Abstract
Utilization of unlicensed spectrum under licensed assisted access ensuring fair coexistence with WiFi networks is a good solution to address immense usage of mobile data. Radio communication operation of LTE in unlicensed frequency band is referred as LTEunlicensed (LTEU) or LTElicensed assisted access. In this paper, we consider a HGNW in which coverage area of WirelessFidelity (WiFi)’s Access Point is integrated within the LTEU small base station’s cellular network coverage area. To overcome the disadvantages of existing LTEU technics like carrier sense adaptive transmission and listen before talk, we proposed a new methodology i.e., sense before transmit in this paper by adopting a transmit power control mechanisms using reciprocity theorem based on the channel state information to assign the secondary carriers in the uplink as well as in the downlink directions in the unlicensed spectrum to carry the traffic. In our proposal, LTEU users are allowed to use the unlicensed spectrum provided that the interference produced at WiFi users due to LTEU activities is remained below a certain threshold. We evaluated the performance of proposed network model in terms of outage probability and achievable throughputs.
1 Introduction
To address the consumer driven demand as well as network driven demand, the extension of LTE/LTEA cellular system operations to unlicensed spectrum is given renaissance for the modern way of wireless radio communication system. Assurance of faire coexistence between LTEU and other networks which are operated in unlicensed bands such as WiFi (802.11), Bluetooth (802.15.1) and ZigBee (802.15.4) is a major concern. Performance of these networks should not be degraded due to LTEU operations and friendly coexistence on 5 GHz band is the ongoing discussion on the 3GPP [1]. Among them WiFi is the most successful technology to serve the wireless broad band coverage in a local area and operates in 2.4 GHz and 5 GHz spectrum bands. Recently after FCC freed 295 MHz bandwidth in the Unlicensed National information Infrastructure (UNII) band, over 400 MHz unlicensed spectrum is available for commercial use. A lot of research has been proposed based on either listen before talk (LBT) [2,3,4,5,6,7,8] or duty cycle based (CSAT) [9,10,11,12] approaches to carry the LTEU activities in unlicensed spectrum. In LBT method similar to the WiFi carrier sensing, it senses the channel before transmitting the data which is required for few markets like in Japan and Europe, on other hand in the CSAT mechanism irrespective of channel state, LTEU transmissions will be scheduled as per the desired duty cycle which is suitable for China, U.S. and South Korea as these do not require any LBT. Hence changes to LTE protocol specifications are required for LBT mechanism only. Available bands in 5 GHz spectrum across different countries is shown in the Fig. 1 [13].
An inter RAT request based approaches are proposed in [11] to notify the upcoming measurement gaps on unlicensed spectrum for friendly coexistence in unlicensed spectrum using CSAT approach. We can find a wellpresented comparison between CSAT and LBT mechanisms in [12], in this the author showed that the same level of fairness to WiFi due to these methods under appropriately configured scenarios but for the shorter transmission times, CSAT results in the lower throughput, higher collision probability and longer WiFi packet delays. The authors proposed a fair and quality based unlicensed spectrum sharing between WiFi and femtocell networks in [14] but changes to existing WiFi network is required. In [15], the author discussed achievable sumrate in standalone mode (we will discuss clearly about standalone mode in the Sect. 2) using the dual mode small cell base station without considering the WiFi fairness. In [16], the author estimated the contention window size by estimating the number of STAs from collision probability to improve the throughput. A channel reservation mechanism based on synchronous and asynchronous approaches has been proposed in [17] to improve the coexistence.
From the above discussion, we can conclude that by using CSAT approach there must be interference during on duration and in case of LBT approach, we can’t use the spectrum if the WiFi user is detected as active. To address these challenges, we proposed a new approach “sense before transmit” to use the unlicensed spectrum in this manuscript. The major contributions of this paper are listed below:

In the considered HGNW model, WiFi network is integrated within the LTE SBS coverage area to realise the LTEU system.

We proposed sense before transmit (SBT) method in this paper by adopting a transmit power control mechanisms using reciprocity theorem based on the channel state information to assign the secondary carriers.

We propose CA approaches of LTE in unlicensed bands without degrading existing WiFi performance.

We restrict the interference generated to WiFisystem due to LTEU based on the channel state information by controlling transmit power to satisfy the QoS of WiFi user.

Simulation and analytical models are proposed for WiFi and LTEU users constrains.

We contemplate the performance evaluation metrics in terms of the outage probability of LTEU user under WiFi user outage constrains.

