Broadcast-Multicast Single Frequency Network Versus Unicast in Cellular Systems

Broadcast-Multicast Single Frequency Network versus Unicast in Cellular Systems

Juan Vargas∗ ,Cedric´ Thienot ∗, Christophe Burdinat ∗, Xavier Lagrange ∗Enensys Technologies, Rennes, France {juan-carlos.vargas-rubio, cedric.thienot, christophe.burdinat}@enensys.com IMT Atlantique/IRISA, Rennes, France [email protected]

Abstract—Video is an important factor of the load in cellular Release 10 introduced the eMBMS counting procedure. It networks due to the growing popularity of streaming and allows the network to count the number of users interested linear services. In unicast transmission mode, the same data is in an MBMS service in a given SFN area [4, Chapter 11]. transmitted as many times as the number of receivers demanding the same video content. Conversely, in broadcast transmissions Release 12 Introduced eMBMS operation on demand (MooD) using the Single Frequency Network (SFN) technique, a set of that allows automatic MBMS activation and deactivation. The base stations perform synchronized transmission of the same option to perform BC transmission in only one cell was waveform to a potentially infinite number of users. The objective presented in release 13 as Single-Cell Point-to-Multipoint (SC- of this study is to compare the performance of unicast and PTM) [5, Chapter 19]. Release 14 introduced Further evolved broadcast. More precisely, we determine the minimum number of users downloading the same data from which a broadcast MBMS (FeMBMS). It included a receive-only mode to allow transmission is more efficient than multiple unicast transmissions. devices without operator subscription to receive broadcast In this paper, a model to calculate the Signal-to-Interference-plus- content. Other options as 100% carrier allocation and 200 µs Noise Ratio (SINR) in unicast and broadcast modes is presented, Cyclic Prefix (CP) were enabled [3]. In release 16, a further considering Poisson distributed base stations, path loss, fading, study item has evaluated the ability of FeMBMS to support shadowing, trisectored antennas, SFN with a different number of base stations and beamforming in unicast mode. Results show an SFN of cells with a coverage radius of up to 100 km that even when an SFN is formed by just 2 base stations and (implying even longer CP) and mobile reception with speeds unicast transmissions are performed using beamforming with 8 up to 250 km/h [6]. 3GPP is considering in release 17 a mixed antennas per sector, broadcast outperforms unicast when there unicast/multicast mode to dynamically switch between both are at least 8 users per cell demanding the same content. transmission modes [7]. Index Terms—Cellular Networks, SFN, Broadcast, Unicast, Beamforming, Trisectored antennas, video delivery. In SFN, the network region in which BSs are synchronized to achieve an SFN transmission is called an SFN Area. It is generally a compact area without any hole, see Fig. 1. An I.INTRODUCTION SFN transmission is seen by a receiver as a single transmission Video transmissions will account for 79 percent of the suffering from multipath propagation. However, BC transmis- world’s mobile data traffic in 2022 [1]. In order to provide a sions do not benefit from link adaptation. Therefore, they are good quality of service, operators are searching for alternatives aimed to cover the users with the worst channel conditions, to reduce the radio resource utilization when several users are i.e. users at the border of the SFN area. On the other hand, demanding the same video content on a given geographical Unicast (UC) transmissions benefit from link adaptation and area. Broadcast (BC) transmission using the Single Frequency the possibility of using the beamforming technique but the Network (SFN) technique is an interesting solution to this same data is transmitted as many times as the number of users problem. Using this technique, multiple Base Stations (BS) demanding the same service. transmit identical waveforms at the same time to a potentially The problem is to identify at which point it becomes more infinite number of users, thus reducing the interference. When efficient to transmit in BC mode rather than in UC mode a video is very popular, contents can be pushed via broadcast from a resource utilization perspective. A user with a very low transmission and then stored in the cache of the receiver, even SINR can degrade the performance of BC transmissions. On prior to user demand [2]. Thus, offloading the network and the other hand, transmitting the same content several times in maintaining good service quality. the same region is inefficient. The difficulty lies in the various The Third Generation Partnership Project (3GPP) has stan- irregularities in cellular systems, such as different BS densities, dardized BC solutions since release 6 with the Multimedia number of users demanding the same service, user’s location, Broadcast Multicast Service (MBMS) interface specification size of the SFN area, antennas capabilities, propagation effects, for 3G. It was conceived as a pre-planned and static mobile TV etc. service based on SFN transmission [3]. In release 9, evolved In [8], the authors propose a method to identify when it MBMS (eMBMS) appeared as the LTE version of MBMS. is convenient to change from UC to BC transmission based on the user with the lowest SINR. In [9], the authors prove 20 the benefits of multicast over unicast when the average channel BS in the SFN area quality is good enough. However, both of these works consider 15 Interfering BS BC transmission only in one cell. Models to calculate the SINR for a receiver in a SFN are presented in [10] and [11]. 