Phase Noise Impact on Satellite Uplink and Downlink Channel Capacity

Given the substantial cost associated with establishing links in satellite communication systems, maximizing throughput or channel capacity, especially on the uplink, becomes imperative. This white paper aims to delve into the fundamentals of phase noise, its impact on channel capacity, and solutions for achieving optimal phase noise using available technology choices. By addressing these aspects, this white paper provides insights into improving the overall efficiency and reliability of satellite communication systems.

UNDERSTANDING PHASE NOISE

Phase noise represents short-term variations in the timing or phase of a signal. In the context of oscillators, essential for frequency translation in RF chains during satellite communication, the instantaneous frequency fluctuates randomly around the nominal frequency. The characterization of this variation is crucial, and phase noise is often depicted in the frequency domain through a spectral density plot.

To quantify phase noise, the spectral plot displays phase noise measurements in decibels relative to the carrier (dBc) at specified frequency offsets. By integrating the phase plot over these frequency offsets, an RMS value of phase error in radians can be obtained. This value is instrumental in quantifying the contribution of phase noise to the SNR, particularly relevant for estimating its impact on throughput in specific modulation schemes like QAM.

While long-term frequency deviations, often related to temperature, can contribute to phase and frequency errors, this white paper focuses specifically on short-term, random phase variations. Advanced modem techniques are typically employed to track and correct long-term deviations.

SOURCES OF PHASE NOISE IN SATELLITE COMMUNICATION

Regarding satellite transponders, local oscillators in both the receiver and transmitter RF chains are central to frequency translation in satellite systems. Factors contributing to phase noise in a transponder's local oscillator include:

• Crystal Reference Oscillator- The stability of the crystal reference oscillator impacts the precision of the local oscillator.
• Temperature Variations- Fluctuations in temperature can affect the performance of the local oscillator.
• Frequency Multipliers and Dividers- Components involved in frequency multiplication and division contribute to phase noise.
• Nonlinearities in RF Components- Amplifiers and other RF components introduce nonlinearities affecting phase noise.
• Power Supply Noise- Variations in the power supply can impact the stability of the local oscillator.
• External Interference- Unwanted external signals can introduce interference and affect phase noise.
• Radiation Effects- Exposure to radiation in space can influence the performance of the local oscillator.
• Microvibrations- Due to satellite navigation and guidance, attitude control, could affect the phase noise in a lesser degree.

Regarding ground-based equipment, RF chains contribute to phase noise. Fortunately, controlled conditions make it more manageable. Factors contributing to phase noise in ground equipment include:

• Controlled Environmental Conditions- The stable environment of ground-based stations minimizes the impact of external factors on phase noise.
• No Radiation- Ground-based stations are not exposed to the radiation present in space, reducing potential interference.
• Thermal Management- Ground-based stations can implement effective thermal management to control temperature variations.
• Ambient Temperature- Ground-based stations benefit from a more predictable and controlled ambient temperature.
• Maintenance- Regular maintenance helps eliminate aging of components, ensuring consistent performance.
• Sophisticated Circuitry- Ground-based equipment employs sophisticated circuitry, including linear power amplifiers and clean power supplies.
• Volume and Weight Considerations- Designs for ground equipment prioritize performance while considering factors such as volume and weight.

IMPACT OF PHASE NOISE ON SATELLITE COMMUNICATION UPLINK AND DOWNLINK CHANNELS

The effects of phase noise on signal quality are integral to understanding its impact on satellite communication channels. One significant parameter influenced by phase noise is the SNR. By integrating the phase noise spectrum profile over frequency, the resulting RMS phase error, when calculated in dB, represents the SNR due to phase noise alone. While modern digital modulators incorporate algorithms to compensate for static phase errors, optimizing phase noise in design remains crucial. Excessive phase noise and mixer sensitivity contribute to a reduction in sensitivity, highlighting the need for meticulous design considerations to ensure signal quality and reliability.

Quantifying the reduction in channel capacity due to phase noise involves understanding its impact on the bit rate, especially in specific modulation schemes. In any modulation scheme, the bit rate is linked to the SNR, determining the data rate. To quantify this relationship, establishing a communication link in a controlled environment allows for the introduction of phase noise, with subsequent measurement of the Bit Error Rate (BER) at the receiver. Utilizing the corresponding waterfall curve, which depicts the Bit Error Rate versus SNR for a specific modulation scheme, facilitates the estimation of phase noise's impact on channel capacity when integrated in dB.

Several methodologies can be employed to assess the impact of phase noise on channel capacity:

• Laboratory Experiments- Setting up a communication link in a lab environment, introducing controlled phase noise, and measuring its impact on the BER provides practical insights.
• Simulation Software- Leveraging powerful simulation tools such as MATLAB or Python, along with libraries like NumPy and SciPy or specialized communication toolboxes, enables the creation of virtual environments to model and analyse the impact of phase noise.
• Channel Capacity Formulas- Applying theoretical frameworks such as Shannon's capacity formula for noisy channels allows for a mathematical understanding of the impact of different levels of phase noise on channel capacity.
• Phase Noise Modelling Tools- Utilizing various mathematical models and simulation techniques tailored for communication systems aids in accurately representing and understanding the effects of phase noise in satellite communication channels.

