On the Performance of Aerial LTE Base-Stations for Public Safety and Emergency Recovery Karina Gomez† , Tinku Rasheed† , Laurent Reynaud‡ and Sithamparanathan Kandeepan§ † CREATE-NET, via alla Cascata 56D, 38123 Trento, Italy ‡ Orange Labs, 2 Avenue Pierre Marzin, 22307 Lannion, France § School of Electrical and Computer Engineering, RMIT University, Melbourne, Australia Email: {kgomez,trasheed}@create-net.org;
[email protected];
[email protected]
Abstract—Recent events have shown that in the aftermath of an unexpected incident, communication infrastructures play an important role in supporting critical services. Airborne communication networks have been recently studied for the provision of wireless communication services and it is a promising candidate for rapidly deployable and resilient emergency networks. However, the choice of communication technologies from Aerial platforms is a challenging issue and depends on a variety of factors including platform payload capacity, coverage and capacity requirements, to name a few. In this paper, we investigate the performance of 4G LTE-WiFi multimode base stations deployed on airborne platforms which provides coverage for first responders during emergencies. We present an adapted simulation model for the analysis of hybrid aerial-terrestrial systems and study the impact of platform elevation and mobility on the cell coverage and channel capacity. Performance analysis with a platform deployment of a single Aerial Base Station (eNodeB) corroborates that airborne units with 4G communication capabilities are very promising candidates for robust communication links during emergency relief operations. Index Terms—Aerial network infrastructure; emergency communications; low altitude platforms; Long Term Evolution (LTE);
I. I NTRODUCTION Recent events have shown that in the aftermath of an unexpected event, communication infrastructures play an important role in supporting critical services such as emergency recovery and post-disaster operations, infrastructure restoration, etc [1]. Current mission critical systems, including Public Protection and Disaster Relief (PPDR) communication systems, are limited in terms of network capacity and coverage. They are not designed for or suitable to address large scale emergency communication needs in a disaster aftermath. PPDR systems are also limited by interoperability barriers, the technological gap with commercial technologies and evolving standards. Aerial communication networks have been recently studied for the provision of wireless communication services and have continually attracted significant interest from government, industry and academia [2]. While much of the original efforts have focused on developing long endurance High Altitude Platforms (HAP) operating at altitudes of about 17-25 km, in the recent years, many other types of aerial platforms, either aerostats or aerodynes, have been developed to fly at lower altitudes. Those platforms, gathered under the denomination
of Low Altitude Platforms (LAP) are increasingly believed to offer the potentiality to effectively complement conventional satellite or terrestrial telecommunication infrastructures, as announced by Google [3]. For example, the DACA (Deployable Aerial Communication Architectures) architecture proposed by the FCC in the US explores the feasibility to deploy aerial platforms during emergency situations to restore critical communications [6]. While LAPs based on UAVs are subject to several research efforts ranging from robotics to remote sensing and surveillance applications, provisioning of broadband communications using low flying LAPs have not been well investigated, mainly due to the associated challenges with payload capacity and power demands [4], [5]. Recently, a hybrid approach, proposed in [7] has the main goal to demonstrate the high-capacity, lowlatency and coverage capabilities of LTE-A solutions adapted for rapidly deployable broadband emergency communications through embedded onboard LAPs. To model the system level parameters in a Hybrid AerialTerrestrial Network and to analyse the LTE performance requires a completely developed LTE system simulator. There are several LTE simulators available in the academic community which are open source [8], [9], [11], but such simulators and associated models are not totally applicable to AerialTerrestrial communication environments. In this paper, we propose a holistic and rapidly deployable mobile network architecture based on a hybrid aerial-terrestrial approach, which is flexible to be adapted to different scenarios based on the characteristics of the aerial platforms and the choice of deployment of the LTE-specific system components [10]. The main contributions of this paper are: •
•
•
We present an adapted simulation model for the analysis and complete performance verification of hybrid AerialTerrestrial systems based on 4G LTE technology. We investigate the performance of multimode 4G LTEWiFi base stations deployed on airborne platforms which provide coverage for first responders during emergencies. We analyze the impact of platform elevation and mobility on channel stability which provides several insights into further investigation into the resilience and scalability aspects of the proposed architecture.