10 In [10] the model is based on a regular hexagonal lattice. On 5 the other hand, authors in [11] consider Poisson distributed BS and use stochastic geometry to derive an approximation 0 of the coverage probability in an infinite SFN network, but -5 Y coordinate [km] they consider omnidirectional antennas and do not consider -10 shadowing. In this study, a model to calculate the SINR for a receiver -15 in UC and BC mode is developed. Additionally, a model to -20 compare their efficiency in terms of resource utilization is -20 -15 -10 -5 0 5 10 15 20 provided. We use a Poisson Point Process (PPP) distribution X coordinate [km] for the BS location, instead of the traditional regular hexagonal Fig. 1. SFN area of 100 BS on a surface where BS are located following a lattice. This choice has been justified in [12] and [13]. We con- PPP with density λ = 0.25 BS/km2. sider the characteristics of both transmission modes as well as path loss, fading, and log-normal shadowing. Utilizing Monte Carlo simulations we calculate the probability distribution of where fc is the carrier frequency in GHz and rg the SINR for each case. Then, we obtain an estimation on is the receiver-BS geographical distance in km. For a the number of users per BS demanding the same service from given frequency, (1) can be written as a function of which the BC mode becomes more efficient that the UC mode, the path loss exponent α and the path loss factor k as PLdB = α10 log rg − 10 log (k), which in linear scale is even when using beamforming. α 10 10 rg The remainder of this paper is structured as follows. Section PL = k . II presents the mathematical equations used to model the C. Fading and Shadowing system, section III presents the derivation of the SINR for UC and BC transmission modes. In section IV we develop Fading is modeled as an exponential random variable (r.v.) the model used to compare the efficiency of both transmission h with unit rate. Shadowing is modeled as a log-normal r.v. modes and the numerical results are analyzed in section V. exp(χ), with χ following a normal distribution with zero mean Finally, the conclusions are presented in section VI. and variance σ2. Shadowing is usually characterized in terms 10 of the standard deviation of its dB-spread σdB = ln 10 σ. II.SYSTEMMODEL Additionally, the r.v. χ is composed of a correlated part We base our analysis on the reference model proposed (χc), to account for the obstacles close to the receiver, and by the 3GPP in [14]. The propagation model is based on a non-correlated part (χi), corresponding to the obstacles 2 2 2 Okumura-Hata-Cost231 with shadowing and fading. Three- independent for each BS, then, χ = χc +χi and σ = σc +σi . 2 sector base stations are considered with adapted antennas. The σc The correlation coefficient is defined as ρ = 2 . 3GPP model considers a limited number of base stations on σ a perfect hexagonal grid. To take into account the irregularity D. Shadowing effect on the BS density of operational networks, we consider BSs located following a The received signal power (Prx) from a BS i considering PPP of density λ as shown in Fig. 1. It is assumed that all BS path loss, fading, shadowing and unit gain antennas, can be use the same transmission power and carrier frequency. calculated as A. Noise Power −α Prx = Ptxkrg,i exp(χc) exp(χi)hi, (2) The noise power (PN ) is the aggregation of the thermal noise spectral density for the given occupied bandwidth (W ) where Ptx is the BS transmission power. By rewriting (2) as 1 − χi −α χc and the receiver noise figure (γ) and its value in dB is Prx = Ptxk(e α rg,i) e hi, the uncorrelated shadowing calculated as PNdB = γ + 10 log10(kBTkW ), where kB can be considered as a random displacement of the BS original 1 − χi is the Boltzmann’s constant and Tk is the receiver system location changing the distance rg,i to ri = e α rg,i. Then, temperature. according to [15, Lemma 1], the new PPP defined by the transformed points ri is also a homogeneous PPP with density B. Path Loss σ2 0 2 i λ = λe α2 . In the remaining of this document, ri refers to The path loss in dB (PLdB), valid for carrier frequencies the distance between the receiver and a BS i considering the between 1400 MHz and 2600 MHz, is calculated as 0 modified BS density λ , then

