Wireless SPIHT-encoded image transmission employing hierarchical modulation: A DSP

implementation Martin Zamkotsian*t, Kostas P. Peppas*, George Fovakis*, Fotis Lazarakis*, Antonis Alexandridis*,

Kostas Dangakis*, and Panayotis G. Cottis t *Laboratory of Wireless Communications, Institute of Informatics and Telecommunications,

National Centre for Scientific Research "Demokritos",

Patriarhou Grigoriou & Neapoleos, Agia Paraskevi, 15310, Athens, Greece. Email: mzamko@iit.demokritos.gr tNational Technical University of Athens, Department of Electrical and Computer Engineering

GR 15773 Athens, Greece.

Abstract-In this paper, the performance of wire­less transmission of SPIHT-encoded images employ­ing Hierarchical Quadrature Amplitude Modulation (HQAM) is investigated with an experimental test-bed. Two Texas Instruments (TI) Digital Starter Kits (DSK), each one equipped with the floating point DSP chip TMS320C6713, are employed for the system testing, one for the transmitter and one for the receiver. The digital signal processing that formats the information data in preparation for transmission as well as the digital signal processing that recovers the informa­tion data at the receiver site are described in detail. Various results measuring bit error rates and peak signal-to-noise ratios are presented to demonstrate the performance of the experimental setup under various channel conditions, for different values of the modulation parameters.

Index Terms-Hierarchical Quadrature Amplitude Modulation (HQAM), SPIHT algorithm, Discrete Wavelet Transform (DWT), Unequal Error Protection (UEP), Experimental Results, Wireless test-bed.

I. INTRODUCTION

Wireless transmission of compressed images is a challenging task because of high error rates resulting from the impairments of the wireless environment, limited bandwidth availability and low energy require­ments. Wavelet-based embedded (or progressive) im­age coders are most suited to cope with the time vary­ing channel bandwidth of wireless systems. Several wavelet-based algorithms for image compression that result in practical advances such as superior low-bit rate performance, continuous-tone and bit-level com­pression, lossless and lossy compression are available in the open technical literature. Representative exam­ples can be found in [1]-[5] and references therein.

One of the most widely used wavelet-based tech­niques for image compression is the Set Partitioning in Hierarchical Trees (SPIHT) [1] because of its high per­formance in terms of peak signal-to-noise ratio (PSNR) for given compression ratios and for a wide variety of

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images. On the other hand, the SPIHT algorithm suf­fers from poor error resilience. Specifically, even single bit errors can cause loss of synchronization between the encoder and decoder. Furthermore, a single error is likely to cause other bits to be decoded incorrectly as well, thus resulting in a severely distorted received image.

In order to address such issues, unequal error protection (UEP) to the transmitted bits has been proposed where information of high priority (HP) is guaranteed to be reliably transmitted under adverse channel conditions while information of lower prior­ity (LP) may be reliably transmitted under favorable transmission conditions. An efficient method to ac­complish UEP is hierarchical quadrature amplitude modulation (HQAM) [6]-[10], where a non-uniform signal constellation is employed to guarantee differ­ent degrees of protection. HQAM has been included in several standards, such as DVB-H, DVB-SH and WiMAX (IEEE 802.16) and has been demonstrated as an efficient transmission scheme achieving satisfac­tory system performance.

Motivated by the above mentioned facts, in this paper, the performance of wireless transmission of SPIHT-encoded images when HQAM is employed, is analysed in a practical DSP-based test-bed. The ex­perimental setup employs two Texas Instruments (TI) Digital Starter Kits (DSK), each one equipped with the floating point DSP chip TMS320C6713 at the trans­mitter and receiver. The entire transmission/reception chain as well as the design of the corresponding hard­ware and software are explained in detail. Various results are presented to demonstrate the functionality of the proposed experimental setup.

The remainder of this paper is structured as follows: Section II provides a detailed description of the im­plementation of the test-bed, including the software parts and the RF front-end. In Section III, various

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! .•••..•.....•••.....•••... �����.�.�!��9.�! .................... !

Fig. 1. A block diagram of the software test-bed part.

ATl Atten:9dB MIXI-TX

-fromTX DSP

ATZ

Fig. 2. A block diagram of the RF front-end.

experimental results illustrating the functionality of the test-bed are provided. Finally, Section IV concludes the paper with a summary of the main results.

