The spectrum sharing approach (SSA) has emerged as a cost-efficient solution for the enhancement of spectrum utilization to meet the stringent requirements of 5G systems. However, the realization of SSA in 5G mmWave cellular networks from technical and regulatory perspectives could be challenging. Therefore, in this paper, an analytical framework involving a flexible hybrid mmWave SSA is presented to assess the effectiveness of SSA and investigate its influence on network functionality in terms of independence and fairness among operators. Two mmWave frequencies (28 GHz and 73 GHz) are used with different spectrum bandwidths. Various access models have been presented for adoption by four independent mobile network operators that incorporate three types of spectrum allocation (exclusive, semipooled, and fully pooled access). Furthermore, an adaptive multi-state mmWave cell selection scheme is proposed to associate typical users with the tagged mmWave base stations that provide a great signal-to-interference plus noise ratio, thereby maintaining reliable connections and enriching user experience. Numerical results show that the proposed strategy achieves considerable improvement in terms of fairness and independence among operators, which paves the way for further research activities that would provide better insight and encourage mobile network operators to rely on SSA.
Future mobile data usage and traffic growth are driven by diverse and innovative technologies and services, such as smart cities, health care, autonomous driving, augmented reality, virtual reality, and Internet of things [
Several studies on the assessment of SSA implementation in mmWave communications have recently been conducted. In [
Similarly in [
On the contrary, the authors in [
In the present work, we extend the prior studies detailed above and our work in [
In this section, the proposed analytical framework is divided into four parts to simulate and apply the proposed HMSSA strategy accurately. Details are as follows.
To serve a recognizable area, we consider two tiers of multi-IMNOs given by
Let
In this study, two types of mathematical expressions have been considered. The first is related to basic mobile communications, and the second is related to the mmWave communication system. They are derived and rewritten to model the proposed strategy and the baseline environments optimally. In the context of determining the special behavior of the overall hybrid mmWave spectrum sharing system, capturing one or more snapshots helps in gaining more insight on such approach and its implications on user experience and operator’s revenue. We consider the commonly used close-in reference distance path-loss model [
Path-loss exponent and wavelength parameters.
Frequency bands (GHz) |
|
|
---|---|---|
28 | 3.4 | 10.71 |
73 | 3.3 | 4.106 |
After applying equation (
However, equation (
To assess the feasibility of the proposed HMSSA strategy and characterize the performance of each operator of the multi-IMNOs, we consider the coverage probability as an indicator when
In this section, we present the most important configurations of the proposed HMSSA strategy and its models in detail. Four multi-IMNOs are considered and distributed throughout the simulation area of 1.2 km × 1.2 km. A square grid-based cell deployment topology is used to ensure high-quality network coverage and mimic the quickest possible cell deployment, such as installing cells on street lamp posts. Two access models are suggested for utilization by the four operators. Each operator shares a part of its own allocated spectrum
HMSSA Model 1.
HMSSA Model 2.
In the proposed network configurations, rental or colocated-based mBS mode is suitable for adoption in of HMSSA strategy. In the first mode, each operator allows the rental of a part of its resources and infrastructures that are necessary for enabling efficient spectrum sharing among the multi-IMNOs. In the second mode, each operator has its own mBSs, which are hosted by other operators, provided that it is supplied with a part of the host’s resources, location, cooling, and power supply.
In case of user and mBS association, the UEs that are subscribed to operator UEs can associate with an mBS that offers an exclusive access to 250 MHz at 28 GHz that belongs to the same operator. UEs that are owned by one of a particular pair (OP1 and OP4 or OP2 and OP3, as assumed in this work) can associate with an mBS that belongs to the same or to the second operator of the same pair, which offers a semipooled access of 250 MHz at 73 GHz and vice versa. UEs can associate with an mBS that belongs to OP1, OP2, OP3, or OP4, which offers a fully shared/pooled access of 500 MHz of the spectrum.
In Model 2, the UEs that are subscribed to the operator
The user and cell association decisions are performed by using our proposed scheme, namely, AMMC-S, which relies on providing an optimal cell selection based on the offered signal quality as a function of
User-association options (a) HMSSA Model 1 (b) HMSSA Model 2.
Deploy
Compute the distance Compute Compute Associates Compute
Compute the outage probability of each operator as a function of SIN Compute the average rate distributions of each operator Apply standard deviation formula using equation (
In this section, the performance of the proposed HMSSA strategy is assessed numerically in a typical mmWave scenario that supports two hybrid access models based on mBS distribution and spectrum allocation. Two key performance metrics (i.e., outage probability and average rate distributions) are considered in the evaluation and assessment process. These performance metrics are tailored for the assessment of operator’s independence and fairness, which is the main goal of this study. The related assumptions and simulation parameters are set, as shown in Table
HMSSA and AMMC-S simulation parameters.