fc −α χ PLdB = 128.1 + 37.6 log (rg) + 21 log ( ), (1) P = P kr e c h . (3) 10 10 2 rx tx i i E. Trisectored Antennas to the modified distance ri. It is assumed that the receiver Consider that each sector has a 120◦ width. The antenna is synchronized with the serving BS which is located at a ri−rs gain for each sector in the direction θ, measured from the distance rs. Thus, τi = c , where c is the speed of light. antenna boresight, can be calculated as stated in [14], as Based on the model presented in [19], the usefulness of the follows: signals received during an SFN transmission can be derived as ( ) θ 2 GdB(θ) = GA − min 12 ,GFB , (4) θ3dB  1 0 ≤ r − r ≤ cT  i s CP TCP rs−ri 2 δi = (1 + T + cT ) cTCP < ri − rs ≤ cTf , (6) where GA is the antenna gain in the boresight direction in u u  0 ri − rs > cTf dB, θ3dB is the 3 dB beam width, GFB is the antenna front to −180◦ ≤ θ ≤ 180◦ back ratio and . In this study it is assumed where Tu is the useful symbol time and Tf = TCP + Tu is ◦ that the antenna boresight angles for the three sectors are 30 , the total OFDM symbol time. 150◦ and 270◦ counterclockwise for all BSs. III.SINRDERIVATION F. Beamforming The beamforming technique uses an array of antennas to In this section, we derive the expressions of the SINR for increase the beam gain in a certain direction. This study a receiver in BC mode and UC mode based on the model considers BS with trisectored antennas in which each sector presented in section II. has a linear array of M antennas capable of performing A. SINR in unicast mode beamforming in unicast mode. The direction towards which the beam is pointed is characterized by the steering angle φ In UC mode, only the serving sector provides useful signal which is measured from the antenna boresight. The expression power (PUC ). The other two sectors of the serving BS and to calculate the array gain for one sector in the direction θ can all sectors from other base stations generate interference be derived from [16, 17, 18] as (IUC ). Then, the SINR for a receiver in unicast mode can be calculated as ( 2 π sin (M 2 (sin(φ)−sin(θ))) 2 π G(θ) θ 6= φ ˆ A(θ, φ) = M sin ( 2 (sin(φ)−sin(θ))) , (5) PUC PUC SUC = = , (7) MG(θ) θ = φ PN ˆ PN + IUC χ + IUC Ptxke c where G(θ) is given by (4) and −60◦ ≤ φ ≤ 60◦. where PÛC and IÛC are the signal and interference power χc G. SFN Model normalized by the factor Ptxke and are calculated as An SFN Area is composed of a number of BS (N ) SFN ˆ −α that form a compact cluster and can perform synchronized PUC = rs hs G(θs,t), (8) transmission of the same waveform. In this study, we consider and a large surface over which a certain number of BS (NBS) are located following a PPP of density λ. Two cases are studied. In 3 3 ˆ −α X X −α X the first one, we assume a very large SFN Area, e.g. country- IUC = rs hs G(θs,j) + ri hi G(θi,j), (9) wide deployment. Thus, all BS in the surface belong to the j=1/j6=t iψ/i6=s j=1 BC area (NSFN = NBS) and the SINR perceived by a user where ψ represents the PPP and the sub-indexes s and t placed in the origin of the plane is considered as a reference represent the serving BS and the serving sector respectively. for all users, see [13, Remark 1.6.6]. In the second case, we consider a local SFN Area with a limited number of BS B. SINR in unicast mode considering beamforming (N < N ) defined as the N BS closer to the origin SFN BS SFN It is assumed that the beam of the serving sector is steered of the plane. The BSs outside the BC area are considered in the direction of the receiver, then θ = φ. The SINR for a as interferers. In this case, users are randomly placed in the receiver in UC mode when considering beamforming can be SFN area, instead of the origin, to take into account the cases calculated as when the receiver is at the border of the BC area and perceive a smaller SINR. PUCb PÛCb SUCb = = , (10) H. Interference in broadcast mode PN ˆ PN + IUCb χ + IUCb Ptxke c Consider a BS in an SFN area located at a distance r from i ˆ ˆ a receiver. Depending on the delay time with respect to the where PUCb and IUCb are the signal and interference power χc serving BS (τi) and the length of the Cyclic Prefix (TCP ), normalized by the factor Ptxke and are calculated as the received signal power can be useful, partially useful or ˆ −α interference. Notice that we approximate