II. SYSTEM MODEL AND EXPERIMENTAL SETUP

In this section, a detailed explanation of the test­bed set-up and the transmission chain is provided. The main components of the test-bed are the software parts of the transmission and reception chains and the RF front-end. A block diagram of the test-bed software implementation is depicted in Fig. 1. The software consists of the source encoding and decoding of the in­put images and the DSP-based implementation of the transmit/receive chains. The RF front-end, depicted in Fig. 2, provides the required functionality for the successful transmission and reception of the image at 2465MHz.

A. Test-bed Transmitter Software

A Visual C++ program was developed to encode the input image employing the SPIHT algorithm. The resulting binary sequence is fed to the transmitter DSK, DSP-Tx, which processes the information data to be transmitted by the Tx-antenna. The receiver

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DSK processes the received data from the Rx-antenna and recovers the original information data stream. Specifically, considering the transmitter, the input bit sequence is first mapped to complex HQAM-symbols, which are then up-sampled four times and pulse­shaped employing a root-raised cosine pulse shaping filter. The resulting complex baseband signal is then

split into an in-phase (I) and a quadrature (Q) com­ponent, up-converted to 10kHz and sent to the radio­frequency (RF) Tx front-end.

1) Image Source Encoding: For test purposes, a

512 x 512 gray-scaled picture is transmitted, after being encoding by a Packetized SPIHT algorithm [11]. This algorithm is more robust to channel errors than the conventional SPIHT algorithm, since it transmits data

employing independently decodable packets. There­fore, a single error only affects the recovery of the packet within it occurs. To generate independent data packets, a two dimensional Discrete Wavelet Trans­

form (2-D DWT) is first employed to encode the source information. The resulting coefficients of the 2-D DWT are used as the input to the Packetized SPIHT encod­ing process. The number of generated SPIHT packets is Npackets = 22(Lmax-L) where L is the wavelet decom­position level and Lmax = log

2(512) = 9. In this work,

a 6-level wavelet decomposition is employed, resulting in 64 equal-sized independent SPIHT packets.

Each packet is generated employing the two-pass conventional SPIHT algorithm after accessing the 22L = 4096 relevant wavelet coefficients. During the first pass (sorting pass) the so-called "significance map" is determined, consisting of two kinds of bits, i.e. the significance and the sign bits. The former encode the entries of the SPIHT lists with values exceeding a predefined threshold (which is a power of two), whereas the latter encode the sign of the wavelet coef­ficient becoming significant in the current pass. During the second pass (refinement pass), refinement bits are generated to provide additional information about the amplitude of the significant wavelet coefficients.

To partition each packet information into two prior­ity layers, the corresponding data stream is first sorted in descending priority order, as follows: Significance bits are classified as the most significant, since a single error may result in dropping the entire packet. Hence, they are placed first (of higher priority) in the sorted data stream. Of lower importance are the sign and refinement bits since an error only affects the value of the corresponding coefficient. However, the sign of coefficient is more important than its exact amplitude and therefore the former are classified as more important than the latter and, thus, sign bits are placed after the significance bits in the sorted data stream.

A compression rate equal to 1 is used, meaning that the output bit stream of the Packetized SPIHT

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algorithm is of size 512 . 512 = 262144, corresponding to 4096 bits per packet. This stream is divided into two segments of equal length where the 2048 Most Significant Bits (MSB), which are the first being sorted in the output stream, are assigned to the High Prior­

ity (HP) layer, whereas the remaining 2048 bits are assigned to the Low Priority (LP) layer. At the end of the Packetised SPIHT algorithm, both the HP and the LP streams contain 131072 bits, corresponding to 64 independently transmitted packets. These two layer bitstreams are fed to the input of the transmitting

DSK. Finally, it is assumed that the number of sig­nificance, sign and refinement bits for each packet is known at the receiver.

2) Modulation: Incoming bits are modulated em­ploying a 16-HQAM modulation. Since the two priority layer streams are of the same length, 2 bits are as­signed to each layer. An important parameter for every hierarchical modulation is the ratio ex = dHP / dLP, shown in Fig. 3. The higher the value of ex, the better the error performance of the HP layer in given channel conditions.

