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Direct-sequence spread spectrum

Direct-sequence spread spectrum (DSSS) is a digital modulation technique in that spreads a narrowband data signal across a much wider by multiplying it with a high-rate pseudo-random (PN) sequence, known as the spreading code or chipping sequence. This process increases the transmission's chip rate—typically by a factor of 10 to 1000—resulting in a signal that resembles wideband to unauthorized receivers, while enabling the intended receiver to despread and recover the original data through correlation with the identical PN sequence. The core principle relies on the or low of PN codes, such as maximal-length sequences (m-sequences) or , to minimize between signals. In operation, the transmitter modulates the data bits—often using binary phase-shift keying (BPSK)—with the PN code before carrier modulation, producing a spectrum shaped like (\sin x / x)^2 with bandwidth approximately twice the code clock rate. At the receiver, despreading involves multiplying the incoming signal with the synchronized PN code, collapsing the bandwidth back to the original data rate and providing a processing gain equal to the ratio of spread bandwidth to data bandwidth (e.g., G_p = N, where N is per bit). This gain, often 10–60 dB, enhances against narrowband interference and jamming, as uncorrelated noise spreads further while the desired signal coheres. DSSS also combats multipath fading through rake receivers, which align and combine delayed signal paths using code timing offsets. Key advantages of DSSS include low probability of interception (LPI) due to its noise-like appearance, robust multi-user access via (CDMA) with orthogonal codes like , and simplified equalization compared to narrowband systems. However, it requires precise and to address the near-far problem, where stronger signals can overwhelm weaker ones. Applications span military secure communications, commercial wireless systems, and ; notable implementations include the (GPS) for civilian and military positioning, 3G cellular standards like IS-95/CDMA2000 and WCDMA, and IEEE 802.11b WLANs.

Overview and History

Definition and Basic Concept

Direct-sequence spread spectrum (DSSS) is a modulation technique in which a data signal is multiplied by a pseudonoise (PN) code sequence running at a much higher rate than the data rate, thereby spreading the narrowband information signal across a much wider bandwidth to create a wideband signal. This spreading process enhances the signal's resistance to interference and jamming by distributing its energy over a broader frequency spectrum. The core concept of DSSS involves transforming an original signal with bandwidth B into a spread signal occupying a bandwidth of approximately N \times B, where N is the spreading factor determined by the length of the PN code. Although the total transmitted power remains constant, the power spectral density decreases proportionally due to the expanded bandwidth, causing the DSSS signal to resemble broadband noise to unintended receivers or interferers. Key parameters include the chip rate R_c, which is the rate at which the PN code chips are generated and defines the spread bandwidth (approximately $2R_c for the ), and the data rate R_b, the rate of the original information bits. The processing gain G_p, a measure of the spreading benefit, is given by G_p = \frac{R_c}{R_b} and typically ranges from 10 to 1000 in practical systems, providing interference suppression on the order of 10 to 30 . A simple of a DSSS transmitter illustrates the process: the input data bits at rate R_b are fed into a multiplier, where they are combined with the PN sequence generated at chip rate R_c; the output of this spreader is then modulated onto a carrier frequency for over the channel. At the receiver, the same PN is used to despread the signal, collapsing it back to the original . This structure ensures that only receivers synchronized with the correct can recover the data effectively.