The effect of the scaling factor of tolerable threshold and outage constraint impacted by WiFi system on LTEU user’s performance.
The remaining sections of the paper are prepared as follows: Sect. 2 enlightens the system architecture proposed and different modes of unlicensed LTE operations including 3GPP certified modes. In Sect. 3, we discuss the performance analysis in terms of metrics throughput and outage probability. Finally, the results and discussions are covered in Sect. 4 followed by conclusion of the paper in Sect. 5.
2 System Model
The integrated HGNW system model assumed is as shown in Fig. 2, in which a WiFi AP is collocated in the coverage area of LTEU SBS. It is considered that the links among the LTEU SBS or WiFi AP and users are complex Gaussian random variables, which are identically distributed independent variables. The cellular users and WiFi users are represented with different symbols as shown in the figure.
Before extending our proposed approach to LTEU, we discuss briefly about the carrier aggregation (CA) of LTEadvanced (LTEA) [18] system. Whenever an EUE establish a session with cellular base station, in general uplink and downlink channel pair will be assigned for transmission in both the directions so called uplink primary component carrier (UL PCC) and downlink primary component carrier (DL PCC) respectively. Jointly these carrier components called as PCC. Based on the traffic load and QoS requirements, EUE can be attached with additional one (or more) CC, called as secondary CC (SCC) which corresponds to the secondary serving cell (SCell). Max we can use up to 5 SCC’s [19] and with different combinations of bandwidths in inter CA or intra CA which is out of scope of this paper. The PCC serves as an anchor CC for the user and it is used for basic connectivity functionalities. The SCCs carry only user data and dedicated signalling information—PDSCH (physical DL shared channel), PUSCH (physical UL shared channel), and PDCCH (physical DL control channel). As the user connection greatly depends on PCC and it to be robust in both the UL/DL directions and to provide ubiquitous coverage it must be in licensed band to guarantee the QoS. For SCCs, unlicensed spectrum can be employed by CA method of LTEU in one of the three modes whenever the achievable data rates using licensed spectrum is not enough to serve the EUE. These three modes are:

1.
Supplemental downlink mode: In this mode, an extra dedicated downlink path i.e., SCC is assigned in unlicensed spectrum to carry the data in downlink only. While the control channels information and the UL/D L transmissions of PCC remains in the licenced spectrum. The pictorial representation is shown in Fig. 3a for FDD and TDD scenarios.

2.
Carrier aggregation mode: In this mode, a separate TDD channel is assigned in unlicensed spectrum to carry the both UL and DL data traffic. Similarly in this mode also, the control channels remain in the licensed bands. Figure 2c shows the graphical representation.

3.
Standalone mode: All channels i.e., UL, DL data traffic channels of all carriers and control channels are assigned in unlicensed spectrum in this mode. As it is not using any licensed spectrum there is no guarantee for QoS. The representation is shown in Fig. 2b.
Out of these three modes, only the supplemental downlink and the carrier aggregation modes are supported by 3GPP release12 [20] as in the standalone mode the transmissions using unlicensed spectrum in UL as well as in DL is not guaranteed the QoS. In supplemental and carrier aggregation modes it is not the case as the control signals and PCC will be assigned in the licensed band and in the unlicensed band SCCs will be assigned.
We assumed that the air interference links Among the SBS, WiFi AP and EUEs are independent complex Gaussian random variables and the channel coefficient of intra and inter licensed/unlicensed spectrums are \(g_{ll}\),\(g_{uu}\),\(g_{ul}\) and \(g_{lu}\) respectively. The additive noise is considered with sigma variance and mean zero. The received signal at LTEU user is given by,
where the \(s(n)\) is the transmitted signal in the unlicensed spectrum and it is assumed as an iid random process with mean 0 and variance \(\sigma_{s}^{2}\). Furthermore, \(s(n)\) is independent of \(w(n)\).
3 Performance Analysis
In this section, we analyse the performance of LTEU in the presence of the WiFi network coverage. The main fundamental necessity of LTEU/WiFi coexistence is, activities of LTEU network in the unlicensed spectrum shouldn’t create interference to WiFi system. WiFi system uses carrier sense multiple access/ carrier avoidance (CSMA/CA) as channel access technology which can be considered as time division duplexing (TDD) because discontinuous transmission (DTx) and discontinuous reception (DRx) activities occurred in the same unlicensed band. So using channel reciprocity [21] to our proposed system model to overtake the feedback problem, we propose a transmit power control (TPC) strategy for LTEU carriers which are operated in the unlicensed band, i.e.

