Debashis Banerjee

A Power-Scalable Channel-Adaptive Wireless Receiver Based on Built-In Orthogonally Tunable LNA

Most of the traditional RF circuits are static or minimally tunable using some digital controllability. For example, high power, low power and shut down modes are available in some commercially available transceivers. If available, the tuning knobs affect different specifications in an interdependent manner, resulting in changing several specifications when only one needs to be tuned. This is not enough for power optimal operation of complete self-aware self-adaptive circuits and systems. Independent or orthogonal tunability of the important conflicting specifications using built-in tuning knobs allow optimal adaptation of the wire-less systems. In this paper we demonstrate the design and benefits of orthogonal tuning knobs using an inductorless LNA as a test vehicle. The design of an orthogonally tunable LNA is discussed that has a 14 dB Gain tuning range and 30 dB OIP3 tuning range as its power consumption goes down by 20×. Measurement results on this LNA validate the concept of orthogonal tunability. Use of this orthogonally tunable LNA within an adaptive wireless receiver framework shows power savings of 2× compared to a static system and an extra savings of 22% compared to a traditional nonorthogonal adaptive system.

Real-time use-aware adaptive MIMO RF receiver systems for energy efficiency under BER constraints

Modern MIMO RF transceiver systems are designed to operate reliably under diverse channel conditions leading to incorporation of significant performance margins in RF transceiver systems. In general, across dynamically varying channel conditions, the fidelity of the RF front end devices can be traded-off against power consumption without compromising system-level BER limits. In this work such a real-time performance vs. power consumption modulation of RF front-end devices in MIMO systems is demonstrated. Through a multi-dimensional optimization technique, power-optimal configuration of the frontend for varying channel conditions are created. Additionally multiple low-power operating modes for the MIMO system are proposed depending on the performance metric (data rate or energy-per-bit) that need to be optimized for different applications.

Self Learning Analog/Mixed-Signal/RF Systems: Dynamic Adaptation to Workload and Environmental Uncertainties

Real-time systems for wireless communication, digital signal processing and control experience a wide gamut of operating conditions (signal/channel noise, workload demand, perturbed process conditions). As device bandwidths expand, it becomes increasingly expensive, from a power consumption and reliability perspective, to operate such real-time systems for worst-case (static) performance requirements. In contrast, it is attractive to design algorithms, architectures and circuits that are power-performance tunable and can adapt dynamically, via self-learning techniques, to the requirements of system-level applications for extended battery usage and device lifetime. Such future systems will feed application level demands to the underlying algorithm-architecture-circuit design fabric through built-in sense-and-control infrastructure (hardware, software). The sense functions assess instantaneous application level demands (e.g. throughput, signal integrity) as well as the performances of the individual hardware components as determined by manufacturing process conditions. The control functions actuate algorithm-through-circuit level tuning knobs that continuously trade off performance vs. power of the individual software and hardware modules in such a way as to deliver the end-to-end desired application level Quality of Service (QoS), while minimizing energy/power consumption. Application to wireless communications systems, digital signal processing and control algorithms is discussed.

Real-Time Use-Aware Adaptive RF Transceiver Systems for Energy Efficiency Under BER Constraints

Modern radio front ends are required to operate over diverse channel conditions requiring the incorporation of significant performance overheads into their design. This results in significantly higher power consumption over most of the operational period since the worst case channels are not statistically prevalent. Adaptive systems solve this problem by adapting the performance and power consumption depending on channel conditions. In this paper, it is demonstrated that depending upon the throughput requirements of the system multiple low-power adaptation modes can be designed. These modes ensure either highest throughput operation or lowest energy-per-bit operation. The operation of these modes is demonstrated in simulation using multiple-input-multiple-output (MIMO) receiver and transmitter front ends. Subsequently, the concepts are demonstrated in hardware for both MIMO and single-input-single-output front ends.

Adaptive RF Front-end Design via Self-discovery: Using Real-time Data to Optimize Adaptation Control

It has been established in prior research that significant power can be saved by dynamically trading off the performance of individual RF modules for power consumption across changing channel conditions. It has also been shown that the control law that reconfigures the RF front end must take into account the process corners from which the RF devices are selected in order to trade off performance for power in an optimal manner (minimum energy/bit at prescribed data throughput). Design of such an optimal control law is virtually intractable due to the complexity of simulating the RF front end across all possible channel and device process conditions. Hence, existing control algorithms are based on a coarse sampling of the channel-process space, suffer from modeling inaccuracies and are inherently sub-optimal from a performance vs. power perspective. In contrast, in this paper, we propose a RF front end control methodology that is optimized during real-time operation, does not require upfront simulation across all channel process conditions and is not susceptible to simulation inaccuracies. This results in far more robust/optimal control as opposed to current practice. A simulated annealing (SA) based framework for process optimization is proposed along with the use of built-in sensors for monitoring of performance and power. Simulation results and hardware data are presented to show the feasibility of the proposed approach.