Historical Development

The origins of direct-sequence spread spectrum (DSSS) trace back to , when engineers sought methods to mask communications signals for secrecy and interference resistance. In 1935, Paul Kotowski and Kurt Dannehl at developed an early DS-SS-like system that embedded voice signals within broadband noise to obscure transmissions, receiving a U.S. in 1940 (US2211132A) for this noise-modulation technique aimed at secure telephony. These early concepts laid the theoretical groundwork, though practical implementations remained limited due to technological constraints and wartime secrecy. Military applications drove DSSS advancements in the 1950s and , primarily for anti-jamming and secure communications. At NASA's (JPL), the CODORAC system—developed from 1952 to 1953 by Eberhardt Rechtin, Richard Jaffe, and Walt Victor—employed DS-SS for reliable rocket telemetry control, achieving robust signal recovery in noisy environments. In 1953, the U.S. Air Force's ARC-50 project introduced DS-SS for radios. By the , DSSS featured in systems like the F9C transcontinental network (operational from 1954) and NASA's (1969–1974), where it supported deep-space links resistant to . The 1973 (JTIDS), a U.S. military initiative, integrated DS-SS for secure, jam-resistant tactical data links among aircraft and ground forces. Concurrently, the GPS program, initiated in the early 1970s, adopted DSSS as its core for civilian and military satellite navigation, enabling precise pseudoranging via codes. Commercialization emerged in the late and , transitioning DSSS from classified military use to broader applications. In satellite communications, early adoption occurred through systems like Equatorial Communications' multiple-access schemes in the , leveraging DS-SS for efficient bandwidth sharing. pioneered DSSS-based (CDMA) for cellular networks, publicly demonstrating a on November 7, 1989, that used spreading codes to support multiple users over shared spectrum. This culminated in the 1993 release of Interim Standard IS-95 (cdmaOne), the first widespread commercial DSSS standard for cellular, operating at 1.25 MHz bandwidth with a 19.3 processing for mitigation. The 1990s marked the shift to fully digital DSSS implementations, enabling scalable mobile networks. IS-95's revisions (IS-95A in 1995 and IS-95B) enhanced data rates and integration, paving the way for 3G evolution. In the , DSSS influenced the Universal Mobile Telecommunications System () under IMT-2000, with wideband CDMA (W-CDMA) using a 3.84 Mcps chip rate for high-speed packet data in uplink (1920–1980 MHz) and downlink (2110–2170 MHz) bands. This progression from analog military prototypes to digital standards solidified DSSS's role in resilient, spectrum-efficient communications.

Technical Principles

Spreading Codes and Sequences

In direct-sequence spread spectrum (DSSS) systems, spreading codes, also known as pseudonoise () codes, are sequences that modulate the signal to its . These sequences consist of represented as +1 and -1 (or equivalently 0 and 1 in ) and are designed to appear random while being fully deterministic, enabling reliable generation and replication at the . codes are typically produced using linear feedback shift registers (LFSRs), which implement a linear over the GF(2) to generate long periods of pseudo-random bits. Common types of PN codes used in DSSS include maximal-length sequences (m-sequences) and . M-sequences, generated by LFSRs with primitive feedback polynomials, have a length of N = 2^n - 1, where n is the register degree, and exhibit balanced runs of 0s and 1s, making them ideal for single-user spreading. , constructed by modulo-2 addition of two preferred m-sequences from LFSRs of the same length, provide large families of codes with bounded , suitable for (CDMA) applications. Orthogonal codes such as Walsh codes, derived from Walsh-Hadamard matrices, are binary sequences of length $2^k, ensuring zero when time-aligned, which supports multi-user in synchronous DSSS environments. Key properties of these codes enable effective spreading and despreading in DSSS. Autocorrelation measures the similarity of a code with its time-shifted version; for m-sequences, it features a sharp of value N at zero lag and low of -1 elsewhere, facilitating precise and despreading by compressing the spread signal energy. Cross-correlation quantifies interference between different codes; m-sequences have potentially high cross-correlation, but achieve low out-of-phase values (bounded by $2^{(n+2)/2} + 1 for odd n), while Walsh codes exhibit perfect (zero cross-correlation) for aligned sequences, minimizing multi-user interference. These properties contribute to the processing gain in DSSS, which is approximately equal to the code length N. PN codes are generated via LFSRs configured with a characteristic polynomial that defines the feedback taps. For example, a 3-stage LFSR using the primitive polynomial x^3 + x^2 + 1 (taps on stages 3 and 2) initialized to [1, 1, 1] produces the repeating m-sequence 1,1,1,0,1,0,0, with period 7. The rate R_c determines the duration of each T_c = 1 / R_c, where shorter T_c increases the spreading and bandwidth expansion. Longer codes (higher n) yield greater processing gain but require more computational resources for generation and .