Parameters | Settings |
---|---|
mmWave BSs layout | Grid-based cell deployment |
mmWave BSs density | 16 |
# of operator | 4 |
UE layout | Uniform random distribution |
UE density | 160 users |
Simulation area | 1.2 km × 1.2 km |
Intersite distance (ISD) | 300 m |
mBS carrier frequency | 28 GHz and 73 GHz |
mBS transmit power | 30 dB |
Variant of white Gaussian noise | −174 dBm/Hz |
mBS bandwidth | Model 1: 1 GHz for 28 GHz and 73 GHz |
SINR represents a key system interference indicator to account for system interference and analyze its effect on network functionality. Typically, this is obtained by dividing the average received signal power by the sum between the noise power and the interfering power at the UE location as illustrated in equation (
Figure
Outage probability percentage for all operators with different percentiles. (a) 5%, (b) 50%, and (c) 95% (Model 1).
In the proposed HMSSA strategy under Model 1, an additional flexible degree of freedom is utilized to bring advantages from all the available mBSs that operate at different carrier frequencies and spectrum assignments. Therefore, the outage probability is reduced considerably with SINR more than 3 dB of the cell edge user, which outperforms the most related works in [
Model 2 is similar to Model 1. Except for the allocated spectrum amount. Moreover, in Model 2, each user can be associated with any mBS belongs to the same operator or to different operators based on one of the two choices, that is, exclusive access to 250 MHz at 28 GHz and fully shared/pooled access to 500 MHz of the spectrum at 73 GHz carrier frequency or exclusive access to 250 MHz at 73 GHz and fully pooled access to 500 MHz of the spectrum at 73 GHz carrier frequency. Such restrictions in Model 2 help to improve the outage probability of the semipooled spectrum access. The outage probability of all operators that utilize the proposed strategy are kept zero (0%), as shown in Figures
Outage probability percentage for all operators with different percentiles. (a) 5%, (b) 50%, and (c) 95% (Model 2).
Another finding related to the utilization of HMSSA strategy is its ability in reducing the number of mBSs to the half and providing a cost-effective solution for enhancing the spectrum utilization and reducing the CO2 emissions; thus, introducing an environment-friendly wireless communication.
In this section, the average rate of all users that belong to the four operators is analyzed based on Monte Carlo simulations. A total of 160 users for each operator are deployed randomly throughout the simulation area. An average of ten users per mBS is assumed in this work. The channel capacity calculation of each UE is performed using Shannon’s law illustrated in equation (
Average rate distributions of the four operators utilizing HMSSA strategy: (a) Model 1 and (b) Model 2 with different percentile rates.
As previously mentioned, the main difference between models 1 and 2 is the allocated spectrum amount at 73 GHz carrier frequency. Such additional amount provides more flexibility to the operators to allocate a part of their spectrum exclusively to enrich the user experience. However, it is shown in Figure
Figure
Semipooled and HMSSA strategy performance compared to the baseline standalone deployment system (with exclusive access at 28 GHz). X-label indicates the 5th, 50th, and 95th percentiles of the granted amount of spectrum bandwidth under Model 1 and Model 2 configurations.
Baseline system, semipooled, and HMSSA strategy configurations for UE rate evaluation process.
Scenario | Spectrum access strategy | Carrier frequency | Granted amount of bandwidth | mBS deployment configuration |
---|---|---|---|---|
Baseline | Exclusive access | 28 GHz | 250 MHz | Standalone deployment |
|
||||
Model 1 | Semipooled | 28 GHz and 73 GHz | 500 MHz at both 28 GHz and 73 GHz for each pair (i.e. OP1 and OP4) | Dual deployment |
HMSSA strategy | 28 GHz and 73 GHz | 1 GHz at 28 GHz and 73 GHz | Hybrid deployment | |
|
||||
Model 2 | Semipooled | 28 GHz and 73 GHz | 500 MHz at 28 GHz and 750 GHz at 73 GHz for each pair (i.e. OP1 and OP4) | Dual deployment |
HMSSA strategy | 28 GHz and 73 GHz | 1 GHz at 28 GHz and 1.5 GHz 73G Hz | Hybrid deployment |
Three scenarios are applied for the evaluation procedure, the baseline standalone deployment system with 16 mBSs for each operator. In this scenario, a particular UE that belongs to an operator (i.e., OP1) has the right to associate with only the mBS that belongs to its own operator. While in the semipooled scenario, 16 mBSs are divided into two groups; the first group with eight mBSs operate at 28 GHz carrier frequency and the second group with eight mBSs operate at 73 GHz carrier frequency, where the UEs have the right to associate with mBS that operates at 28 GHz carrier frequency or with mBS that operates at 73 GHz carrier frequency that belongs to its own operator or to its own pair operator based on the highest
According to the implementation and evaluation of the above scenarios, it is notably that the proposed semipooled and HMSSA strategy (Model 1) enhances the average rate of the users by more than 143% and 193%, respectively; whereas under (Model 2) configurations, the proposed semipooled and HMSSA strategy enhances the average rate of the users by more than 194% and 229%, respectively. The increase in the UE enhancement rate under Model 2 configurations can be attributed to the extra amount of the allocated bandwidth to the participated operators, specifically in the performance of semipooled (500 MHz at 28 GHz and 750 GHz at 73 GHz for each pair (i.e., OP1 and OP4)), as shown in Table
These observations indicate that the utilization of such hybrid dynamic spectrum access strategy will pave the way for non-standalone cell deployment with non-standalone licensed spectrum access because of its ultraflexibility and capability that offers an optimal UE-mBS association that helps in maximizing the user experience.