3) Frame Packing: The incoming data to the trans­mitting DSP is split into frames, each consisting of 512

samples. Three categories of frames are used:

• Carrier frames, which consist of samples of a sinusoidal carrier with frequency equal to 10kHz. This carrier is useful to determine the beginning

of the transmission at the receiver side, as well as for frequency estimation purposes.

• Synchronization (Synch) frames, which consist of a training sequence employed for synchronization purposes.

• Data frames, which consist of pilot sequence, use­ful for channel estimation purposes, as well as of the actual transmitted 16-HQAM modulated data symbols.

The structure of the frames employed by the consid­ered experimental setup is depicted in Fig 4. Each super-frame consists of three carrier frames, one synch and twelve data frames. The organization of frames into super-frames as depicted in Fig. 4, enhances per­formance since frequency estimation and synchroniza­tion are periodically performed.

4) Up-Sampling and Filtering: Up-sampling and pulse shaping are employed for inter-symbol interfer­ence (lSI) reduction [12]. Each frame is up-sampled

with a ratio of 4, and then passed through a root raised cosine (RRC)-finite impulse response (FIR) fil­ter having 64 taps and a roll-off factor of 0.22. Up­sampling is performed by adding three zeros between every sample. In this work, an efficient 4-phase joint implementation of the pulse shaping filter and up­sampling was adopted. This filter employs the overlap­add method [13] to process data in a frame-by-frame

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dHP • • ---1--"'--• •

·dL� • •

• • • • • • • •

Fig. 3. 16-HQAM constellation with modulation parameter a =

dHP/dLP.

basis.

Super·frame (16 frames) � ________ �A� __________ �

x3

Pilot & Data

Data (120 symbols)

�------�y�------� x12

Fig. 4. Frame structure of the experimental setup.

5) Training Sequence: Synchronization is performed on a known training sequence of length 128. The received training sequence is then cross-correlated with the locally stored, known, training sequence. Ideally, the training sequence t(n) should be white, i.e. lE[t(n)t(n + k)] = 5(k) with 5(-) denoting the Kro­necker delta. This important property results in a better estimation of the correct sampling instant at the receiver side. Finally, the training sequence is BPSK-modulated, rendering the synchronization pro­cess more robust.

6) Pilot Symbols: Channel estimation is an impor­tant task that guarantees the correct detection of the modulated symbols. In this work, the least squares (LS) channel estimation algorithm with local orthog­onal pilot sequences is employed to estimate the chan­nel [14]. To this end, eight BPSK modulated pilot symbols are added at the start of each data frame.

7) Up-Conversion: The transmitting DSP output af­ter pulse shaping and up-sampling is a base-band sig­nal with one-sided bandwidth equal to 7kHz. However, before being sent to the RF front-end, the DSK output Tx signal is converted into a pass-band with a center frequency of 10kHz. This conversion can be expressed as

SRp(n) = � { sss(n) exp (J27r �: n) } (1)

where sss(n) = AJ(n) + JAQ(n) is the complex base­band signal with AJ(n) and AQ(n) being its in-phase and quadrature components, respectively, SRF (n) is the up-converted signal, ie is the carrier frequency of 10kHz and is is the sampling frequency of 44. 1kHz.

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B. Test-bed Receiver DSP Software

After being processed by the RF front-end, the frequency of the pass-band signal at the input of the receiver DSK is estimated employing a digital Phase-Locked-Loop (PLL) structure. This estimate is then used to down-convert the pass-band signal and retrieve its I- and Q-components. A matched filter­ing with a root-raised cosine is then employed. The matched filter also acts as a low-pass filter which removes the high frequency component of the down­converted signal. Synchronization is then performed

and the optimal sampling instant is determined. Sam­ples are reconstructed and channel estimates are cal­culated to be employed by a Maximum Likelihood (ML) detector.

1) Frequency Offset Compensation: A critical task performed at the receiver of any communication sys­tem is the compensation of the difference between frequencies generated by local oscillators at the trans­mitter and receiver. The frequency offset introduces time-varying phase shift and rotates the signal con­stellation. A common robust technique to mitigate the deleterious impact of the frequency offset on the re­ceiver performance is to employ a Digital Phase Locked Loop (DPLL). The frequency offset compensation is accomplished by transmitting three frames of sinusoid carrier before the actual data transmission. This sinu­soid is fed to the DPLL at the receiver, which in turn adaptively tracks the frequency difference between two local oscillators.

