependence-based LTE-V2V clustering and alarm information forwarding. In: Proceedings of IEEE/CIC International Conference on Communications, 2016. 6. Google Scholar
[11] Khan A A, Abolhasan M, Ni W. An Evolutionary Game Theoretic Approach for Stable and Optimized Clustering in VANETs. IEEE Trans Veh Technol, 2018, 67: 4501-4513 CrossRef Google Scholar
[12] Zhou Z, Yu H, Xu C. Dependable Content Distribution in D2D-Based Cooperative Vehicular Networks: A Big Data-Integrated Coalition Game Approach. IEEE Trans Intell Transp Syst, 2018, 19: 953-964 CrossRef Google Scholar
[13] Xiao H, Chen Y, Zhang Q. Joint Clustering and Power Allocation for the Cross Roads Congestion Scenarios in Cooperative Vehicular Networks. IEEE Trans Intell Transp Syst, 2019, 20: 2267-2277 CrossRef Google Scholar
[14] Selvitopi O, Acer S, Aykanat C. A Recursive Hypergraph Bipartitioning Framework for Reducing Bandwidth and Latency Costs Simultaneously. IEEE Trans Parallel Distrib Syst, 2016, : 1-1 CrossRef Google Scholar
[15] Purkait P, Chin T J, Sadri A. Clustering with Hypergraphs: The Case for Large Hyperedges. IEEE Trans Pattern Anal Mach Intell, 2017, 39: 1697-1711 CrossRef Google Scholar
[16] Chen C, Wang B, Zhang R. Interference Hypergraph-Based Resource Allocation (IHG-RA) for NOMA-Integrated V2X Networks. IEEE Internet Things J, 2019, 6: 161-170 CrossRef Google Scholar
[17] Min H, Lee J, Park S. Capacity Enhancement Using an Interference Limited Area for Device-to-Device Uplink Underlaying Cellular Networks. IEEE Trans Wireless Commun, 2011, 10: 3995-4000 CrossRef Google Scholar
[18] Sun J, Zhang Z, Xiao H. Uplink Interference Coordination Management With Power Control for D2D Underlaying Cellular Networks: Modeling, Algorithms, and Analysis. IEEE Trans Veh Technol, 2018, 67: 8582-8594 CrossRef Google Scholar
[19] Liu F, Hou X, Liu Y. Capacity Improvement for Full Duplex Device-to-Device Communications Underlaying Cellular Networks. IEEE Access, 2018, 6: 68373-68383 CrossRef Google Scholar
[20] Zhang D D, Zhang Z S, Wang X. 全双工通信关键技术研究. Sci Sin-Inf, 2014, 44: 951-964 CrossRef Google Scholar
[21] Zhang G, Yang K, Liu P. Power Allocation for Full-Duplex Relaying-Based D2D Communication Underlaying Cellular Networks. IEEE Trans Veh Technol, 2015, 64: 4911-4916 CrossRef Google Scholar
[22] Xie X, Chen J, Fu Y. Energy efficiency and throughput maximization scheme based on joint antenna selection and beamforming optimization in FD-SWIPT bidirectional relay systems. Sci Sin-Inf, 2019, 49: 1217-1230 CrossRef Google Scholar
[23] Megson G M, Cadenas J. Rapid preconditioning of data for accelerating convex hull computations. Electron Lett, 2014, 48: 270-272 CrossRef ADS Google Scholar
Figure 1
(Color online) Communication scenario
Figure 3
Data structure
Figure 4
(Color online) The diagram of clustering based on HG-C strategy
${V_n}$ receives Beacon information, calculates ${D_{{V_n},{V_m}}}(t)$ by the formula of (9), creates the neighborhood list of ${V_n}$, and initializes $L({V_m},{V_n})=1$, where ${V_m}~\in~{\rm{Nei}}\left(~{{V_n}}~\right)$; |
|
${V_n}~\in~{{\cal~V}_{h'}}$; |
|
Calculate ${\bar~D_{{V_n}}}(t)$ by the formula of (10), and broadcast to ${\rm{Nei}}\left(~{{V_n}}~\right)$; |
Update the neighborhood list, and find out ${\bar~D_{{V_{\max~}}}}(t)$ with the max value of ADLD, ${V_{\max~}}~\in~{\rm{Nei}}\left(~{{V_n}}~\right)$; |
|
${V_n}$ sends an join request to ${V_{\max~}}$, and resets $L({V_{\max~}},{V_n})~=~2$; |
|
Mark ${V_n}$ as a candidate cluster head, and form a coarsening hyperedge; then update the member list of the candidate cluster, and set $L({V_m},{V_n})~=~2$, ${V_m}~\in~c'\left(~{{V_n}}~\right)$; |
|
|
|