Modulation and Transmission Process

In direct-sequence spread spectrum (DSSS) systems, the modulation and transmission process begins with the preparation of the input data signal, which consists of a binary stream of bits transmitted at a rate R_b bits per second, with each bit having a duration T_b = 1 / R_b. The data bits are typically represented as d(t) = \sum_{k} d_k p_{T_b}(t - k T_b), where d_k \in \{+1, -1\} (or equivalently 0 and 1 mapped to bipolar values) and p_{T_b}(t) is a rectangular pulse shaping function over the bit interval. The spreading step follows, where the narrowband signal is multiplied by a pseudonoise () code to expand its . The code, generated at a much higher chip rate R_c \gg R_b (with chip duration T_c = 1 / R_c), is represented as c(t) = \sum_{m} c_m p_{T_c}(t - m T_c), where c_m \in \{+1, -1\}. The spread signal is then formed as s(t) = d(t) \cdot c(t), effectively modulating each data bit with a of N = R_c / R_b , which spreads the signal . This is often implemented using an exclusive-OR () gate for signals, equivalent to in the . Next, the spread baseband signal s(t) is modulated onto a radio-frequency carrier for transmission. A common approach is binary phase-shift keying (BPSK), where the transmitted signal is x(t) = \sqrt{2P} \, s(t) \cos(2\pi f_c t), with P denoting the transmit power and f_c the carrier frequency. Other variants, such as quadrature phase-shift keying (QPSK), may be used for higher , but BPSK is prevalent in basic DSSS implementations due to its simplicity. This spreading process results in bandwidth expansion, where the original data bandwidth of approximately $2 R_b is increased to approximately $2 R_c for BPSK modulation, reflecting the chip rate dominance. The gain, defined as G_p = R_c / R_b = T_b / T_c, quantifies the bandwidth spreading factor and is typically on the order of 100 or more in practical systems. The transmitter structure can be described via a consisting of key components: a data source providing the input ; a PN code generator producing the high-rate spreading sequence (often via a ); a multiplier or for combining the data and code to form the spread signal; a modulator (e.g., BPSK) to upconvert to the carrier; and a power amplifier to boost the signal for . In some designs, a precoder or filter may precede spreading to shape the data pulses.

Signal Processing and Demodulation

Despreading and Correlation

In direct-sequence spread spectrum (DS-SS) receivers, despreading recovers the original data signal from the wideband received signal r(t) by exploiting the properties of the spreading code. This process requires precise to align the receiver's local code replica with the incoming signal, followed by and to collapse the spectrum back to the original data rate R_b. The despreading operation enhances the (SNR) by spreading interference while concentrating the desired signal energy. Synchronization begins with code phase acquisition to determine the timing offset between the received pseudonoise (PN) code and the local , typically using a sliding correlator. In this method, the local is shifted relative to the received signal at a rate faster than the chip rate (e.g., by tuning a ), producing a peak when occurs within one duration. Once acquired, tracking maintains via a delay-lock (DLL), which generates early, punctual, and late versions of the local offset by half a ; the in outputs from the early and late branches adjusts the local timing to minimize misalignment. phase is achieved concurrently, often using a (PLL) or to recover the carrier frequency and , ensuring coherent . These steps enable accurate despreading, with acquisition times on the order of milliseconds for typical PN sequences. Despreading proceeds by multiplying the synchronized received signal r(t), which includes the spread data d(t), spreading code c(t), and noise n(t), with the local code replica c(t): y(t) = r(t) \cdot c(t) = d(t) + n(t) \cdot c(t) Since c(t) has values of \pm 1, this multiplication despreads the data term d(t) to its original bandwidth around R_b, while the noise term n(t) \cdot c(t) remains spread over the wider chip rate bandwidth R_c. To extract the data bit, the despread signal y(t) is then integrated (correlated) over the bit period T_b = 1/R_b: \hat{d} = \int_{0}^{T_b} y(t) \, dt A decision is made based on the sign of \hat{d}: positive for bit 1 and negative for bit 0, yielding a processing gain of $10 \log_{10}(R_c / R_b) dB that suppresses interference. In multi-user environments like code-division multiple-access (CDMA), each user employs a unique spreading code orthogonal to others, allowing simultaneous despreading of multiple signals from the shared bandwidth. The rake receiver addresses multipath propagation by deploying multiple correlator fingers, each despreading a distinct delayed path using a time-shifted local code replica. The finger outputs are combined via maximal-ratio combining, weighting each by its channel gain to maximize SNR and mitigate fading; for example, in wideband CDMA (W-CDMA), up to 8 fingers per channel can be allocated based on path searches. This structure collects energy from resolvable paths separated by more than one chip duration. Errors in despreading arise primarily from carrier phase offsets, which degrade coherent and reduce effective SNR, and code misalignment, where timing errors exceeding a of the chip cause partial and processing (e.g., 3 at half-chip for codes). Doppler shifts or clock drifts exacerbate these issues, necessitating robust tracking loops to maintain alignment within 1/8 chip for optimal performance.

