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DVB-S2 Adaptive Coding and Modulation for HAP Communication System Miha Smolnikar, Tomaz Javornik, Mihael Mohorcic

Matteo Berioli

Department of Communication Systems Jozef Stefan Institute (JSI) Ljubljana, Slovenia {Miha.Smolnikar, Tomaz.Javornik, Miha.Mohorcic}@ijs.si

Institute of Communications and Navigation German Aerospace Center (DLR) Oberpfaffenhofen, Germany [email protected]

Abstract— Combining some of the best terrestrial and satellite systems’ characteristics, high altitude platforms (HAPs) have recently emerged as an alternative solution for the provision of broadband services. Characterised by challenging propagation conditions in the allocated frequency bands, they require efficient utilisation of radio interface in order to make best use of the available spectrum. This paper analyses possible utilisation of DVB-S2 standard on HAPs, focusing on the performance of its adaptive coding and modulation (ACM) procedures as a mean of maximizing the link reliability and throughput. Two distinct operating scenarios are addressed, one assuming static channel conditions with the applied rain fading and the other representing mobile channel conditions along a representative railway track. We show that by considering only a subset of transmission modes (MODCODs) defined by the DVB-S2 standard, the system could be optimized in terms of achievable spectral efficiency as well as in terms of implementation complexity. A procedure for optimal MODCOD subset selection is proposed, taking into account the predefined switching thresholds and round-trip time delay. Keywords—High Altitude Platform (HAP), DVB-S2 Standard, Adaptive Coding and Modulation (ACM), MODCOD subset selection

I. INTRODUCTION Interactive wireless multimedia communications have tremendously expanded over the last decade. With the yet growing capacity demands and support for mobility, the existing systems are faced with ever increasing challenges to satisfy users’ needs. The trends are thus in the exploitation of higher frequency bands, with terrestrial systems consequently suffering from smaller coverage areas and satellite systems being more sensitive to the changing environmental conditions. Recently emerged High Altitude Platforms (HAPs) equipped with communication payload and operating in the lower stratosphere at altitudes of 17-22 km appear as attractive complementary solution to terrestrial and satellite systems [1, 2]. They have the capability to provide primarily line-of-sight (LOS) links to fixed and/or mobile terminals within the coverage area with radius of approximately 50 km, making them an attractive solution for establishing broadband wireless access (BWA) links in the metropolitan area networks (MAN) segment. The International Telecommunications Union (ITU) allocated frequency bands for their operation are 47-48 GHz and 28-31 GHz.

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Efficient use of radio resources in such challenging operating environment can be achieved by Adaptive Coding and Modulation (ACM) procedures, implemented in several modern communication standards. They offer the ability to dynamically adapt the physical layer transmission parameters according to time and/or location dependent Signal-to-Noise Ratio (SNR). In this paper we assume that the forward link of a HAP communication system is based on the second generation Digital Video Broadcasting – Satellite (DVB-S2) standard [3]. Besides showing in general how the standard that was initially designed for satellites should be adapted for the operation on HAPs, the emphasis is given on the performance evaluation of the proposed ACM procedures. Considering the propagation delay as the major difference between HAP (in the order of milliseconds) and satellite (in the order of several hundreds of milliseconds) systems, HAPs are capable of compensating much faster channel variations than satellites, offering themselves as a suitable platform for both, fixed and mobile operating scenarios. For each scenario we define a procedure to select the most appropriate subset of transmission modes among 28 defined by the DVB-S2 standard. The rest of the paper is organized as follows. Besides briefly describing the DVB-S2 standard and HAP channel model, the emphasis in Section II is given to system modelling and the assumptions taken into account. In Section III procedures for selecting the optimal subset of transmission modes are described in detail for both investigated scenarios, while Section IV discusses the functionalities of HAP-based ACM procedures. Finally, Section V concludes the paper. II.