Another important observation is that increasing the amount of allocated spectrum bandwidth at 73 GHz carrier frequency to operate as another exclusive right access for UEs under (Model 2) assumptions does not lead to much improvement in the UE rate. This can be attributed to the fact that UEs tend to associate with mBS that operates under exclusive right access at 28 GHz or 73 GHz which has the highest
To sum up, the reported enhancement in the performance of UE rate can be considered as an encouraging step to enable the success of SSA in 5G mmWave cellular networks with less mBSs density and small amount of spectrum bandwidth compared to the most related works in [
Assessing the operator’s independence and fairness based on the signal quality (outage probability) and the average rate distributions of particular subscribers that belong to an operator
Particularly, in this work, characterizing OP1 as an independent operator implies that its performance is not influenced by other operators (e.g., OP2, OP3, and OP4).
Additionally, the term "fairness" is defined as the ability to handle all operators equally or in a manner that all operators are treated without bias.
The coverage or average rate probability of user
Considering
More specifically, either coverage or average rate probability of any operator (OP1 and OP2 as an example) is independent if and only if
This condition can be applied for other operators to assess their independence.
By substituting the coverage probability of each user
Recall equation (
As
In terms of fairness, standard deviation formula is utilized to assess the differences among the operators that share the spectrum in terms of average rate distributions.
The average rate percentages of all operators are relatively close to one another. The small margin in the average rate probability among all operators indicates that the resources are evenly allocated to the users regardless of which operator the users belong to.
The standard deviation of the average rate of a set of operators is expressed as follows:
As shown in Table
Margin percentage and standard deviation of the proposed HMSSA strategy (Model 1 and Model 2).
HMSSA configurations | Percentiles (%) | HMSSA margin in terms of |
|
Average rate (Mbps) | ||||
---|---|---|---|---|---|---|---|---|
Fully pooled access (%) | Exclusive or semipooled access (%) | OP1 | OP2 | OP3 | OP4 | |||
Model 1 | 95 | 0.845 | 1.691 | 4.0169 | 1005.5 | 1004.4 | 1013.1 | 1005.5 |
50 | 2.548 | 5.097 | 6.3713 | 457 | 462 | 472.3 | 463.5 | |
5 | 7.662 | 15.2 | 1.9155 | 44.3 | 45.8 | 47.7 | 43.3 | |
|
||||||||
Model 2 | 95 | 1.362 | 2.366 | 6.4727 | 1010.6 | 1026.3 | 1019.7 | 1017.5 |
50 | 2.082 | 4.165 | 5.2066 | 506.2 | 509.9 | 513.9 | 501.7 | |
5 | 1.876 | 3.752 | 0.4690 | 50.1 | 51.2 | 50.6 | 50.9 |
In this study, we investigate the implementation of a flexible HMSSA strategy by analyzing various practical aspects, such as spectrum access strategies, various rate percentiles, and two mmWave frequency bands with different characteristics and spectrum bandwidth. An optimization framework was developed to enable operators to harvest the gains from several considerations, such as hybrid spectrum integration, resource sharing strategy, as well as user-mBS association. Moreover, a detailed analytical and discussion is presented to assess independence and fairness among operators under the proposed HMSSA strategy assumptions. The numerical results show that the integration of a hybrid spectrum (i.e., exclusive, semipooled, and fully pooled) strategy can provide a considerable solution to overcome mutual interference issues, thereby reducing outage probability to zero with (SIN
The data used to support the findings of this study are included within the article.
The authors declare that there are no conflicts of interest regarding the publication of this article.
The authors gratefully acknowledge the UTeM Zamalah Scheme, Universiti Teknikal Malaysia Melaka (UTeM), and the supports from the Centre for Research and Innovation Management (CRIM), Centre of Excellence, Universiti Teknikal Malaysia Melaka (UTeM).