2) Down Conversion: The received pass-band signal, r b (n) is down-converted by employing a carrier with P A

the estimated frequency Ie. Specifically, the I- and Q-components are retrieved by multiplying rpb (n) with

cos (27r]en) and sin (27r]en) , respectively.

3) Low-Pass Filtering, Matched Filtering and Down­

sampling: Mter down-conversion, low-pass filtering is employed to eliminate high-frequency components. At the same time, matched filtering and down-sampling is also performed. A FIR root-raised cosine filter having 64 taps performs the three-fold processing. The im­pulse response of the matched filter, h( n) is given by h(n) = g (n) , where g (n) is the impulse response of the pulse-shaping filter at the transmitter. At the receiver, however, there are no zero samples and therefore no poly-phase implementation is needed.

4) Synchronization: Synchronization is a critical task that guarantees the reliability of the experimen­tal setup. In this work, synchronization is performed in two phases: During the first phase, the receiver evaluates the time instance that data transmission starts. To this end, when the receiver is activated for the first time, it evaluates the cross-correlation of a sinusoidal carrier, stored at the DSP memory with the received carrier and compares it with a predefined

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threshold. If the presence of the carrier is detected by the receiver, the value of the above mentioned cross correlation exceeds the predefined threshold and the receiver decides that data transmission has started. The corresponding time instance, noffset, is used by the second phase to perform a more accurate synchroniza­tion. During the second phase, the received training sequences, rt (n) , are cross-correlated with the already known training sequence at the transmitter side, t (n) , stored at the receiver DSP. This cross-correlation can be expressed as

c(n) = L rt(n + k)t(k) (2)

k

The optimal sampling instant is the time when the magnitude of c( n) is maximized, plus the time offset determined from the first phase, i.e.

noptim = noffset + arg max c( n) n

(3)

5) Channel Estimation: Assuming slow-varying fad­ing conditions, the complex channel impulse response h is assumed constant within a frame. Channel estima­tion is performed employing a least squares channel algorithm. Specifically, let r( n) be the received pilot sequence and p( n) the already known pilot symbols, stored at the receiver DSP. The received pilot sequence can be expressed as

r(i)=h·p(i)+w(i),i=1, ... ,8 (4)

where w( i) is the noise sequence. The impulse response can be estimated by taking the dot product between r( i) and p( i), that is

h � L�=l r(i) . p(i) (5)

L�=1Ip(i)12 6) Maximum likelihood detection: The Maximum

Likelihood optimal detector is employed, which can be expressed as

s = argmin li s - srll (6) sE§

where s is the detected symbol, § the set of all 16-HQAM constellation points and Sr the received base­band signal.

7) Image Source Decoding: The inverse Packetized SPIHT algorithm along with the 2-D inverse DWT (IDWT) is employed using a Visual C++ program to reconstruct the transmitted image. The resulting bit error rates and the corresponding PSNR are also recorded.

C. RF Front-End

The RF hardware guarantees the successful trans­mission and reception of the RF signal at 2465MHz. All employed mixers at both the transmitter and the receiver are double-balanced with low conversion loss. The local oscillators to the IF- and RF- stage mixers

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Fig. 5. The experimental prototype equipment for the measurement campaign.

employ Rodhe & Schwarz RF signal generators. Also, power supplies of 5V and 15V are employed to the active filter and the Low Noise Amplifiers (LNA), respectively.

At the transmitter side, the pass-band signal gener­ated by the Tx DSP is fed to a 9dB fixed attenuator. The attenuator ensures protection of the devices em­ployed in the Tx chain and also serves for impedance matching purposes (the characteristic impedance of the transmission lines is equal to Zo = 50Sl). The resulting signal is then up-converted to 30MHz and filtered, employing a narrow band crystal filter with a bandwidth of 20kHz. Filtering eliminates higher order harmonics as well as intermodulation products gener­ated by the mixer. Before filtering, another attenuator

is also used in order to keep other devices isolated and eliminate possible out-of-band reflections generated at next stages of the Tx chain. The filtered signal is amplified employing an LNA with a gain of 20dB. The amplified signal is finally up-converted to 2465MHz and transmitted employing a vertically polarized patch antenna with a 6dBi peak gain. At the receiver side, the impinging signal at the receive antenna is first amplified by a LNA, having a very low noise figure (0.76dB) and gain equal to 15dB. A band-pass filter is employed to eliminate co-channel interference due to other wireless applications operating at the 2.4GHz ISM band as well as higher order harmonic frequencies generated by the LNA. The filtered signal is down­converted at 30MHz, employing also a crystal filter that eliminates undesired frequencies. The resulting signal is amplified by a LNA having gain equal to 18dB and down-converted to 10kHz. Finally, a 3-pole Butterworth low-pass active filter is employed in order to eliminate the undesired frequencies of the input signal at the receiver DSP Analog-to-Digital converter.