the real distance rg,i PUCb = rs hsMG(θs,t), (11) and B. Resource utilization in unicast mode 3 −α X The Unicast mode uses link adaptation. Thus, to calcu- IÛCb = r hs A(θs,j, φs,j) s late the average number of RB per time slot used per UC j=1/j6=t (12) N 3 user ( RBUC ), the expected value is estimated. Given that X X −α po max = P[SUC ≤ sminUC ] = 0.05, then + ri hi A(θi,j, φi,j), iψ/i6=s j=1 C 1 s t R where the sub-indexes and represent the serving BS and NRBUC = E SUC ≥ sminUC the serving sector respectively. WRB log2(1 + SUC ) Z ∞ CR 1 C. SINR in broadcast mode = f(s)ds (17) WRB smin log2(1 + s) In BC SFN mode, all sectors of the BS belonging to the UC CR SFN area transmit the same waveform at the same time, and = ΓUC , W (6) is used to determine the usefulness of these signals. The RB SINR for a receiver in BC mode can be calculated as where f(s) is the probability density function (PDF) of the SINR for a UC receiver and ΓUC represents the integral. PBC PˆBC SBC = = , (13) C. Resource utilization in broadcast mode PN ˆ PN + IBC χ + IBC Ptxke c Broadcast transmissions do not benefit from link adaptation. where PˆBC and IˆBC are the signal and interference power Thus, transmissions are made aiming to cover the users with χc normalized by the factor Ptxke and are calculated as the worst channel conditions (low SINR). Since we allow a 5% outage probability, the average number of RB used per BS per NSFN 3 X X time slot in BC mode (NRBBC ) to transmit to a theoretically Pˆ = δ r−αh G(θ ), (14) BC i i i i,j infinite number of BC receivers is given by i=1 j=1 and CR 1 CR NSFN 3 NRBBC = = ΓBC , (18) ˆ X −α X WRB log (1 + smin ) WRB IBC = (1 − δi)ri hi G(θi,j) 2 BC i=1 j=1 (15) such that po max = P[SBC ≤ sminBC ] = 0.05 and ΓBC 3 represents the second term, thus simplifying the expression. X −α X + ri hi G(θi,j). D. User Threshold iψ/i>NSFN j=1 Consider a certain number of users demanding the Notice that in the case NBS = NSFN the interference factor same service (N ). The total number of resource blocks (IˆBC ) is reduced to the first term. U needed for each transmission mode can be calculated as IV. RADIO RESOURCE UTILIZATION NTRBUC = NU NRBUC and NTRBBC = NSFN NRBBC , for A. System Capacity and Outage Probability UC and BC respectively. We define the User threshold (UT ) Consider a certain service with a capacity requirement as the number of users per BS from which the BC mode consumes fewer resources than the UC mode (N < (CR) in bits per second (bps). According to Shannon’s the- TRBBC orem, the capacity of a system (C) can be calculated as NTRBUC ). It can be derived as C = W log (1 + S), where W represents the system band- 2 ΓBC width and S the SINR. Then, the number of resource blocks UT = . (19) ΓUC per time slot (NRB) needed to transmit a service with a V. NUMERICAL RESULTS capacity requirement CR, can be calculated as The first objective of the simulations is to calculate the CDF CR 1 NRB = , (16) of the SINR for all cases presented in previous sections and WRB log2(1 + S) to do so, we use the Monte Carlo method. In each Iteration where WRB is the bandwidth of a single resource block a new PPP for the BS location is generated and the SINR (RB). When the SINR at the receiver is very low, a lot of for a receiver in UC and BC modes are calculated based on resources are needed to satisfy the capacity requirement. The equations presented in section III. To be compliant with 3GPP network cannot allocate all resources to a single user. Thus, standards, most of the simulation parameters were taken from generally, users with a bad link quality are left out of service. [14, Table C.6] and are given in Table I. The probability of a receiver being out of service is called the Fig. 2 shows the SINR CDF for a receiver in UC mode, outage probability po and is defined as po = P[S ≤ s] which including beamforming with a different number of antennas is the Cumulative Distribution Function (CDF) of the SINR. per sector (M), and BC mode when considering a very large In this study, an outage probability threshold (po max) of 5% SFN area, i.e. NBS = NSFN and a user located in the origin 2 is allowed for both transmission modes. of the plane, for two different BS densities λ1 = 0.25 BS/km TABLE I SIMULATION PARAMETERS -20 M=8 Parameter Value -25 M=4 Area of the surface 1600 km2 M=8

