1.1. Related Work
1.3. Main Contributions
- We deploy mPCs under coexisting environments of public safety networks (PS-LTE and LTE-R) to assess the proposed scenario’s performance.
- We propose a QoS_mPCD scheme for load balancing and interference reduction that can associate users wisely during a cell range extension (CRE) offset to an mPC according to their connection priority levels, as mentioned in Table 1.
- Since high-priority users can be offloaded to the mPC, we thus employ an eICIC scheme to further decrease interference with the mPC’s offloaded users.
- Unlike fixed small cells, the dynamic ratio of the almost blank sub-frame (ABS) muting ratio is considered in this paper .
- Sine LTE-R is assumed to be the train control signal, zero error tolerance is needed for reliable communications. Therefore, we provide the best resources to the LTE-R user during the resource allocation process.
- We evaluate important performance indexes (throughput, interference, and outage).
2. System Methodology for Coexisting Public Safety Networks
2.1. Priority Gates Model of the PS-LTE Network
2.2. Details of the Network Layout
2.3. Details of the Channel Model
3. Proposed QoS_mPCD Scheme Procedure
|Algorithm 1. Proposed QoS priority-based mPC deployment scheme|
|1: For each BS j ∈ B |
3. BS (K ∈ 11) ← (BS[PS =3, R = 8]))
3: parameters (i, SINR_threshold, cellEdgeUE, cellCenterUE,
LTE RUE, PS UE, mPC UE, HII).
4: Step 1. Context Information Collection
5: Exchange the context information between UE and BS.
6: Count the number of cell-edge users based on SINR threshold.
7: for each UE u ∈ U do
8: Check SINRu,j < SINR_thresholdu,j
9: uedge = uedge + 1
10: end for
11: Users (PS-LTE UE, LTE-R UE, mPC UE) are classified based on priority.
12: Step 2. User Association and Resource Allocation
13: for each UE u ∈ U do
14: Estimate PLu,j and select BS j that maximizes and associates user u with it.
15: Allocate maximum transmission power to users.
16: if SINRLTE-R,j < SINR_thresholdLTE-R,j
17: Use distance-based power control scheme for users to meet LTE-R UE SINR.
18: end if
19: Dynamically adjust RBs during the RBs allocation for mPC user.
20: end for
21: Calculate the load on each BS j.
22. Compute Throughput, Received SINR, and Interference on each UE u, respectively.
23: i = i + 1
24: Step 3. Application of SDN-based eICIC
25: while HII = 0
26: for each M ∈ B in 1st-tier do
27: Use optimum ABS ratio to accordingly transmit ABS.
28: Plan offloaded users’ u in mPC during ABS.
29: end for
30: end while
3.1. Step 1: Context-Information Collection
3.2. Step 2: User Association and Resource Allocation
3.3. Step 3: Application of SDN-Based eICIC
4. System-Level Simulation
Simulation Results and Discussion
Conflicts of Interest
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|User Priority||User Identification||Traffic |
|PS First Responders||PS Emergency: |
PS1 to PS5
|12–14||Barring for Special||High-priority Access|
|10||Barring for Special||Emergency|
|Traffic Model||ARP||QCI||QCI Priority|
|Carrier Frequency||723 MHz|
|System Bandwidth, No. of PRBs||10 MHz uplink, 50 PRBs|
|No. of PS-LTE eNBs||21 Sectors (1-tier, 7 Sites) [Only 3 Inner Sectors in the ROI]|
|No. of LTE-R eNBs||Maximum 2 eNBs/Sector beside the Railway|
|Inter-eNB Distance||PS-LTE eNBs: 4 km / LTE-R eNBs: 1 km|
|No. of mPCs||21 mPCs/Inner Sector in the ROI|
|mPC Mobility Pattern, Speed||mPC Random Walking Model, 3km/h|
|No. of UEs/Sector||mPC UEs: 4/mPC / PS-LTE UEs: 8|
LTE-R UEs: 1 (Control Signal)
|UE Mobility||LTE-R UEs: 250 km/h|
|UE RF Parameters||Max Tx Power: 23 dBm / Noise Figure: 9 dB|
|Path Loss Model||Rural Macro (3GPP TR 36.837)|
|Shadowing||Log-normal Distribution (Mean: 0 dB, SD: 6 dB)|
|Fast Fading||mPC: Winner Ⅱ (D1-Rural Macro)|
LTE-R: Winner Ⅱ (D2a-Rural Macro)
|MCS||MCS 0 ~ MCS 28|
|Transmission Mode||SISO (1 × 1)|
|Thermal Noise Density||174 dBm/Hz|
|Scheduling||Proportional Fair Traffic|
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