III. EXPERIMENTAL RESULTS

A. Measurement Campaign

A gray-scaled 512 x 512 bitmap image, Lena.bmp, is sent to obtain the experimental results. The 131072

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information bits for both the HP and LP layers are packed in i2��3112

0072l = 547 frames. As shown in Fig. 4, each frame consists of 120 16-HQAM modulated sym­bols. Based on the super-frame structure described in Section II, i5;t;l = 46 super-frames are transmitted, wherefrom the first 45 are complete whereas the last one transmits 7 data frames. Two setups are consid­ered: The first employs a fixed 53-dB attenuator be­tween the transmit and receive RF chains, emulating a free space propagation environment. The second setup is performed indoors in a officellaboratory and employs

over-the-air real-time communication by means of the RF subsystem described above. The host PCs, DSK kits and RF devices employed during the experiments are illustrated in Fig. 5.

B. Experimental Results

The experimental results for both experimental se­tups are depicted in Table I considering the two­layer bit error rate (BER) performance, i.e. BERHP and BERLP, and the PSNR. The corresponding values of the carrier-to-noise ratio (C / No) and modulation parameter a are also presented. As it is evident, for low values of C / No uniform QAM (a = 1) cannot yield high PSNR, due to the inadequate HP performance. On the other hand, when HQAM is employed with a = 4 and a = 1.75 for the two considered setups, respectively, a significant BERHP improvement is ob­served, resulting in higher PSNR values. This can be observed comparing Fig. 6(a) with Fig. 6(b) and

Fig. 7(a) with Fig. 7(c) for the two setups, where the quality of retrieved images is enhanced by employing hierarchical modulation. Finally, note that for large values of C / No both experimental setups yield high PSNR values. The almost perfectly retrieved images observed in Figs. 6(c) and 7(c) for both setups indicate the correctness of the design and implementation of the experimental test-bed.

IV. CONCLUSION

In this paper a DSP implementation of wireless transmission of SPIHT-encoded images is presented. A 16-HQAM modulation was employed to accomplish unequal error protection and henceforth enhance the received image quality. Various experimental results demonstrated the effect of the modulation parameters on the performance of the proposed system as well as the functionality of the suggested implementation.

V ACKNOWLEDGEMENT

The authors would like to thank Texas Instruments for supporting this work via the TI European Univer­sity Program.

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TABLE I MEASURED BER OF HP AND LP LAYERS AND THE CORRESPONDING PSNR VALUES FOR BOTH EXPERIMENTAL SETUPS

Fixed Attenuator Patch Antennas 0<=1 0<=1 0<=4 0<=1 0<=1 0< = 1.75

GINo(dB) 25.6 13.6 13.6 32.1 19.8 19.8 BERHP 0 2.77 X 10-4 7.69 X 10-6 0 5.1S X 10-3 2.S5 X 10-4 BERLP 7.69 X 10-6 2.2 X 10-2 2.S X 10-2 2.31 X 10-5 4.49 X 10-2 5.24 X 10-2

PSNR(dB) 35.19 18.2 22.58 34.54 7.76 9.67

(a) 0< = 1, PSNR = 1S.2dB, (b) 0< = 4, PSNR = 22.5SdB, GINo = 13.6dB GINo = 13.6dB

(c) 0< = 1, PSNR = 35.19dB, GINo = 25.6dB

Fig. 6. Reconstructed Lena for various values of 0< and GINo when fixed attenuator (53dB) is employed

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(a) 0< = 1, PSNR = 7.76dB, (b) 0< 1.75, PSNR GINo = 19.5dB 9.67dB, GINo = 19.5dB

(c) 0< = 1, PSNR = 34.54dB, GINo = 32.1dB

Fig. 7. Reconstructed Lena for various values of 0< and G I No for over-the-air communication in an indoor environment

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