System Bandwidth (W ) 5 MHz M=2 Carrier Frequency (fc) 2000 MHz BC -30 UC Receiver system temperature (Tk) 300 K M=4 UE Noise Figure (γ) 9 dB BS Transmission Power (Ptx) 20 W -35 Useful OFDM Symbol Time (Tu) 66.7µs M=2 Cyclic Preﬁx Length (TCP ) 16.67µs UC BC Trisectored antenna gain (GA) 15 dBi Average Signal Power [dBm] -40 Antenna frontback ratio (GFB ) 20 dBi ◦ 3 dB beam width (θ3dB ) 65 Shadowing Standard Deviation (σdB ) 10dB -45 Shadowing Correlation Coefﬁcient (ρ) 0.5 =0.25BS/km2 =2BS/km2 1 2 Noise Power (PN ) −98dBm Path Loss Exponent (α) 3.76 1 Path Loss Factor (k) 0.0295 Fig. 3. Average Signal power for Unicast mode, including beamforming with 1 For distance in meters. different number of antennas M, and Broadcast mode, considering all BS as part of the SFN area, for different values of BS density λ.

-35

-40 UC M=2 M=4 M=8 -45

-50 UC M=2 M=4 M=8 -55

-60

-65

-70

BC -75

Average Interference Power [dBm] -80 BC -85

-90 =0.25BS/km2 =2BS/km2 1 2

Fig. 2. Cumulative Distribution Function of the SINR for Unicast mode, including beamforming with different number of antennas M, and Broadcast Fig. 4. Average Interference power for Unicast mode, including beamforming mode, considering all BS as part of the SFN area, for different values of BS with different number of antennas M, and Broadcast mode, considering all density λ. BS as part of the SFN area, for different values of BS density λ.