INVESTIGATED ENVIRONMENT

The system model considered in this study is composed of a single HAP located at an altitude of 22 km above Ljubljana, the capital of Slovenia, serving static users experiencing rain fading (static operating scenario) and mobile users on train travelling between two major cities, i.e. Koper and Maribor (mobile operating scenario). A. DVB-S2 Standard The second generation Digital Video Broadcasting – Satellite (DVB-S2) standard [3] was recently specified to redefine the forward link of a satellite communications system. By employing adaptive air interface it has been designed to

assure significant system capacity increase with respect to the DVB-S standard. The key enabling technology is ACM, where the transmission parameters are optimized on a frame-by-frame basis according to the user perceived SNR. As a result of four modulation schemes (i.e. QPSK, 8-PSK, 16-APSK and 32APSK) and eleven channel coding rates (based on concatenated LDPC and BCH coding), the standard specifies 28 different modulation and coding (MODCOD) transmission modes. B. Static and Mobile HAP Channel Model Contrary to satellite channel models that are typically represented by extensively validated statistical models, there are currently no statistical HAP channel models or a channel models obtained from measurement campaigns available. Therefore, HAP propagation channel model considered in this paper is based on a land-mobile satellite (LMS) channel model [4], taking into account the necessary modifications due to different carrier frequency, shorter path length and variable elevation angle caused by the unpredictable motion of the aerial platform. Regarding the two studied scenarios two separate traces were obtained by the purposely developed simulator [5]. Static conditions with the applied rain fading are modelled by segment channel approach proposed for satellite channel [6], while the mobile channel conditions are modelled by applying a ray tracing approach on the digital elevation model to emulate the three channel states representing LOS, shadowed and blocked conditions [4]. The channel conditions are modelled as a superposition of different propagation effects (i.e. free space loss, rain attenuation, scintillation and attenuation due to shadowing and blockage of signal).

Gaussian noise (AWGN) is added to the signal at the receiver. Assuming perfect synchronization, the pilot and payload part are then separated, with the payload part being forwarded to the Automatic Gain Control (AGC) and the pilot symbols forwarded to the SNR estimator. The latter is based upon SNORE SNR estimation algorithm, which was proposed for the use with DVB-S2 in [7]. Its SNR estimates are computed as a ratio of the estimated signal power PS and the estimated noise power defined as PN = PR - PS, where PR denotes the estimated received power. The latter is also forwarded to AGC, which is amplifying the payload symbols back to nominal power. PR and PS are computed according to the following equations, where NP is the number of symbols, pn is the original pilot symbol sequence and rn is the received pilot symbol sequence:

1 PR = NP

NP

¦r

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§ 1 PS = ¨¨ © NP

NP

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· Re rn p ¸¸ . ¦ n =1 ¹ * n

Besides for reporting to the GW on the estimated channel conditions, the SNR estimates are also required by the softdemodulator for computing the initial a posteriori probabilities (APP) of the received information. In order to minimize the estimation error consecutive estimates are further averaged by exponential forgetting averaging function, where the short-term parameter estimate is obtained by combining previous X k −1 and current X k parameter estimates, with the 0 < αA < 1 denoting the exponential forgetting factor: X = (1 − α A ) X k + α A X k −1 .

The short-term received power estimate PR is forwarded to the C. System Modeling and Assumption We are assuming our system model being composed of a gateway (GW) in the form of HAP and a single user terminal (UT) exploiting the ACM to optimise its link efficiency according to time and/or location dependent propagation conditions. These are computed at the UT in the form of SNR estimates and with minimum possible latency reported back to the GW, which makes the actual MODCOD switching decisions. As for the return link, we are not assuming it to be based upon any standard (e.g. DVB-RCS), but take it into account only in the form of round-trip time set to 3 ms in our simulations (obtained as a sum of 1 ms forward link frame duration, 1 ms processing delay and 1 ms return link duration). According to the DVB-S2 standard the forward link transmitted signal is time-division multiplexed, with each physical layer frame (PLFRAME) being composed of the pilot and payload part. The latter is in our case restricted solely to the use of normal FECFRAME length (i.e. 64800 bits blocks), with only the LDPC coding applied to the randomly generated baseband payload data (BBFRAME). The pilot part is assumed to be based only upon the Start Of Frame (SOF) pilot sequence containing 26 symbols that are added in front of the payload part, while the optional periodic 36 symbol pilots are omitted. Following baseband modulation the frame is sent through the channel and the amplitude is multiplied with the value of fading corresponding to the current time and location of a predefined channel trace. Finally, thermal additive white

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AGC block, while the short-term SNR estimate SNR is forwarded to the soft-decision demodulator and reported back to GW, to support the MODCOD switching decisions. The above described DVB-S2 system model is used in the following to investigate a methodology for optimal MODCOD subset selection and the specifications of respective ACM procedures in HAP working environment. III.