Table I: LTE available bandwidth and resource blocks. Channel bandwidth [MHz] Number of RB
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video over three kilometers in suburban settings or up to five kilometers in rural settings. In order to avoid interference, licensed spectrum dedicated to PPDR can be used for operating LTE and WiFi. However, unlicensed spectrum can be also considered in scenarios where terrestrial communication infrastructure are destroyed. III. A IRBORNE LTE S IMULATION M ODEL Figure 1: Hybrid Aerial-Terrestrial Network Architecture. II. S YSTEM M ODEL The European FP7 ABSOLUTE project [7] investigates the design and demonstration of a reliable Hybrid TerrestrialAerial Architecture which supports flexible and rapid deployment of a low delay and high capacity wireless network. Once deployed, this robust infrastructure is intended to accommodate the multiple requirements of PPDR end-users during emergency, public safety and temporary events. One prominent feature of this architecture is the tight interconnection between a terrestrial segment, which consists of adapted user equipments and transportable communication platforms (used to provide swift access to multiple wireless access technologies, including 4G-LTE, legacy PPDR technologies and backhaul access to core networks and remote sites) and an aerial segment [4]. The aerial segment includes LAP equipped with a LTE E-UTRAN Node B (eNB), therefore providing autonomous operation with a scalable network coverage. In this work, we consider a subset of this hybrid architecture, as shown by Fig. 1, with the aerial segment consisting of a single LAP with its LTE eNB communication payload (Aerial-eNB), operating at varying altitudes, keeping a quasistationary position over a predefined area and servicing a set of user equipments (UEs). The network is deployed for the public safety personnel and first responders over the disaster area in order to coordinate rescue and first-aid services for the survivors. The Aerial-eNB can be easily deployed in the center of the disaster area using a Helikite platform [12]. For the LTE Aerial-eNB equipments, several commercial solutions for LTE public safety in [13] can be considered. A directional antenna can be also used in the Aerial-eNB for providing macrocell, microcell or picocells coverage. A directive IEEE 802.11 communication link (the WiFi link is only an assumption for the backhaul and is not binding in the architecture) is set up between the Aerial-eNB and the terrestrial ground station, here composed of an Evolved Packet Core (EPC), which is connected to external Public Safety Center and the Internet. For the WiFi equipments in EPC and Aerial-eNB, we can consider commercial solutions [14] that enable WiFi to operate over macrocell ranges, supporting a variety of indoor and outdoor use cases. Using this WiFi solution, it is possible to successfully stream high-bandwidth
In this section, we present the adapted link level simulator for Hybrid Aerial-Terrestrial Network simulations and describe the assumptions and parameters to be used for studying the performance of LTE-based Aerial-eNB deployments. The network scenario was developed in OMNeT++ [15] simulator using the INET framework. We extended the MONAMI LTE implementation [11] using the ChSim [16] channel models in order to implement the LTE logical and physical layers according to 3GPP Rel-10 [10]. The UE, eNB and EPC models implemented in the simulator are designed and set according to [10], [18]. It is important to note that the Ethernet connectivity between eNB and EPC is replaced by a wireless channel in order to allow the communication between eNB and EPC and the easy deployment of eNB in the hybrid network scenario. A. LTE Simulator Implementation Overview In the following, we detail the main features implemented in the link simulation model. 1) Duplex schemes: The LTE simulator supports TimeDivision Duplex (TDD) and Frequency Division Duplexing (FDD) duplex scheme. In the current version of the LTE simulator, two links are implemented: uplink (UL) the transmission from UE to eNB and downlink (DL) the transmission from eNB to UE. 2) LTE TDD sub-frame allocations: In LTE TDD, it is possible to dynamically change the UL and DL balance and characteristics to meet the load conditions. In fact, a total of seven UL/DL configurations have been set within the LTE standard using 5 ms or 10 ms switch periodicity. The proposed simulator allows the possibility to set one of seven UL/DL configurations for each simulation. In each configuration i) D is a sub-frame for downlink transmission, ii) S is a special sub-frame used for a guard time and iii) U is a sub-frame for uplink transmission. 3) LTE channel bandwidths: LTE defines 6 options of channel bandwidths and resource block (RB) as shown in Table I. It is obvious that the greater the bandwidth implies also greater the channel capacity. Our model supports all the LTE signal bandwidth with the respective RB. 4) Downlink carriers and resource blocks: The sub-carriers in downlink are organized into RB regardless of the overall LTE signal bandwidth. Each RB contains 12 sub-carriers. In this way, the system can allocate data across standard number of sub-carriers. One RB also covers one slot in the time frame.
