Kyle Jung-Lin Pan

Peak Power Characteristics of Single Carrier FDMA MIMO Precoding System

A salient advantage of single carrier frequency division multiple access (SC-FDMA) is low peak-to-average power ratio (PAPR) which is lower than that of OFDMA. Precoding using transmit beamforming (TxBF) is a MIMO spatial multiplexing method that increases the data throughput significantly. However, when applied to SC-FDMA, it increases the PAPR. In this paper, we describe how we can apply TxBF to an SC-FDMA system and show its effect on PAPR We then consider the effects of precoder averaging across subcarriers and quantization, typically used to reduce feedback overhead, on the PAPR Comparisons are made with single antenna, non-precoded spatial multiplexing (SM) and space-frequency block coding (SFBC) systems. Lastly, we show that a modest amount of amplitude clipping can reduce PAPR to an acceptable level with virtually no harmful effects on performance or spectral growth.

Theory and Design of a Quadrature Analog-to-Information Converter for Energy-Efficient Wideband Spectrum Sensing

A flexible bandwidth, blind sub-Nyquist sampling approach referred to as the quadrature analog-to-information converter (QAIC) is proposed. The QAIC relaxes the analog front-end bandwidth requirements at the cost of some added complexity compared to the modulated wideband converter (MWC) for an overall improvement in sensitivity and energy consumption. An approach for detailed frequency domain analysis of the proposed system with linear impairments is developed. A process for selecting QAIC parameter values is illustrated through examples. The benefits of the QAIC are highlighted with cognitive radio use cases where a wide range of spectrum is observed at various resolution bandwidth settings. We demonstrate that the energy consumption of the QAIC is potentially two orders of magnitude lower than the swept-tuned spectrum analyzer (STSA) and an order of magnitude lower than the MWC. We also demonstrate that the QAIC significantly improves upon the sensitivity performance delivered by the MWC.

Zero-Forcing Beamforming Codebook Design for MU-MIMO OFDM Systems

Zero-forcing (ZF) beamforming, an efficient technique for multiuser MIMO systems, requires perfect channel state information to be available at the base station. This is achieved by quantizing the channel and feeding back the information with a limited number of bits. A challenge of this method is the large downlink signaling overhead, which is due to the large size of the codebook that can be used at the base station for ZF beamforming. In this paper, we first analyze this problem and then present a technique designing codebooks with reduced size and minimal performance degradation. We also define the associated procedures required for the system implementation. Simulation results show that the size of the eNodeB codebook can be substantially reduced with only a small (5%) penalty in performance.

Enhanced data detection employing compressed sensing In wireless communications

A framework and algorithm employing compressed sensing (CS) for orthogonal frequency division multiplexing (OFDM) systems is proposed. A compressive iterative interference cancellation for OFDM signal is presented. Prior knowledge of communication system is exploited to enhance data detection performance. Simulation results indicate that such an advanced data detection and receiver yields significant gains in bit error rate (BER) at low sampling rates.

An Enhanced Compressed Sensing-Based Interference-Resistant Receiver for LTE Systems

This paper proposes a novel interference-resistant receiver for wideband long-term evolution (LTE) system which employs orthogonal frequency division multiple access (OFDMA) for the downlink. In case the received spectrum is underutilized, compressed sensing (CS) enables us to operate at a sub-Nyquist sampling rate for lower device cost, higher data transmission rate and faster spectrum sensing speed. To improve the receiver performance under a mutually interfering and noisy environments, a resource block (RB)-detection based iterative interference cancellation algorithm for LTE OFDMA signals is presented. Active RBs are blindly detected in order to improve performance of the proposed CS-based receiver. Specifically, the RBs of active users are estimated by minimum mean square error (MMSE) and those of interference users are estimated via ℓ1- norm minimization in a semi-blind manner, both in compressive signal domain. By canceling the interferences directly from compressive measurements iteratively, the proposed algorithm improves the estimates of both the desired and interfering signals. Simulation results indicate that such an interference-resistant receiver yields significant gains in bit error rate at low sampling rates.