$c'\left(~{{V_n}}~\right)$ is a closed hyperedge, and the vehicles in the hyperedge ${{\cal~G}_{{V_n}}}$ are divided into a cluster $c\left(~{{V_n}}~\right)$; |
|
Send the neighbor list and cluster member list to the base station; |
|
Send a join invitation to the corresponding member according to the member list divided by the base station, and then perform step 9; |
|
${V_n}$ joins the corresponding cluster according to the invitation of the cluster head; |
|
|
| Symbol | Definition |
| ${\cal~G}~=~\{~{{{\cal~G}_1},{{\cal~G}_2},~\ldots,~{{\cal~G}_g}~,\ldots~,{{\cal~G}_G}}~\}$ | The number of clusters is $G$ by vehicle division in this cell |
| ${{\cal~D}_g}~=~\{~{{\cal~D}_1^g,{\cal~D}_2^g,~\ldots,~{\cal~D}_d^g~,\ldots,{\cal~D}_{{N_{{C},g}}}^g}~\}$ | The number of FD-D2D links is ${N_{{C},g}}$ in the $g$-th cluster |
| ${\cal~D}_d^g~=~\{~{V_{\rm{h}}^g,V_{m,d}^g}~\}$ | The set of VUE transceivers with $d$-th FD-D2D link in the $g$-th cluster |
| ${{\cal~G}_g}~=~\left\{~{V_{\rm{h}}^g}~\right\}~\cup~\{~{V_{m,x}^g|x~=~1,2,~\ldots~{\rm{,}}{\kern~1pt}~{N_{C,g}}}~\}$ | The set of VUEs in the $g$-th cluster, $V_{\rm{h}}^g$ denotes cluster-head, $V_{m,x}^g$ denotes cluster-member. |
| $c\left(~{V_{\rm{h}}^g}~\right)~=~\{~{V_{m,x}^g|x~=~1,2,~\ldots~{\rm{,}}{\kern~1pt}~{N_{C,g}}}~\}$ | The set consisting of $N_{C,g}$ cluster-members in the $g$-th cluster. |
| ${\cal~C}_d^g{\rm{~=~}}\{~{C_{{\cal~D}_d^g}^1,C_{{\cal~D}_d^g}^2,~\ldots~,C_{{\cal~D}_d^g}^{K_d^g}}~\},{\cal~C}_d^g~\in~{\cal~C}'$ | The set of the $K_d^g$ CUE spectrums of sharing for the $d$-th FD-D2D link in the $g$-th cluster. |
| ${\cal~C}_g^{\rm~h}~=~\{~{{\cal~C}_1^g,{\cal~C}_2^g,~\ldots~,{\cal~C}_{{N_{D,g}}}^g}~\},{\cal~C}_g^{\rm~h}~\in~{\cal~C}'$ | The set of CUE spectrums used by cluster-head multicast in the $g$-th cluster. |
| ${{\cal~D}_{{C_n}}}~=~\{~{{\cal~D}_1^n,{\cal~D}_2^n,~\ldots~,{\cal~D}_{{I_n}}^n}~\},{C_n}~\in~{\cal~C}'$ | The set of ${I_n}$ FD-D2D links reuses the spectrum of ${C_n}$. |
The base station integrates the neighbor list of all candidate cluster heads to establish an adjacency matrix $A$; |
Perform block diagonalization on matrix $A$ to obtain block diagonal matrix $B$; |
Extract the non-zero blocks on the diagonal of matrix $B$ to obtain the adjacency matrix of the related cluster set ${{\cal~G}_{\rm{r}}}{\rm{~=~}}\left\{~{{{\cal~G}_{{\rm{r,1}}}},{{\cal~G}_{{\rm{r,2}}}},~\ldots~,{{\cal~G}_{{\rm{r,}}{N_{\rm~r}}}}}~\right\}$; |
Freely combine the column vectors of the adjacency matrix of the related cluster set ${{\cal~G}_{{\rm{r,}}i}}$, and take out the effective cluster head set ${\cal~C}_{{\rm{r,}}i}^{\rm{h}}$ with full rank; |
Find out the combination ${\cal~C}_{{\rm{r,}}i}^{{\rm{h,min}}}$ with the least number of cluster heads in ${\cal~C}_{{\rm{r,}}i}^{\rm{h}}$; |
|
Find out the combination with the most weighted in ${\cal~C}_{{\rm{r,}}i}^{{\rm{h,min}}}$, and delete other combinations; |
|
Divide VUE to the candidate cluster with the largest connection weight; |
$i~+~~+~$; |
| Parameter | Value | Unit |
| The radius of the cell | 500 | m |
| Shadow fading | 2 | dB |
| The SINR threshold for cellular links | 12 | dB |
| The maximum transmit power for CUE ($P_{\max~}^{C}$) | 23 | dBm |
| The power of Gaussian white noise | $-$174 | mW |
| Interference signal ratio at the base station (${\lambda~_B}$) | 0.01 | – |
| Path loss factors (${\alpha~_0},{\alpha~_1},{\alpha~_2}$) | 3, 4, 3.5 | – |
| The weighting factors for DLD (${\bf{\beta~}}$) | 0.3, 0.1, 0.55, 0.05 | – |
| The number of CUEs | 40, 90, 160 | – |
| The number of VUEs | 500 | – |
| Maximum communication distance between vehicles | 20–300 | m |
| Vehicle speed | 40–50 | km/h |
Download PDF