Mathematical Foundations

The mathematical foundations of direct-sequence spread spectrum (DSSS) rely on the of with a spreading to achieve expansion, followed by correlation-based recovery at the receiver. The transmitted signal in a DSSS system can be expressed as x(t) = \sum_{k} d_k \, c(t - k T_b) \, \cos(2\pi f_c t), where d_k represents the k-th (typically \pm 1), T_b is the bit , f_c is the , and c(t) is the spreading waveform given by c(t) = \sum_{m} c_m \, p(t - m T_c). Here, c_m = \pm 1 are the code chips, T_c is the chip duration with T_b = N T_c and N the number of chips per bit (processing gain factor), and p(t) is a rectangular pulse of unit amplitude over [0, T_c). This formulation spreads the narrowband data signal across a wider bandwidth determined by the chip rate $1/T_c. The spreading code c(t) is typically generated using pseudonoise (PN) sequences, such as maximal-length sequences (m-sequences), which exhibit ideal two-level autocorrelation properties essential for despreading. The normalized discrete autocorrelation function of an m-sequence of length N = 2^l - 1 (where l is the degree of the generator polynomial) is R_c(\tau) = \frac{1}{N} \sum_{i=0}^{N-1} c_i c_{i+\tau} \approx \begin{cases} 1 & \tau = 0 \pmod{N}, \\ -1/N & \text{otherwise}. \end{cases} This sharp peak at zero lag and near-zero values elsewhere enable the receiver to synchronize and recover the data with minimal self-interference. The approximation holds for large N, where sidelobes approach white noise-like behavior. At the receiver, despreading involves multiplying the received signal r(t) = x(t) + n(t) (where n(t) is ) by a locally generated of the c(t) and ing. Assuming perfect , the output of the for the k-th bit interval approximates y_k \approx d_k G_p + \eta_k, where G_p = N is the processing gain, and \eta_k is a with variance scaled by $1/G_p relative to the input. This collapses the spread signal back to the original data , concentrating the signal power while spreading the noise. The power spectral density (PSD) of the DSSS signal reflects its noise-like spreading, appearing flat over the chip-rate bandwidth. For large N, the baseband PSD is approximately S_x(f) \approx \frac{P T_c}{2} \left( \frac{\sin(\pi (f - f_c) T_c)}{\pi (f - f_c) T_c} \right)^2, or equivalently, a nearly constant level P / R_c (where R_c = 1/T_c is the chip rate) for |f - f_c| < R_c/2, with sidelobes decaying as $1/f^2. This uniform, low-amplitude spectrum masks the signal below the noise floor, enhancing security and interference resistance. The processing gain G_p = N provides a theoretical signal-to-noise ratio (SNR) improvement of $10 \log_{10} G_p after despreading, particularly effective against interference. Interference power within the data bandwidth is attenuated by the code's autocorrelation sidelobes, reducing its effective impact by approximately $1/N, while noise is spread evenly. This gain quantifies DSSS's robustness, with typical values of 20–60 in practical systems. In (CDMA) extensions of DSSS, multiple users share the spectrum using distinct codes with low to minimize inter-user interference. For , derived from pairs of m-sequences, the normalized cross-correlation R_{ij}(\tau) between distinct codes i and j takes on values in a small set including -t(l), -1, and t(l)-2, where t(l) = 2^{(l+2)/2} + 1 for even l and t(l) = 2^{(l+1)/2} + 1 for odd l, ensuring effective user separation with bounded multi-access interference proportional to the number of users. These properties, bounded by Welch's theorem, support scalable multi-user operation.