Table II: Characteristics of Wideband Codecs Service
Unit
HD Audio
HD Video
Codec Bandwidth Data Rate Data rate at good audio Maximum Delay for QoS
[kHz] [kb/s] [kb/s] [ms]
G.722FB 10 64 32 40
H.264 10 384 32 80
Table III: Parameters used in the channel models Link Channel Model Modulation α K Transmission Power Bitrate per TTI Receiver Sensitivity Central Frequencies Antenna GainT x/Rx
Figure 2: Aerial-eNB with the LTE and IEEE 802.11 protocol stack implemented in the simulator. 5) LTE OFDMA in the downlink: The OFDM signal used in LTE comprises a maximum of 2048 different sub-carriers having a spacing of 15 kHz. Within the OFDM signal it is possible to choose between three types of modulation: (i) QPSK 2 bits per symbol , (ii) 16-QAM 4 bits per symbol and (iii) 64-QAM 6 bits per symbol. The current version of simulation model supports all the modulations. 6) LTE SC-FDMA in the uplink: The access technique used by LTE standard and simulator is the Single Carrier Frequency Division Multiple Access (SC-FDMA). B. Aerial-eNB Model The Aerial-eNB model with the LTE and IEEE 802.11 protocol stack implemented in the simulator is illustrated in Figure 2. The basic protocol structure of LTE is composed by: - Packet Data Convergence Protocol (PDCP) is responsible of control plane data transfer and PDCP sequence number maintenance. - Radio Link Control (RLC) is responsible for classifying each flow according to the destination address and controlling unacknowledged or acknowledged mode handling. Each flow is buffered in different queues and is served following a Deficit Round Robin (DRR) scheduler. - Medium Access Control (MAC) is responsible for retransmission handling using multiple Hybrid Automatic Repeat Requests (Hybrid ARQ) and multiplexing of data flows. - Physical Layer (PHY) assigns the modulation/code-scheme and RB to the data that is to be transmitted and encapsulates this data into the OFDM signal. The transmitted signal is organized into sub-frames of one Transmission Time Interval (TTI) duration equal to 1ms, each consisting of 14 or 12
LTE UL/DL
WiFi UL/DL
Clarke’s Fading 16-QAM 2.2 23/30 dBm 33.6 Mb/s -98.8 dBm 1.85 GHz 3/3 dB (SISO)
Rice BPSK/QPSK/QAM 2 8 dB 23/23 dBm 2-54 Mb/s -100 dBm 2.4 GHz 3/3 dB (SISO)
OFDM symbols. PHY switches between D or U transmission according with the LTE TDD sub-frame allocations. - Relay unit (RU) is responsible of forwarding the data from one interface to other. For example, when data arrives to Aerial-eNB through the IEEE 802,11g interface, the data is forwarded from IEEE 802.11g to LTE interface. The RU encapsulates the packets into packet data units (PDU) and sends it to the PDCP layer and vice-versa. - Mobility Manager (MM) is responsible for the mobility and tracking of the Aerial-eNB. The mobility module informs the exact positions of the Aerial-eNB (using embedded localization techniques) to the Terrestrial-EPC. Since the AerialeNB will be deployed using a Helikite platform [12] at lower altitude, from 500 to 2000 m, it is unrealistic to consider a fixed Aerial-eNB. In lower altitudes, the weather conditions are predominant ,i.e. wind and rain, which means that the Aerial-eNB cannot remain completely static. Therefore a realistic consideration is to assume that the Aerial-eNB has random mobility inside a specific area with low speed (see Figure 1). - Light EPC: It is responsible to manage all the mechanisms implemented for supporting the basic functionalities of the autonomous Aerial-eNB. The Light EPC guarantees that if a specific server located in terrestrial EPC (e.g. high level like short message service center (SMSC) or low level like Authentication, Authorization and Accounting (AAA)) is temporarily unavailable due to disruption or disconnections; the Light EPC manages the routines during the considered disruption, as a surrogate server. IV. P ERFORMANCE E VALUATION We present the outcomes of a set of experiments carried out using the adapted simulation platform described above for analyzing the performance of Aerial-eNBs. Our objective is mainly to study the flexibility of using 3GPP LTE-A technologies in hybrid Aerial-Terrestrial deployments without
