In-patient monitoring of blood pressure, heart rate, and pulse oximetry require very sensitive analog front ends (AFE's) designed from a system perspective. Analog techniques to lower power consumption of the AFE's while maintaining SNR will be discussed. Challenges for power management in wearables and digital processing needed for next generation patient monitoring will be discussed from the context of improving patient comfort, without sacrificing performance. This paper describes some of the critical parameters and design approaches for state-of-the-art monitoring systems focusing on signal acquisition and intelligent signal processing.

Narrowband interference (NBI) is a significant impairment for multi-carrier modulation systems in both wireless and wireline channels. NBI may be generated by switching power supplies and legacy communication systems, and in many instances may be tonal in nature [1]. Recently, a novel method for mitigating the effect of NBI was proposed in [2] which works on minimizing the NBI spectral leakage by downconvering, nulling, and upconverting the received signal. In this paper we address the key question of how the algorithm performs as the number of interferers scales. We perform a distortion analysis on the received signal and obtain the following results under the assumption of an idealized analog front end: a) the distortion scales linearly with the number of interferers b) the distortion is independent of interferer frequency and amplitude. We also carry out a signal-to-interference noise ratio (S!NR) analysis of the proposed algorithm and show a good match between theory and simulation results.

Non-Gaussian noise/interference severely limits communication performance of narrowband powerline communication (PLC) systems. Such noise/interference is dominated by periodic impulsive noise whose statistics varies with the AC cycle. The periodic impulsive noise statistics deviate significantly from that of additive white Gaussian noise, thereby causing dramatic performance degradation in conventional narrowband PLC systems. In this paper, we propose a robust transmission scheme and corresponding receiver methods to combat periodic impulsive noise in OFDM-based narrowband PLC. Towards that end, we propose (1) a time-frequency modulation diversity scheme at the transmitter and a diversity demodulator at the receiver to improve communication reliability without decreasing data rates; and (2) a semi-online algorithm that exploits the sparsity of the noise in the frequency domain to estimate the noise power spectrum for reliable decoding at the diversity demodulator. In the simulations, compared with a narrowband PLC system using Reed-Solomon and convolutional coding, whole-packet interleaving and DBPSK/BPSK modulation, our proposed transceiver methods achieve up to 8 dB gains in Eb/N0with convolutional coding and a smaller-sized interleaver/deinterleaver.

Non-Gaussian noise/interference severely limits communication performance of narrowband powerline communication (PLC) systems. Such noise/interference is dominated by periodic impulsive noise whose statistics varies with the AC cycle. The periodic impulsive noise statistics deviates significantly from that of additive white Gaussian noise, thereby causing dramatic performance degradation in conventional narrowband PLC systems. In this paper, we propose a robust transmission scheme and corresponding receiver methods to combat periodic impulsive noise in OFDM-based narrowband PLC. Towards that end, we propose (1) a time-frequency modulation diversity scheme at the transmitter and a diversity demodulator at the receiver to improve communication reliability without decreasing data rates; and (2) a semi-online algorithm that exploits the sparsity of the noise in the frequency domain to estimate the noise power spectrum for reliable decoding at the diversity demodulator. In the simulations, compared with a narrowband PLC system using Reed-Solomon and convolutional coding, whole-packet interleaving and DBPSK/BPSK modulation, our proposed transceiver methods achieve up to 8 dB gains in Eb/N0with convolutional coding and a smaller-sized interleaver/deinterleaver.

A Smart Grid intelligently monitors and controls energy flows in an electric grid. Having up-to-date distributed readings of grid conditions helps utilities efficiently scale generation up or down to meet demand. Narrowband powerline communication (PLC) systems can provide these up-to-date readings from subscribers to the local utility over existing power lines. A key challenge in PLC systems is overcoming additive non-Gaussian noise. In this paper, we propose to use a cyclostationary model for the dominant component of additive non-Gaussian noise. The key contributions are (1) fitting measured data from outdoor narrowband PLC system field trials to a cyclostationary model, and (2) developing a cyclostationary noise generation model that fits measured data. We found that the period in the cyclostationary model matched half of the period of the main powerline frequency, which is consistent with previous work in indoor PLC additive noise modeling.

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) is a spectrally efficient modulation scheme which combines the advantages of having multiple antennas at both transmitter and receiver and the ease of equalization afforded by OFDM. When channel state information (CSI) is available at the transmitter a simple technique called linear preceding can be used to improve the error rate performance in both beamforming and spatial multiplexing systems. However, in frequency division duplex (FDD) systems there is typically a lack of channel reciprocity and precoder matrices have to be designed at the receiver and sent back through a limited feedback channel with the help of codebooks. By constraining the precoders to lie on the Grassmann manifold optimal codebook design for the single carrier MIMO channel has been well studied. If these codebooks are used in a MIMO-OFDM system and precoder information for all subcarriers is sent back, the amount of feedback can get prohibitively large. In this paper we use simple geometrical ideas on the Grassmann manifold to further reduce this feedback requirement. The performance of these algorithms are shown to provide improvement over existing schemes.