Performance Characteristics

Advantages

Direct-sequence spread spectrum (DSSS) provides significant resistance through its , which spreads the signal over a wide and allows despreading to reject interferers by 10 to 30 or more, depending on the spreading factor. This , defined as the ratio of the chip rate to the data rate expressed in decibels, enables the receiver to correlate the desired signal while treating as , effectively suppressing intentional or unintentional interference. DSSS also offers multipath immunity via the , which captures energy from multiple delayed signal paths by aligning them through and combining them coherently to improve . The orthogonality of spreading codes further reduces () by minimizing cross-correlations between paths, leveraging the low properties of pseudonoise sequences outside the . The noise-like spectrum of DSSS contributes to low probability of intercept (LPI), as the spread signal appears indistinguishable from to unintended receivers without the spreading code, allowing transmission at power levels below the . This inherent privacy is enhanced by the requirement of the correct code for despreading, which acts as an additional encryption layer, preventing unauthorized decoding even if the signal is intercepted. In multiple access scenarios, DSSS enables (CDMA), where unique orthogonal or near-orthogonal codes allow simultaneous transmission from multiple users over the same , increasing system capacity by a factor approximately equal to the processing gain K \approx G_p. This facilitates efficient reuse in cellular systems, as the shared wideband channel supports more users compared to frequency-division or time-division schemes without requiring additional allocation.

Limitations and Challenges

One significant limitation of direct-sequence spread spectrum (DSSS) systems is the near-far problem, where a strong signal from a nearby transmitter overwhelms the receiver, desensitizing it to weaker signals from distant transmitters due to differences. This occurs because interference from co-channel users is proportional to their received power levels, degrading the (SIR) and reducing overall system capacity. To mitigate this, DSSS implementations, particularly in (CDMA) variants, require precise mechanisms to equalize received signal strengths across users. Synchronization in DSSS presents another challenge, as the must acquire and track the spreading , with acquisition time scaling proportionally to the square of the code length N in search strategies, especially under conditions with Doppler-induced offsets. This arises from the need to search a large , often involving correlation over multiple hypotheses, which prolongs initial alignment and increases latency in dynamic environments. In multi-user CDMA applications of DSSS, self- from cross-correlations between spreading codes generates multiple-access (MAI), which limits the supported number of s to fewer than the processing gain G_p. MAI accumulates as grows, elevating levels and degrading bit error () , thereby capping below the theoretical maximum defined by G_p = R_c / R_b, where R_c is the chip and R_b the data . DSSS exhibits bandwidth inefficiency when supporting low data rates in single-user scenarios, as the high chip rate R_c occupies substantial spectrum far exceeding the minimal bandwidth needed for the information signal. This spreading, while beneficial for interference rejection via processing gain, results in low spectral efficiency for isolated low-rate transmissions, underutilizing the allocated bandwidth unless multiple users share it. Implementation of DSSS demands specialized , including high-speed correlators capable of operating at chip rates from MHz to GHz to perform despreading and matching. For instance, correlator designs must achieve processing speeds exceeding 100 MSPS to handle oversampled signals, requiring significant logic resources and pipelined architectures in FPGA or ASIC implementations. Finally, DSSS offers limited protection against wideband , as the processing gain provides less effective suppression when the interference spans the full spread , akin to broadband that permeates the despreading process. In such cases, the margin—determined by the ratio of spread to unspread —is insufficient if the interferer power exceeds system thresholds, leading to desynchronization.