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Figure 3: Channel gain in [dB] using Clarke’s Fading Channel Model for one RB varying the Aerial-eNB altitude and speed. taking into account any optimization to reduce the payload weight of the respective technologies. A. Network Settings The simulation scenario is depicted in Figure 1. We considered a disaster scenario with an area of 1 km2 , which represents ≈80 urban blocks. It is assumed that the terrestrial communication and electrical network infrastructure is destroyed in this area. The Hybrid Aerial-Terrestrial Network is deployed for the public safety personnel and first responders in order to coordinate rescue and first-aid services for the survivors. The Aerial-eNB is deployed in the center of the disaster area, using a Helikite [12]. The Aerial-eNB has a single site equipment with a directional antenna and its transmission power is set to 30 dBm [18] for achieving a microcell with coverage radius equal to ≈700 m. We focus on analyzing of the maximum downlink capacity of the AerialeNB, so the cell is configured with TDD duplex scheme in UL/DL configuration number 5 (D|S|U |D|D|D|D|D|D|D) with 5 ms switch periodicity. The bandwidth used is 10 MHz in the downlink for the cell with 50 full resources allocation and 16-QAM radio modulation. Inside the cell, a number of UEs (USB-LTE modems and phones) from public safety personnel and survivors (chosen in the range [1-300]) are uniformly distributed. The transmit power of each UE is set to 23 dBm [18]. UEs move inside the disaster area following a random waypoint mobility model with a uniformly distributed speed between (0.3-0.8) m/s. We performed two experiments, firstly the LTE push-to-talk application [13] is tested. In this experiment, each user receives one HD Audio G.722FB Codec flow [17] (encoded at 64 kb/s) from the Public Safety center in order to transmit instructions or information i.e. secure zones or danger areas. In the second experiment, the streaming real-time video application [13] is tested. In this case, each user receives HD Video-Audio H.264 Codec flow [17] (encoded at 384 kb/s and 32 kb/s for audio) from the Public Safety center in order to transmit video instructions i.e. medical support for the wounded individuals. The HD video and audio codec flow specifications are shown in Table II and the flow runs for a duration of 700 seconds. The performance analysis is carried out varying the Aerial-eNB
elevation in a range of [500, 2000] meters and the number of served UEs for both the experiments. The Aerial-eNB has two access interfaces, the 4G-LTE and WiFi. The WiFi interfaces in the Aerial-eNB and EPC are equipped with directive antennas, the parameters used for MAC layer are according to 802.11g standard protocols with an autorate adaptation implemented. We tune the WiFi settings according to the parameters required for long-range WiFi over unlicensed spectrum [14]. The Table III summarizes the parameters used in the channel model used for each link. In the LTE UL/DL, we consider Clarke’s fading channel model with a mean pathloss exponent of 2.2. The central frequency for LTE is set to 1.85 GHz and for WiFi to 2.4 GHz. It is to be noted that since the terrestrial equipment is destroyed, consequently interference is not considered over the disaster area. However, specific frequencies dedicated to PPDR can be also considered for avoiding interference effects. Note that there exists no proper model for the pathloss exponent values for the hybrid Aerial-Terrestrial