MODCOD SUBSELECTION

The DVB-S2 standard specifies 28 MODCODs that could be used as a part of ACM. Table I and Figure 1 shows the simulation results for SNR thresholds in AWGN channel assuming the target BER set to 10-5. These results indicate that ACM scheme considering all MODCODs would inherently lead to suboptimal performance. In particular, MODCODs 10, 15, 22 and 23 achieve lower spectral efficiency at higher SNR than neighboring MODCODs; MODCODs 11, 16 and 17 achieve just slightly better spectral efficiency performance for the higher required SNR; and MODCOD 19 has its BER-vsSNR curve practically overlapped with MODCOD 20. This indicates that several MODCODs are impractical for the implementation, promising simultaneously simplification and optimization of the system. Thus we have specified a set of criteria to select the most appropriate MODCOD subset with respect to the rate of channel variations for each operating scenario (static or mobile).

In order to compare the efficiency of different schemes 28 MODCOD subsets were defined. Starting from non-adaptive scheme considering only QPSK 1/4 towards the scheme considering all 28 MODCODs, additional MODCODs are in each consecutive subset added by trying to respect the equidistance in terms of SNR between the adjacent MODCODs. All subsets with indicated MODCODs considered in a particular subset are listed in Table I. In both operating scenarios the demodulation threshold of the most robust transmission scheme was set so as to provide practically uninterrupted service in the LOS conditions. Since the only propagation effect we are aiming to compensate using ACM is fading, the scintillation was set to 0 dB and perfect SNR estimation was assumed at the UT. The estimates were delivered to the GW after the round-trip time delay as specified in Section II.C. Each MODCOD subset was tested on the same representative segment of the channel trace depicted in Figure 2 (a) for static and in Figure 3 (a) for mobile operating scenario. The frame is considered to be corrupted when the SNR is lower than the MODCOD’s demodulation threshold value provided in Table I, in other words when received at higher than targeted BER. We are assuming the pilot symbols are always present. Simulation results in terms of SNR, MODCOD switching and spectral efficiency are depicted for static scenario in the case of the MODCOD subset 11 in Figure 2, and for the mobile scenario using the MODCOD subset 7 in Figure 3. In Figures 2 (c) and 3 (c) the value of spectral efficiency being 0 indicates when targeted BER is violated, TABLE I.

Figure 1. MODCOD spectral efficiencies versus respective SNR thresholds

while the value of spectral efficiency being -1 indicates when SNR is lower than the demodulation threshold of the most robust transmission scheme. By post-processing simulation results obtained for all MODCOD subsets we tried to find the subset with optimal performance in a given operating scenario. For the static operating scenario we compared the performance of subsets in terms of average spectral efficiency, as shown in Figure 4. A rapid increase of average spectral efficiency can be perceived by adding spectrally efficient MODCODs to operate in clear

DVB-S2 MODCOD TRANSMISSION SCHEMES’ PERFORMANCES AND MODCOD SUBSETS CONSIDERED FOR ACM

MODCOD No.

mode

1 QPSK 1/4 2 QPSK 1/3 3 QPSK 2/5 4 QPSK 1/2 5 QPSK 3/5 6 QPSK 2/3 7 QPSK 3/4 8 QPSK 4/5 9 QPSK 5/6 10 QPSK 8/9 11 QPSK 9/10 12 8PSK 3/5 13 8PSK 2/3 14 8PSK 3/4 15 8PSK 5/6 16 8PSK 8/9 17 8PSK 9/10 18 16APSK 2/3 19 16APSK 3/4 20 16APSK 4/5 21 16APSK 5/6 22 16APSK 8/9 23 16APSK 9/10 24 32APSK 3/4 25 32APSK 4/5 26 32APSK 5/6 27 32APSK 8/9 28 32APSK 9/10

MODCOD subsets

SNR

SE

[dB]

[bit/s/Hz]

-2.54 -1.42 -0.53 0.91 2.07 2.98 3.94 4.58 5.13 6.09 6.31 5.71 6.64 7.93 9.28 10.11 10.52 8.87 10.86 10.98 11.53 12.78 12.98 12.63 13.57 14.13 15.52 15.76

0.4902 0.6564 0.7894 0.9889 1.1883 1.3223 1.4875 1.5872 1.6547 1.7665 1.7886 1.7800 1.9806 2.2281 2.4786 2.6460 2.6792 2.6372 2.9667 3.1656 3.3002 3.5231 3.5673 3.7033 3.9516 4.1195 4.3979 4.4530

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Figure 2. Time traces of SNR, MODCOD switching and spectral efficiency in static operating scenario

Figure 3. Time traces of SNR, MODCOD switching and spectral efficiency in mobile operating scenario

sky conditions, while the impact of number of MODCODs considered for use in deep fading event is negligible to overall performance (see Figure 2 (b)). MODCOD subset 11 was therefore selected as the one offering optimal trade-off between performance and complexity of the system.

with GW, allocating its forward link resources. In case of inefficient MODCOD switching algorithm two events limiting the achievable capacity can occur: (i) a frame can either be corrupted and therefore lost because of the GW selecting too powerful MODCOD, or (ii) a frame can be transmitted using too robust transmission scheme, resulting in inefficient utilisation of the available link capacity.

