Vladislav Zaimov is an experienced Telecommunications specialist with expertise in enterprise telecommunications and the risk management of vulnerable networks. In this interview, we’ll be discussing his team’s development of three new design techniques for wireless transmitters. We’ll dive into how these techniques improve power efficiency and data rates, details on the CORDIC-less polar transmitter architecture, and the potential applications for such innovations.
Can you explain what inspired your team to develop these three new design techniques for wireless transmitters?
The rapid growth of the Internet of Things (IoT) and the increasing demand for interconnected devices have necessitated more efficient and faster wireless communication systems. Traditional approaches using CORDIC for polar transmitters present challenges in power consumption and linearity, limiting the system’s efficiency. Our goal was to address these issues by developing techniques that could enhance power efficiency and data rates without compromising each other.
How does the proposed CORDIC-less polar transmitter architecture function differently from traditional transmitters?
Traditional transmitters rely on CORDIC to generate multi-bit amplitude and phase signals, leading to higher power consumption and linearity issues. Our CORDIC-less architecture employs Delta-Sigma Modulators (DSMs) to re-encode the input data into 3-level signals. This approach simplifies the modulation process by using a look-up table (LUT) with only nine distinct amplitude-phase combinations, avoiding the complexity and power-hunger of CORDIC.
What are the main challenges associated with using CORDIC in wireless transmitters?
CORDIC is inherently power-hungry and produces multi-bit amplitude and phase signals that require precise modulators. These modulators often suffer from nonlinearity due to manufacturing defects, which limit the transmitter’s data rates. Balancing power efficiency and data rate becomes challenging because improving one aspect often compromises the other.
Could you elaborate on the advantages of your CORDIC-less approach over the traditional CORDIC-based transmitters?
Our CORDIC-less approach reduces power consumption significantly by eliminating the power-hungry CORDIC circuit. Additionally, it simplifies the modulation process, enabling higher data rates and improved linearity. By reducing the bit count for amplitude and phase, we can use more straightforward and efficient modulation techniques, which contribute to the overall system’s enhanced performance.
What role do Delta-Sigma Modulators (DSMs) play in your new transmitter design?
Delta-Sigma Modulators are crucial in our design as they re-encode the input data into 3-level signals. This encoding enables us to avoid the direct calculation of polar coordinates, which is typically done by the CORDIC circuit. The 3-level signals generated by DSMs provide an efficient and straightforward way to determine amplitude and phase using a look-up table.
How do DSMs help in re-encoding the input data in your first proposed technique?
In our first technique, DSMs convert the input x and y signals into 3-level outputs, leading to only nine distinct amplitude-phase combinations. Instead of directly calculating the polar coordinates, we use these 3-level signals to determine the necessary amplitude and phase through a simple nine-state look-up table. This process reduces the complexity and power consumption associated with traditional methods.
Why did you decide to use 3-level signals generated by DSMs instead of multi-bit amplitude and phase signals?
Using 3-level signals simplifies the modulation process and addresses the linearity issues associated with multi-bit signals. Multi-bit amplitude and phase signals require modulators that must be precisely matched, but mismatches can occur during production, leading to linearity problems. Our 3-level approach mitigates these issues, offering a more efficient and reliable solution.
What is a nine-state look-up table (LUT) and how does it work in your design?
A nine-state look-up table (LUT) is a simple method of determining amplitude and phase from the 3-level signals generated by DSMs. Because the DSMs produce only nine distinct amplitude-phase combinations, we can use this LUT to quickly and efficiently find the required amplitude and phase for transmission without the need for complex calculations.
Can you explain in detail how the first technique reduces power consumption by avoiding CORDIC?
By re-encoding input data through DSMs into 3-level signals, we eliminate the need for CORDIC, which requires significant power to operate. The use of a nine-state LUT further simplifies the modulation process, reducing computational complexity and, consequently, power consumption. This streamlined approach allows us to achieve the desired modulation without the energy-intensive steps associated with traditional methods.
How does your approach facilitate the use of linear amplitude and phase modulation techniques?
Our approach utilizes DSMs to generate 3-level signals and uses a nine-state LUT to determine amplitude and phase, reducing the bit count for these signals. This simplification enables the use of linear amplitude and phase modulation techniques more effectively, as it addresses the linearity issues seen with multi-bit modulation schemes.
In your second proposed technique, why is the 2-bit amplitude signal quantized to 1-bit?