scenario. Therefore we perform an educated assumption for the pathloss value considering the fact that the users on the ground will have light mobility. On the other hand, the WiFi UL/DL transmissions consider a Rice fading model with a pathloss exponent of 2. The Rice model is assumed here since the EPC node is stationary with a line of sight (LOS) link with the Aerial-eNB. Results shown in this paper are the average of multiple runs presenting the expected results for the performance of the system considering the fact that the channels are random. B. Simulation Results Firstly, we set the mobility of the Aerial-eNB to 0.1 m/s for assuming a quasi-stationary position and analyze the effect of Aerial-eNB altitude on the channel state. In Figure 3.a, the channel state h(t in [dB] using Clarke’s Fading Channel Model for one RB with different Aerial-eNB altitudes is shown. As it can be seen, the figure clearly shows the effect of the altitude of the Aerial-eNB on the channel state. In fact, when the Aerial-eNB altitude increases form 500 m until 2000 m, the channel quality is affected.Then, we analyze the effect of the mobility of the Aerial-eNB on the channel state h(t). In
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Figure 4: Peak Bitrate achieved in LTE-TDD using 10 MHz bandwidth with 16-QAM and full resource allocation. the performed experiments, the channel state is sampled each millisecond for 2 seconds. In Figure 3.b-c, the channel state in [dB] using Clarke’s Fading Channel Model for one RB with the speed of the Aerial-eNB set to 0.1 and 1 m/s versus the time is depicted. As it can be seen, the results clearly show the effect of the increases of the Aerial-eNB speed on the channel state. In fact, when the Aerial-eNB speed increases from 0.1 to 3 m/s, the channel quality is affected. In the post-disaster area there is a requirement to provide VoIP services to support (i) communication between public safety center and personal in incident areas and (ii) communication between people in the incident areas and their families. In such a case, the UL and DL communication capacity is important so the maximum UL/DL capacity achieved in the system using 10 MHz bandwidth with 16-QAM and full resource allocation is depicted in Figure 4. It is important to note that (i) most UE classes supports 16-QAM in SISO mode only and (ii) due to the payload limitation of the helikite, SISO is assumed in order to reduce the weight of the antenna. As it can bee seen, each TDD configuration is characterized by different capacity in UL and DL. The higher capacity achieved in UL is using the TDD configuration number 0 (D|S|U |U |U |D|S|U |U |U ) while in DL is using the TDD configuration number 5 (D|S|U |D|D|D|D|D|D|D) as expected. We also observed that the WiFi point-to-point link used for communication between the EPC with AerialeNB was able to support the bitrates achieved in LTE-TDD using 10 MHz bandwidth with 16-QAM without introducing additional delay to the packets due to the bottleneck. In Figure 5.a-b, the network performance for HD Audio and HD Video-Audio services with varying Aerial-eNB altitudes is presented. We show the retransmission results due to the fact that the total packets lost in the system was less than 1% for all the experiments. The results show the percentage of PDU retransmitted for the LTE link. As it can be observed, a similar performance for both services; the percentage of retransmitted PDUs performing HD Audio and HD Video-Audio services is around 5% and it is not affected when the Aerial-eNB altitude and number of UEs increases as expected. In fact, the mean received SINR observed in the simulations is very high (in the order of 40dB). Therefore the main source for packet error is due to fading; we can observe comparable retransmission rates since the fading model is the same in the LTE links for