1.
Interference power sensed at the WiFi user should be always less than the threshold limit \(P_{\lambda }\) due to SCC assignments in the unlicensed band which is given by Eq. (2).
$$E(g_{lu} *P_{LTE  U} (n)) \le P_{\lambda }$$(2)Here \(P_{LTE  U}\) denotes the transmit power of the LTEU system, \(P_{\lambda }\) is the average interference constraint to the WiFi network, and E (.) is the expectation.

2.
Once we have decided the interference threshold, we can estimate the allowable transmit power of a LTEU based on CSI by measuring the channel coefficient i.e.,

a.
When LTEU user is within the interference range of WiFi user then the allowable Tx power of LTEU user in this case can be expressed as [22],
$$P_{LTE  U} = \frac{{P_{\lambda } }}{{\hat{g}_{lu} }}$$(3)where \(\hat{g}_{lu}\) is the actual estimated channel gain at LTEU user.

b.
When it is detected as free medium, LTEU user can transmit with desired closed loop power control set by cellular BS.

a.
So, the allowable transmit power of LTEU is given by,
In practical, as the channel information estimation of links between LTE user and WiFi network is imperfect, we consider power control parameter \(\gamma\) (0 < \(\gamma\) < 1) to assure the faire coexistence. By considering the power control parameter the maximum transmittable power by LTEU system is given by
We can regulate the maximum allowable transmit power for a desired outage constrain at WiFi user by calculating the \(\gamma\) as follows,
From the above equation we can find the maximum possible value of \(\lambda\) so that maximum allowable \(P_{LTE  U}\) can be calculated. Having calculated the allowable transmitted power, we can now analyse the two metrics namely throughput and outage probability of SCC assignments in unlicensed spectrum.
3.1 Throughput
The mean capacity achieved by SCC of LTEU system via unlicensed system can be calculated as follows:
where “W” is the unlicensed spectrum band width used, \(\chi\) is the signaltointerferenceplusnoise ratio and it’s pdf and cdf functions are denoted by \(f_{\chi } (x)\), \(F_{\chi } (x)\) respectively. Let the power transmitted by LTEU in unlicensed spectrum is \(P_{LTE  U}\) and \(P_{W}\) is the power transmitted by WiFi system, then the throughput in case of (i) maximum transmittable power and (ii) restricted power transmit case can be calculated as follows:
Casei
When LTEU is allowed to transmit with maximum power, under the considered case the \(F_{\chi } (x)\) can be expressed as,
Thus, the capacity is expressed as,
Using [23] and after some algebra, (11) can be expressed as,
Caseii
when LTEU user is allowed to transmit with restricted power in which the CDF can be expressed as,
We can reduce above equation as,
Thus, the capacity is expressed as,
3.2 Outage probability
Outage probability is defined as the probability that the mutual information rate is less than the minimum required threshold information rate. Here we assume that the LTEU has expected this threshold value as R for the faithful communication and an outage will be resulted if the information rate is less than the desired rate R. Therefore, the outage probability of LTEU in the integrated system for two mentioned scenarios can be expressed as:
Casei
The LTEU will be allowed to transmit with maximum power during absence of the WiFi user i.e., no WiFi user is detected as active. Therefore, the outage probability in this scenario can be found as follows,
Caseii
In this case the outage probability can be expressed as,
where \(a = \frac{{(2^{R}  1)}}{{\gamma *P_{\lambda } }}\), \(\alpha = \frac{{N_{o} a + 1}}{{1  \sigma_{e}^{2} }}\), \(\beta = \frac{1}{{P_{W  U} a}}\) and \(Ei(x)\) is the exponential integral function which can expressed as, \(Ei(x) = \int\nolimits_{0}^{\alpha } {\frac{{e^{  t} }}{t}dt}\) [23].
4 Results and Discussion
In this section, we have evaluated analytical and simulation results based on above investigation using MAT LAB test bed. The following default values of the parameters are considered in this: \(f_{s}\) = 5.6 MHz, \(P_{\max }\) = 20 dB, outage constrain delta = 0.01, \(I_{th}\) = 10 dB, SCC B.W = 20 MHz, data rate = 1, error variance = 0.01 and we assume the noise variance of AWGN as unity.
In Fig. 4, we represented WiFi user’s outage probability as a function of scaling factor of LTEU transmit power for several values of correlation coefficient which are indicated by legends r = 0.2, r = 0.6 and r = 0.9. From the plot, it is clear that the outage probability of WiFi user increases as the value of n increases while other parameters are kept constant and the effect of correlation coefficient on the outage probability is also depicted. With the increased value of n, the effective transmitted power of LTEU user is increased so the interference at WiFi user. With the higher correlation coefficient value i.e., estimation of CSI closer to the perfect case, allows higher transmit power level of LTEU user which reduces outage probability. So, from the graph one can decide LTEU transmitted power by choosing a proper value of n to restrict the desired outage constrain at WiFi user.