Self-Learning RF Receiver Systems: Process Aware Real-Time Adaptation to Channel Conditions for Low Power Operation

Prior research has established that dynamically trading-off the performance of the radio-frequency (RF) front-end for reduced power consumption across changing channel conditions, using a feedback control system that modulates circuit and algorithmic level “tuning knobs” in real-time based on received signal quality, leads to significant power savings. It is also known that the optimal power control strategy depends on the process conditions corresponding to the RF devices concerned. This leads to an explosion in the search space needed to find the best feedback control strategy, across all combinations of channel conditions and receiver process corners, making simulation driven optimal control law design impractical and computationally infeasible. Since this problem is largely intractable due to the above complexity of simulation, we propose a self-learning strategy for adaptive RF systems. In this approach, RF devices learn their own performance vs. power consumption vs. tuning knob relationships “on-the-fly” and formulate the most power-optimal control strategy for real-time adaptation of the RF system using neural-network based learning techniques during real-time operation. The methodology is demonstrated using SISO and MIMO RF receiver front-ends as test vehicles and is supported by hardware validation leading to 2.5X-3X power savings with minimal overhead.

Efficient system-level testing and adaptive tuning of MIMO-OFDM wireless transmitters

A low cost methodology for simultaneous testing and tuning of multiple chains of MIMO-OFDM wireless transmitter for system-level specifications is presented. Bandwidth-partitioned test stimuli enable the determination of the behavioral characteristics of the different chains of the RF transmitter using a one-time data acquisition. The determined behavioral characteristics of the transmitters are then correlated to system-level specifications in the simulation environment. Using the test setup, a power conscious system-level tuning approach for yield improvement is developed for tuning of parametric deviations. A yield improvement of 20% is obtained using the proposed methodology. Finally, an adaptive tuning approach is presented for those devices that face increased reliability risks/power-budget violations due to the excessive power consumption caused by post-manufacturing tuning. The tuning methodology achieves new performance metrics for these devices that attempt to maximize the conditions under which the device operates. Significant improvement in yield is obtained using the adaptive tuning methodology. Preliminary hardware validation of the proposed methodology using off the shelf components is performed.

DSP Driven Parallel EVM Testing of Embedded MIMO-OFDM RF Modules

In this paper, we present a low-cost methodology for parallel testing of MIMO-OFDM RF modules using optimized bandwidth-partitioned frequency domain stimulus applied from the embedded DSP module of the MIMO-OFDM system and a simple combination of sensors on the load board. A comprehensive set of specifications of multiple RF modules chains are computed simultaneously from the observed DUT response using a single data acquisition. This allows MIMO-RF chains to be tested efficiently with lower test cost and test time as compared to prior test techniques. Experimental results provided for a 2.4 GHz transmitter showcase the ability of the presented technique to compute the RF specifications accurately.

Low cost high frequency signal synthesis: Application to RF channel interference testing

The quality of a communication link is commonly indicated by signal to noise/interference ratio and affected by noise and interference variance. To ensure a power efficient adaptive OFDM systems performance, the system needs to be tested against various channel conditions. Conventional algorithms and experiments assume that the noise and interference density stays constant over the OFDM frequency band but in reality the communication link often populated with both white noise and interference that results an uneven impact on OFDM spectrum. To create such channel condition, an up-conversion is commonly used. However, due to the non-linearity of the mixer, the up-converted interference is always distorted. The proposed method uses a modified higher-than-Nyquist-rate RF signal generation algorithm to minimize the distortion of generated interference within a pre-defined output bandwidth. Both concept validation and experimental measurement have been conducted to prove the effect of proposed method.

Adaptive MIMO RF systems: Post-manufacture and real-time tuning for performance maximization and power minimization

MIMO RF systems are seeing widespread use due to their inherent ability to extend the range of wireless channel conditions under which data can be transmitted reliably while satisfying communication throughput requirements. However, as frequencies scale upwards and aggressive CMOS technologies are used to manufacture RF devices, semiconductor process variations will limit the range of operating conditions under which MIMO systems can operate reliably with low power usage. To resolve this, we propose post-manufacture testing and tuning algorithms for MIMO systems assembled from devices across diverse process corners. These algorithms allow such systems to operate across the widest range of channel conditions as possible while minimizing power consumption (performance maximization also maximizes manufacturing yield). To further save power consumption in the field, real-time tuning algorithms are proposed that dynamically trade off available performance slack in MIMO designs, across the relevant signal modulation and MIMO modes to save power consumption. With regard to post-manufacture tuning, it is seen that as much as 20% yield improvement is possible through use of the proposed tuning methodology. With regard to real-time tuning, it is seen that as much as 3X power savings is possible for specific wireless channel conditions. The results of various experiments on MIMO systems are discussed.