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Figure 5: Retransmitted PDU and average packet delay for real-time services with different Aerial-eNB altitudes. all the simulations (i.e. for all altitude levels of the AerialeNB). Likewise for the WiFi link as well, we observe similar results when the Aerial-eNB altitude increases, in which case the retransmission rate was around 1%. (due to lack of space we have not presented the WiFi results here). In the Figure 5.c-d, the results depict the average packet delay in order to understand the impact of Aerial-eNB altitude and number of served UEs on the QoS of the HD audio and HD Video-Audio services (results are presented with the 95% confidence interval). In the case of HD Audio, there is no significant effect on the delay when the Aerial-eNB altitude increases. However, when the number of served UEs increases until 150 UEs the packet delay also increases, and the maximum delay achieved in the hybrid Aerial-Terrestrial network is around 100 ms as shown in the Figure 5c. For HD
Table IV: Cell capacity and average delay for HD Audio and HD Video-Audio services using single/multiples Aerial-eNBs. Service Served UE/cell HD Audio HD Video-Audio Packet Delay HD Audio HD Video-Audio
Single Aerial-eNB
Multiple Aerial-eNB1
Multiple Aerial-eNB2
≈ 130 UEs ≈ 42 UEs
≈ 125 UEs ≈ 40 UEs
≈ 127 UEs ≈ 39 UEs
36±0.4 ms 77±0.7 ms
34±1,8 ms 70±1,5 ms
33±2,2 ms 71±1,7 ms
Audio Codec G.722FB the maximum latency allowed is 40 ms (see Table II), and the hybrid Aerial-Terrestrial network is supporting ≈130 HD-Audio in parallel with excellent QoS. Similarly for HD Video-Audio service, there is an effect on the delay when the number of served UE increases until 45 UEs. However, the Aerial-eNB altitude does not affect the packet delay. The maximum observed delay is around 700 ms for 45 UE receiving one HD Video-Audio session at the same time. For HD Video H.264 Codec the maximum latency allowed is 80 ms (see Table II). Therefore, the hybrid Aerial-Terrestrial network is supporting ≈42 HD Video-Audio streams in parallel with a good QoS as shown in Figure 5d. It is mainly due to the high data rate, 384 kb/s for video and 32 kb/s for audio, demanded for the HD Video-Audio that the codec is generating. Finally, we also show results regarding multiple AerialeNBs deployments in order to show the scalability of the network architecture and the flexibility of the simulation platform. The scenario considered for such analysis include two Aerial-eNBs with single EPC deployed in the disaster in a star topology. We considered a disaster scenario with a simulation area of 1 km2 for each Aerial-eNB (altitude=1000 m) with the EPC located between each other. The same settings explained before are assumed for the second Aerial-eNB except for the central frequency set to 700 Mhz in order to avoid interferences. In the Table IV, cell capacity for HD audio and HD Video-Audio services using one and multiples AerialeNBs are shown. As it can be seen, two Aerial-eNB do not have too much effect on the cell capacity when using a WiFi backhaul. V. C ONCLUSIONS AND F UTURE W ORK In this paper, we studied the feasibility of deploying onboard LTE eNB for hybrid Aerial-Terrestrial communications for rapid deployment during emergencies. The performance analysis for selected network scenarios that involve WiFi and 4G-LTE as access technologies for the different link segments demonstrate that varying the altitude of the Aerial-eNB does not affect the network performance for a typical deployment altitude, between 500 and 2000 meters. This highlights the fact that LTE-based eNB onboard the LAP are excellent candidates for emergency communications due to the robustness of 4GLTE in terms of coverage, capacity and low latencies. We observed that when the number of parallel service flows increases, the packet delay increases, which shall be mitigated