The 2-bit amplitude signal is further quantized to 1-bit to prevent increased in-band noise and ensure complete transmitter output linearity. By toggling the output between zero and peak amplitudes without intermediate states, we achieve a fully linear amplitude modulation, which contributes to the overall system’s efficiency and performance.
How does quantizing the amplitude signal to 1-bit prevent increased in-band noise?
Quantizing the amplitude signal to 1-bit ensures that the transmitter’s output toggles only between zero and peak amplitudes, eliminating intermediate states. This method helps in maintaining linearity, preventing the introduction of noise within the signal band, thus contributing to clearer and more efficient data transmission.
What improvements in transmitter output linearity did you observe with the 1-bit amplitude control?
With the 1-bit amplitude control, we’ve observed a significant improvement in transmitter output linearity. This technique avoids the intermediate states that typically introduce nonlinearity, ensuring a more precise and accurate modulation of the transmitted signal, ultimately enhancing overall performance.
How does the third proposed technique generate the eight required phases using 3-bit phase control code?
In the third technique, we generate eight phases separated by 45° by leveraging the rising and falling edges of a square wave running at four times the carrier frequency. By multiplexing these different edges, we can form the required output phase without the need for complex interpolation from 0° to 360°, ensuring efficient phase modulation.
Can you clarify how multiplexing the different edges of the square wave forms the output phase?
Multiplexing different edges of the square wave involves using both the rising and falling transitions of the wave, which occur at precise intervals. By selecting and combining these transitions appropriately, we can create the desired phase shifts at 45° increments, achieving the necessary phase modulation with minimal complexity.
Why are 45° separated phases adequate for the desired phase modulation?
Utilizing 45° separated phases offers a balanced compromise, providing sufficient granularity for accurate phase modulation while remaining relatively simple to implement. This separation helps efficiently achieve the desired modulation states, ensuring the transmitter can perform effectively without requiring overly intricate phase control mechanisms.
What specific advantages do your proposed techniques offer in terms of transmitter linearity?
Our proposed techniques offer enhanced linearity by eliminating the CORDIC circuit and using simpler modulation methods. The DSM-based 3-level signals and the LUT-based approach for amplitude and phase determination ensure more precise modulation. Additionally, 1-bit amplitude control and 45° separated phases prevent non-linearities, providing a highly linear modulation system.
How does your new transmitter technology impact data rates compared to the state-of-the-art designs?
Our CORDIC-less polar transmitter architecture allows for broader bandwidths, enabling higher data rates. By improving power efficiency and reducing linearity issues, our design supports faster data transmission without sacrificing performance, which positions it favorably compared to current state-of-the-art designs.
What was the rationale for using a 65nm CMOS process to implement your digital transmitter?
Utilizing a 65nm CMOS process balances performance, power efficiency, and integration density. This technology is mature and widely adopted, providing a reliable platform for implementing our innovative transmitter design while ensuring cost-effectiveness and scalability for potential commercial applications.
What were the key findings when you compared your new design to other state-of-the-art wireless transmitter designs?
Our new design demonstrated superior power efficiency and data rates without the typical trade-offs present in conventional transmitters. By eliminating the CORDIC circuit and using our innovative design techniques, we achieved top-tier performance in both efficiency and speed, positioning our transmitter as a leading solution in the field.
How does your new transmitter design align with the needs of the Internet of Things (IoT)?
Our design is highly power-efficient, which is crucial for battery-operated IoT devices. Additionally, the enhanced data rates support the increased data demands of interconnected devices, ensuring more reliable and faster communication essential for IoT applications. This alignment makes our transmitter a prime candidate for IoT integration.
What potential applications do you envision benefiting most from this power-efficient and speedier transmitter technology?
Applications that require efficient and rapid wireless communication, such as smart homes, industrial automation, healthcare monitoring, and automotive systems, will benefit greatly. Our design’s efficiency and speed also make it ideal for next-generation AI-driven applications that rely on quick data processing and reliable connectivity.
How do your design techniques support the integration of AI into daily life via IoT?
By providing a transmitter that efficiently handles high data rates and consumes less power, our design supports the seamless integration of AI in IoT environments. This allows for real-time data collection, processing, and decision-making, which are essential for smart applications and services in daily life.
Are there any foreseeable challenges in scaling up this technology for commercial deployment?
While our design shows promise, scalability challenges could include ensuring consistent performance across mass-produced units and maintaining cost-effectiveness. Addressing regulatory requirements and standardizing the technology for broader adoption will also be crucial. However, with continued research and development, we are optimistic about overcoming these challenges for successful commercial deployment.