Applications

Wireless Communication Systems

Direct-sequence spread spectrum (DSSS) plays a central role in (CDMA) cellular systems, enabling multiple users to share the same frequency band through orthogonal spreading codes. The IS-95 standard, released in 1995 and commercialized as cdmaOne, employs DSSS with a chip rate of 1.2288 Mcps across a 1.25 MHz , achieving a processing gain of 64 for services by spreading a 19.2 kbps coded rate. This design allows simultaneous transmission of and while mitigating via pseudonoise sequences and Walsh codes for channelization. IS-95's DSSS implementation supported up to 9.6 kbps channels, marking a significant advancement in cellular capacity over analog systems like . This CDMA framework evolved into 3G systems, with wideband CDMA (WCDMA) integrated into the Universal Mobile Telecommunications System () in 2001. WCDMA extends DSSS principles using a higher chip rate of 3.84 Mcps over 5 MHz channels, supporting variable spreading factors from 4 to 512 for flexible data rates up to 2 Mbps. Orthogonal variable spreading factor (OVSF) codes, derived from Walsh-Hadamard matrices, enable efficient multi-rate services while maintaining with IS-95 concepts in core network elements. UMTS's DSSS modulation, typically (QPSK), enhances for multimedia applications in mobile networks. In wireless local area networks, the IEEE 802.11b standard, ratified in 1999, utilizes DSSS in the 2.4 GHz ISM band to achieve data rates up to 11 Mbps. Lower rates of 1 and 2 Mbps employ an 11-chip Barker sequence for spreading, providing robust short-range connectivity over 22 MHz channels spaced 5 MHz apart. Higher rates of 5.5 and 11 Mbps use complementary code keying (CCK), a variant of DSSS that employs sets of 8-chip orthogonal codes to maintain while improving throughput. This DSSS approach, combined with differential binary phase-shift keying (DBPSK) or differential quadrature phase-shift keying (DQPSK), ensures reliable packet transmission in environments with multipath fading. In military applications, DSSS enhances and data communications in tactical radios for anti-jamming resilience in VHF/UHF operations. DSSS in CDMA systems significantly boosts capacity; for instance, IS-95 supports approximately 40-50 simultaneous voice users per cell within a 1.25 MHz , leveraging the processing gain and to manage from neighboring cells. This represents a threefold to tenfold increase over FDMA/TDMA equivalents, depending on reuse factors and loading, with further optimizing resource use by silencing idle channels. Direct-sequence spread spectrum (DSSS) plays a critical role in systems, where it enables precise ranging and positioning by modulating (PRN) codes onto signals, allowing s to distinguish signals from multiple satellites despite . In the (GPS), the civilian coarse/acquisition (C/A) utilizes a sequence consisting of 1023 chips repeating every millisecond at a chip rate of 1.023 MHz, superimposed on the L1 of 1575.42 MHz. This spreading provides resistance to multipath and , with despreading at the correlating the incoming signal against the known PRN to recover the underlying 50 bits per second (bps) data message, which includes satellite and clock information. For military applications, the precision (P(Y)) operates at a higher chip rate of 10.23 MHz on both L1 and frequencies (1227.60 MHz), offering enhanced accuracy and anti-jam performance through a longer period of one week, though the exact Y-code encryption details remain classified. Other Global Navigation Satellite Systems (GNSS) employ DSSS variants for similar ranging purposes. The system, developed by , uses DSSS-based PRN codes in its modern CDMA signals on L1 (around 1602 MHz) and (around 1248 MHz) bands, with ranging codes generated from sequences to enable for satellite discrimination and improved signal acquisition in challenging environments. Galileo's signals, such as E1 (centered at 1575.42 MHz) and E5 (1176.45 MHz and 1191.795 MHz), incorporate DSSS modulation with primary codes like the E1-B in-phase component using a Gold-like sequence for open service ranging, supporting high-precision positioning with data rates up to 125 bps after despreading. In military contexts, DSSS enhances anti-jam capabilities for guided munitions and unmanned systems. The integrates GPS receivers employing DSSS signals to maintain accuracy under conditions, with upgrades incorporating eight-channel anti-jam receivers that leverage the inherent processing gain of DSSS to suppress interference by up to 40 dB or more. For unmanned aerial vehicles (UAVs), DSSS facilitates secure data links by spreading signals across wide bandwidths, reducing detectability and enabling robust command-and-control communications in contested environments, as demonstrated in systems using PN sequences for low-probability-of-intercept transmissions. Emerging applications extend DSSS to resource-constrained domains. In (IoT) sensor networks for low-power wide-area coverage, DSSS variants like those in IEEE 802.15.4g standards provide interference resilience and scalability, allowing battery-powered devices to transmit over kilometers with minimal energy, though often hybridized with other for duty-cycled operation. Underwater acoustic communications benefit from DSSS to combat severe , where rake-like receivers correlate multipath arrivals using PN codes, achieving bit error rates below 10^{-3} at signal-to-noise ratios as low as -10 in shallow-water channels with delays up to 10 ms. Beyond communications, DSSS finds use in non-navigation systems for stealthy operation. Spread-spectrum employing DSSS waveforms transmits low-power, signals that mimic , enabling low-probability-of-intercept detection of targets with range resolutions down to meters, as in designs where yields precise height measurements while evading countermeasures. In grid applications, DSSS via GPS-derived timing signals ensures microsecond-level for measurement units, supporting wide-area monitoring and fault detection by aligning distributed sensors to a common time base resilient to atmospheric disturbances.

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