MITIGATION STRATEGIES FOR REDUCING PHASE NOISE

Implementing effective mitigation strategies is crucial for reducing phase noise in satellite communication systems. One approach is the utilization of low phase noise oscillators at RF and mm wave frequencies. High-Q resonators at RF frequencies mitigate the need for frequency multiplication, thereby improving phase noise. Dielectric Resonator Oscillators (DROs) represent a noteworthy solution. DROs employ high-Q factor resonators in their oscillation loops, resulting in superior phase noise performance. When synchronized with a reliable reference clock, DROs demonstrate both stability and accuracy, making them a cost-effective option for applications demanding very low phase noise.

Yttrium Iron Garnet (YIG) oscillators, akin to DROs, operate at RF frequencies using a YIG sphere—a low-loss, strong ferrimagnetic material. While YIG oscillators offer exceptional performance, they come with trade-offs such as higher cost and larger size. Additionally, they necessitate magnetic field control for frequency tuning, limiting their suitability for compact or portable applications.

Phased-locked oscillators, employing analog phase detectors in integer mode, present another mitigation strategy. This approach allows for modifying the reference frequency to achieve the desired output frequency. Furthermore, incorporating DROs as Voltage-Controlled Oscillators (VCOs) in synthesizer circuits contributes to minimizing phase noise.

A comprehensive overview of mitigation techniques involves the exploration of advanced modulation schemes, error correction coding, and adaptive signal processing. Advanced modulation schemes enhance the robustness of the communication system by adapting to varying channel conditions. Error correction coding plays a crucial role in compensating for distortions introduced during transmission, while adaptive signal processing dynamically adjusts system parameters to optimize performance in real-time.

The selection of mitigation strategies requires careful consideration of trade-offs. In scenarios where error correction resources are limited and selective, prioritizing a baseline solution that ensures the transmitted signal is as distortion-free as possible becomes important. This approach allocates correction resources to address transmission channel distortions, such as Doppler and atmospheric effects. A synergistic combination of optimal phase noise sources and the corrective capabilities of digital modems positions satellite communication systems closer to achieving the maximum channel capacity as defined by Shannon's law. This strategic amalgamation enhances the overall efficiency and reliability of communication in the presence of phase noise.

FUTURE TRENDS AND CHALLENGES

Satellite communication is continually evolving, driven by the increasing demand for internet bandwidth from many different sources, including internet service providers. As satellite bandwidth becomes increasingly important, there is a pressing need for ground to enhance the purity of communication signals. Future trends in satellite communication technologies will likely focus on innovations that optimize signal quality and bandwidth utilization.

The development of future satellite constellations is important for both governmental and commercial communication. These demands underscore the significance of reliable and efficient satellite communication networks as an essential component for the success of space missions.

The importance of phase noise in shaping the future of satellite communication cannot be overstated. The increasing need for higher bandwidth is steering the industry towards higher carrier frequencies and higher modulation orders. Both advancements demand extremely low phase noise sources, accompanied by linear and low-noise circuits. As satellite communication systems evolve to meet these demands, addressing the challenges associated with phase noise becomes a critical factor in ensuring their efficiency, reliability, and successful operation.

CONCLUSION

In conclusion, our exploration of phase noise in satellite communication underscores its direct impact on the SNR and, consequently, the reduction in channel capacity. To accurately quantify this contribution, the calculation of integrated RMS phase noise in radians provides a valuable metric, with its equivalent in dB representing the SNR. Notably, Dielectric Resonator Oscillators (DROs) based Phase-Locked Loops (PLLs) with analog phase detectors, operating directly at millimeter-wave frequencies, exhibit significantly lower phase noise, especially in distant frequency offsets, compared to their synthesizer counterparts.

The advantages of DRO-based solutions extend beyond reduced phase noise. The absence of digital circuitry noise adds spurious and harmonic purity to the list of benefits. While modern modems can compensate for phase noise at receivers, it is important to prioritize using this capability to overcome channel impairments rather than addressing shortcomings in PLL design.

Emphasizing the significance of phase noise management, we acknowledge that alongside thermal noise, it sets the baseline for channel capacity performance in satellite communication. Establishing a high-speed satellite link necessitates the design of low-noise and low-distortion circuits, with phase noise playing a substantial role in achieving this goal.

In summary, the following recommendations are proposed for optimizing satellite channel capacity:

• Low Phase Noise PLLs- Implementing low phase noise PLLs is pivotal to ensuring optimal signal quality in satellite communication systems.
• Use of Appropriate Clock References- Choosing suitable clock references contributes to the stability and precision of signal timing, minimizing phase noise.
• Proper Filtering- Employing effective filtering mechanisms aids in reducing unwanted noise and distortions in the communication signal.
• DRO Based PLLs with Analog Phase Detection- Leveraging DRO-based PLLs with analog phase detection offers advantages in terms of lower phase noise and improved signal purity.
• Utilize Modem Capabilities- Exploiting modem capabilities on the receiving side to compensate for phase noise degradation resulting from channel