The throughput of LTEU system for case1 is shown as a function of transmitted power in the Fig. 5. Legends in the graph indicates simulation and analytical results for N = 1 and 5. Figure 5 depicts the variation of throughput of LTEU as a function of its Transmitted power. As the throughput is the function of SNR value and it increases with Transmitted power of the EUE of the interest, throughput is increasing with the transmitted power. It is also observed that the effect of the background noise as well from the graph and it decreases the throughput as overall SNR value is decreased with the increment of background noise.
In Fig. 6, the throughput of LTEU user is shown as a function of interference limit \(I_{th}\) for caseii. As shown in the figure the throughput of LTEU user is increasing monotonically with the allowable interference threshold value at WiFi user. In the figure, the legends indicate analytical and simulation results for different values of scaling factor (n) and correlation variance. One can observe the effect of \(I_{th}\) from the graph that the throughput of LTEU user is increased with interference limit by keeping other values constant. Increase in interference limit is nothing but allowing EUE of interest to transmit with higher Tx levels. As it is allowed to transmit with the higher Tx levels, it’s achievable throughput values also increases for fixed values of n and p. It is also observed that the gain in the throughput of LTEU user with incremented n and p values. However further increase in Tx level doesn’t produce any significant improvement as it achieves saturated throughput.
In the Fig. 7, the analytical and simulation results of the outage probability is shown as the function of the Tx power of EUE with separate legends. It is observed that the outage probability of LTEU in unlicensed spectrum decreases with the transmit power. As we already discussed in the earlier plots, the achievable throughput will be increased if the Tx power increases. Hence the increment of Tx power results in lower outage probability. The effect of background noise is also depicted in the graph. The signal quality at the receiver will be worsen with the increased \(N_{o}\) is the reason for the further increased outage probability.
In Fig. 8 the Outage probability in caseii is represented as the function of Interference threshold for the proposed TPC methodology. Legends in the plot indicate the simulation and analytical results for the different set of r, p values. In all the cases, the outage probability is decreasing with the interference threshold as shown in the figure. As the interference threshold is increased, EUE is allowed to transmit at the higher power levels is the reason for reduction of outage probability. The considered higher values of n, p result in lower outage constrain. With the increased value of n, EUE can transmit at higher levels for the same given interference threshold value and the higher value of p indicates the estimated channel is close to perfect. Hence these values together increase the SNR value and lower the outage probability.
5 Conclusion
In this paper, we have evaluated the channel access mechanism for the LTEU SBS to utilize the unlicensed spectrum by developing the SBT approach without modifying the existing WiFi protocol. Under the condition of EUE association, we categorise two practical scenarios based on channel reciprocity theorem in which the way of utilizing the unlicensed spectrum is defined and we have derived a closed form expression for the outage probability and achievable data rates for each case. We have contemplated the performance evaluation in terms of allowable interference threshold, outage constrains and maximum transmittable power of LTEU. With the increase in the channel estimation error, the LTEU users performance will be degraded. From the simulation results, it is observed that the higher interference threshold reduces the LTEU outage, the WiFi user’s interference is found to degrade the LTEU performance and the outage of LTEU user increases with increase in WiFi user interfering power. The comparison of the analytical and the simulation results hold good and well agreed.
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Reddy, S.R.V., Roy, S.D. SBT (Sense Before Transmit) Based LTE Licenced Assisted Access for 5 GHz Unlicensed Spectrum. Wireless Pers Commun 119, 2069–2081 (2021). https://doi.org/10.1007/s11277021083181
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DOI: https://doi.org/10.1007/s11277021083181
Keywords
 LTEU small base station (SBS)
 Channel state information (CSI)
 Enhanceduser equipment (EUE)
 Carrier aggregation (CA)
 Listen before talk (LBT)
 Carrier sense adaptive transmission (CSAT)
 Throughput and outage probability