In the mobile operating scenario, characterised by much faster rate of channel variations, we have additionally to average spectral efficiency observed also the maximum downswitch time parameter, which is together with average spectral efficiency in dependence of subsets depicted in Figure 5. The latter is denoting the adaptation time that ACM procedure needs to switch down from spectrally efficient to the sufficiently robust transmission scheme. When larger than the assumed round-trip time (i.e. 3 ms), this parameter is denoting that ACM procedures were actually switching among nonadjacent MODCODs to re-establish the link operating at proper BER. MODCOD subset 7 was selected as the one offering best performance in terms of average spectral efficiency and downswitch time. IV.

PROPOSED ACM PROCEDURES

When utilising ACM procedures the increased system complexity is represented by a larger number of MODCODs, the necessity to feed the SNR estimated by UT back to the GW with minimal latency, and the need to implement a suitable MODCOD switching algorithm. While the feed-backs can be periodical or triggered by SNR exceeding certain threshold value, the decision on switching between MODCODs still lies

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MODCOD switching algorithm shall therefore account for contributions of the effects that are not intended to be compensated using ACM (e.g. scintillation), SNR estimation errors, and the fact that GW always disposes only with the outdated SNR estimation. Different techniques have been proposed to mitigate these effects. To minimise the impact of SNR estimation error averaging of the consecutive estimates is usually used. We propose the usage of exponential forgetting averaging, described in Section II.C, with the forgetting factor αA being optimised with respect to the rate of channel variations. Averaging would thus be more dependent on the history in the case of static channel affected by rain fading, and more dependent on the current estimate in mobile channel. This would cause the estimation error being lower in rain fading, while it would offer higher adaptability in mobile conditions. This is also in accordance with the MODCOD subsets proposed for each scenario, where fever more separated transmission schemes are considered in mobile scenario. Concerning the estimation information at the GW being outdated, it can in general be said that adjacent MODCODs must be separated by at least the magnitude of SNR change in the adaptation time.

Figure 4. Average spectral efficiency in dependance of the increasing number of MODCODs (MODCOD subsets) in static operating scenario

Finally, shifted thresholds and hysteresis have been proposed to be added to the ideal switching points in [8, 9, 10], for the mitigation of scintillation effect. Our proposal on adapting these procedures for HAP working environment and especially in the case of the mobile operating scenario is to use shifted thresholds optimised with respect to the scintillation standard deviation, while the hysteresis for avoiding frequent MODCOD switches, when the estimated SNR is close to switching threshold, could be introduced by the BER estimation or resource management algorithm. V.

CONCLUSION

In this paper we are analysing the utilisation of DVB-S2 standard in the HAP working environment. In particular, based on static and mobile propagation channel model we define two distinct operating scenarios. With the DVB-S2 offering ACM capabilities, we focus on their potential to increase the system capacity with respect to non-adaptive systems designed with respect to worst-case conditions. Based on simulation results assuming perfect channel knowledge, we show that the MODCODs defined by the DVB-S2 standard are too numerous for the implementation. Even more, the results show that performances in terms of average spectral efficiency even decrease when considering too many MODCODs. Therefore, a procedure to select the most appropriate MODCOD subset is proposed, taking into consideration the rate of channel variations and round-trip time adaptation delay. For the case of static channel affected by rain fading a subset of 11 MODCODs has been identified to offer the optimal trade-off between the system complexity and performance in terms of average spectral efficiency, while in mobile channel conditions, where the rate of variations is much higher, a subset of 7 MODCODs provides the best compromise between the average spectral efficiency and the maximum adaptation time. Modifications of the existing ACM procedures intended for satellite operating environment have also been proposed in order to successfully mitigate the effects not intended for the compensation by ACM in different propagation conditions. ACKNOWLEDGMENT This work has been partially funded by the European Community through the 6th Framework Programme IST project SatNEx (FP6-IST-027393).

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Figure 5. Average spectral efficiency and maximum down-switch adaptation time in dependance of the increasing number of MODCODs (MODCOD subsets) in static operating scenario

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