using resource and slot (LTE-TDD) allocation schemes tailored for hybrid Aerial-Terrestrial scenarios, which is part of our ongoing work. Moreover, as future work, we are currently extending our performance analysis of LTE-based Hybrid Aerial-Terrestrial Network implementations to a network of coordinated multiple Aerial-eNBs deployed over a disaster area. Besides, we are also evaluating the most suitable technology for each link segment to optimize the system capacity for the network infrastructure deployed for emergency response and the effect of interferences between Aerial-eNBs. ACKNOWLEDGMENTS The research leading to these results has received partial funding from the EC Seventh Framework Programme (FP72011-8) under the Grant Agreement FP7-ICT-318632. The authors would also like to thank Dr. Stefan Valentin for the valuable discussions related to the ChSim and Dr. Amna Eleyan for providing us the MONAMI LTE model. R EFERENCES [1] Information and Communications in the Aftermath of the Great East Japan Earthquake, Ministry of Internal Affairs and Communications, Tech. Rep., Nov. 2011. [2] A. Qiantori, B. Sutiono, H. Hariyanto, H. Suwa and T. Ohta, An Emergency Medical Communications System by Low Altitude Platform at the Early Stages of a Natural Disaster in Indonesia, International Journal of Medical Systems, vol. 34, March 2010, pp. 1-12. [3] Google’s news. Broadband Internet Access to the Developing World. Available at http://ravenaerostar.com/about/project-loon-raven-aerostargoogle. [4] L. Reynaud and T. Rasheed, Deployable Aerial Communication Networks: Challenges for Futuristic Applications, in Proc. 9th ACM Intl Symp. PE-WASUN, Cyprus, October 2012. [5] G. Araniti, M. De Sanctis, S. C. Spinella, M. Monti, E. Cianca, A. Molinaro, A. Iera and M.Ruggieri, Hybrid System HAP-WiFi for Incident Area Network, in Proc. of PSATS 2010 Conference, RomeItaly, 2010. [6] The Role of Deployable Aerial Communications Architecture in Emergency Communications and Recommended Next Steps, Federal Communications Commission (FCC), Washington, Tech. Report, 2011. [7] ABSOLUTE (Aerial Base Stations with Opportunistic Links for Unexpected and Temporary Events), EU FP7 Integrated Project. Available at: http://www.absolute-project.eu/ [8] G. Piro, L. A. Grieco, G. Boggia, F. Capozzi and P. Camarda, Simulating LTE Cellular Systems: An Open-Source Framework, Vehicular Technology, IEEE Transactions on, vol.60, no.2, pp.498-513, Feb. 2011 [9] N. Baldo, M. Requena, J. Nin and M. Miozzo, A New Model for the Simulation of the LTE-EPC Data Plane, in Proc. of the Workshop on ns-3 (WNS3 2012), Sirmione, Italy, 23 March 2012 [10] 3rd Generation Partnership Project. Technical Reports for Release 10. Available at: http://www.3gpp.org/Release-10. [11] M. Arouri, Z. Atiyyeh, A. Mousa, A. Eleyan, H. Badr, A Simulation Implementation of the LTE-Uu Interface Datalink Layer in OMNeT++. MONAMI 2010: p.270-284. [12] Allsopp Helikites. Available at: http://www.allsopphelikites.com/ [13] Public Safety LTE. Available at: http://enterprise.alcatel-lucent.com [14] InterDigital Demonstrates Long-Range Wi-Fi over Unlicensed Spectrum for Backhaul Applications. Available at: www.interdigital.com [15] OMNET++ Network Simulator. Software and documentation vailable at: http://www.omnetpp.org [16] S. Valentin, ChSim - A Wireless Channel Simulator for OMNeT++, in TKN TU Berlin Simulation Workshop, September 2006. Software and documentation available at http://wwwcs.upb.de/cs/chsim. [17] K. J´ arvinen, I. Bouazizi, L. Laaksonen, P. Ojala, and A. R´ am´ o. Media Coding for the Next Generation Mobile System LTE. Comput. Commun. 33, 16 (October 2010), 1916-1927. [18] L. Song and J. Shen, Evolved Cellular Network Planning and Optimization for UMTS and LTE-CRC. Press (2010).