2 2 and λ2 = 2 BS/km . As expected, the beamforming technique different BS densities are considered λ1 = 0.25 BS/km and 2 increases the SINR in UC mode, the higher the number of λ2 = 2 BS/km . In this case, we limit the maximum value of antennas per sector (M), the higher the SINR, thanks to the NSFN based on the maximum geographical size of the SFN increased signal power, as seen in Fig. 3. However, the BC area. It is set to half the size of the total simulated surface, i.e. 2 mode provides a higher SINR that all UC cases due to the 800km . This is NSFN = 200 BS and NSFN = 1600 BS for reduced interference power as seen in Fig. 4. Notice in Fig. λ1 and λ2 respectively. As expected, the SINR increases with 2 that the BS density doesn’t have a significant effect when the number of BSs in the SFN area. Notice that for the same transmitting in UC mode. As seen in Fig. 4 the interference value of NSFN , the BS density doesn’t have an important power increases when increasing the BS density attenuating effect on the SINR. However, if NSFN is fixed, with a reduced the effect of the increase in signal power. In contrast, when BS density the SFN covers a larger geographical area. On transmitting in BC mode, the higher the BS density the the other hand, if the objective is to increase the SINR in a higher the SINR. A higher number of BS in the SFN area surface with a fixed size, i.e. 800 km2, the operator should increases drastically the signal power while maintaining a low deploy more BS as part of the SFN area, thus increase the interference. BS density. As seen in Fig. 5, an SFN with NSFN = 1600 Fig. 5 shows the CDF of the SINR in BC mode when the provides a higher SINR than an SFN with NSFN = 200. SFN area is formed by the NSFN BSs closer to the origin of Finally, in Fig. 6, the User threshold (UT ) versus the number the plane. BSs outside the BC area generate interference. Two of BS in the SFN area (NSFN ) for different UC configurations of the number of users per BS demanding the same service 1 N =2, from which the BC mode consumes fewer resources than the SFN 1 0.9 N =2, SFN 2 UC mode. It was found that the user threshold is below 8 N =10, 0.8 SFN 1 N =10, users in all cases. Future work could consider sub-grouping SFN 2 N =50, 0.7 SFN 1 techniques in SFN mode. N =50, SFN 2 N =100, 0.6 SFN 1 N =100, REFERENCES SFN 2 N =200, 0.5 SFN 1 [1] Cisco White Paper. Cisco Visual Networking Index: Global Mobile N =200, SFN 2 Data Traffic Forecast Update, 2017–2022. White Paper. ENST Paris, 0.4 N =400, SFN 2 February 2019. N =800, SFN 2 0.3 N =1600, [2] Hao Feng, Zhiyong Chen, and Hui Liu. “Performance Analysis SFN 2 of Push-Based Converged Networks With Limited Storage”. In: =0.25BS/km2 Cumulative Distribution Function 0.2 1 IEEE Transactions on Wireless Communications 15.12 (Dec. 2016), =2BS/km2 2 0.1 pp. 8154–8168. [3] David Gomez-Barquero et al. “Point-to-Multipoint Communication 0 Enablers for the Fifth Generation of Wireless Systems”. In: IEEE -15 -10 -5 0 5 10 15 20 25 30 SINR [dB] Communications Standards Magazine 2.1 (Mar. 2018), pp. 53–59. [4] SeungJune Yi et al. Radio protocols for LTE and LTE-advanced. Wiley, 2012. 339 pp. Fig. 5. Cumulative Distribution Function of the SINR for Broadcast mode [5] Erik Dahlman, Stefan Parkvall, and Johan Skold.¨ 4G LTE-Advanced considering SFN areas with a fixed number of BS (NSFN ) for different Pro and The Road to 5G (Third Edition). Academic Press, Jan. 1, values of BS density λ. 2016, pp. 421–431. [6] Jordi Joan Gimenez et al. “5G New Radio for Terrestrial Broadcast: A Forward-Looking Approach for NR-MBMS”. In: IEEE Transactions 8 on Broadcasting 65.2 (June 2019), pp. 356–368. UC, 1 UC, [7] Mikko Saily et al. “5G Radio Access Networks: Enabling Efficient 2 7 UC, M=2, 1 Point-to-Multipoint Transmissions”. In: IEEE Vehicular Technology UC, M=2, 2 Magazine 14.4 (Dec. 2019), pp. 29–37. UC, M=4, 6 1 UC, M=4, 2 [8] Seon Yeob Baek, Young-Jun Hong, and Dan Keun Sung. “Adaptive UC, M=8, 1 Transmission Scheme for Mixed Multicast and Unicast Traffic in

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