Wenshu Zhang

Relay Selection from a Battery Energy Efficiency Perspective

Relay network is proposed as a means of improving the error performance and energy efficiency of the wireless networks. Inspired by the battery power efficiency (BPE) analysis in [1], relay selection from the battery energy efficiency perspective turns out to be an interesting topic. Under the general network setup which integrates typical transmission and reception modules, we adopt the realistic nonlinear battery model, extend the BPE results in [1] to relay network over Rayleigh fading channels, investigate the optimum and suboptimum energy allocation solutions for the relaying transmission, and finally establish the relay selection criterion from the battery energy efficiency point of view. Both the theoretical derivation and numerical results show that, subject to the same average bit error rate (BER) performance constraint, relaying does not necessarily increase the system energy efficiency, but is a possible alternative of the direct transmission depending on the relaying situation. Additionally, we prove that the two relaying protocols Decode and Forward (DF) and Amplify and Forward (AF) are equivalent for relay selection over Rayleigh fading channels at high SNR.

Communications-Inspired Sensing: A Case Study on Waveform Design

Information theory, and particularly the mutual information (MI), has provided fundamental guidance for communications research. In Bells 1993 paper, the MI was first applied to radar waveform design. Similar to its communications counterpart, the solution comes in a water-filling form. However, the practical meaning of MI in the sensing context remains unclear to date. Recently, Yang and Blums 2007 paper shows that under the white noise assumption, the optimum water-filling scheme simultaneously maximizes the MI and minimizes the estimation minimum mean square error (MMSE). Such an equivalence, however, does not hold when the target parameter statistics are not perfectly known as shown in Yang and Blums subsequent work. To further the understanding of the practical meaning of MI and to establish a connection between the MI and commonly adopted MSE measures for sensing, this paper takes a fresh look at the target estimation problem. We consider the general colored noise, incorporate the normalized MSE (NMSE), and develop joint robust designs for both the transmitter (waveforms) and the receiver (estimator) under various target and noise uncertainty models. Our results show that i) the optimum waveform designs resulted from the MI, MMSE and NMSE criteria are all different and ii) compared to MMSE, the NMSE-based designs share more similarities with the MI-based ones, especially when the target and noise statistics are not perfectly known.

Relay selection from a battery energy efficiency perspective

Relay network is proposed as a means of improving the error performance and energy efficiency of the wireless networks. Inspired by the battery power efficiency (BPE) analysis in [1], relay selection from the battery energy efficiency perspective turns out to be an interesting topic. Under the general network setup which integrates typical transmission and reception modules, we adopt the realistic nonlinear battery model, extend the BPE results in [1] to relay network over Rayleigh fading channels, investigate the optimum and suboptimum energy allocation solutions for the relaying transmission, and finally establish the relay selection criterion from the battery energy efficiency point of view. Both the theoretical derivation and numerical results show that, subject to the same average bit error rate (BER) performance constraint, relaying does not necessarily increase the system energy efficiency, but is a possible alternative of the direct transmission depending on the relaying situation. Additionally, we prove that the two relaying protocols Decode and Forward (DF) and Amplify and Forward (AF) are equivalent for relay selection over Rayleigh fading channels at high SNR.

Performance Investigation of Distributed STBC-OFDM System with Multiple Carrier Frequency Offsets

In the distributed space time block coded (DSTBC) orthogonal frequency division multiplexing (OFDM) system (DSTBC-OFDM), since the transmit antennas belong to different nodes that are distributed, there may exist multiple carrier frequency offsets (CFOs) to the transmitters at the receiver. Several kinds of equalization techniques, which intend to mitigate the intercarrier interference (ICI) when detecting symbols, are compared in terms of the BER performance. And an equalization method based on iterative ICI cancellation is proposed. Simulation results show that when the difference of normalized CFOs (with respect to the subcarrier spacing) between distributed transmitters is not more than 0.2, the proposed iterative ICI cancellation method could combat ICI effectively at very low computational cost. However, in case of large difference of normalized CFOs, i.e., 0.4, the frequency offsets could cancel the space diversity gain of distributed STBC totally even when ideal ICI cancellation is assumed, and the performance is close to that of OFDM system using single transmit antenna without space time block coding

SC-FDMA for uplink smart meter transmission over low voltage power lines

Recently data communications over smart grid between the smart meters and the central modem attract a lot of interests. Extensive works have been done based on Orthogonal Frequency Division Multiple Access (OFDMA) system on one of the possible solutions for smart grid, i.e., low voltage power lines. Although OFDMA has been widely adopted in many wired and wireless communication systems, its multicarrier nature results in severely high peak-to-average power ratio (PAPR), which is undesirable for low-cost terminal equipments. On the other hand, Single Carrier-Frequency Division Multiple Access (SC-FDMA), a promising alternative to OFDMA, can greatly reduce PAPR while achieving similar performance and complexity. In this paper, SC-FDMA is for the first time introduced to PLC. We compare it with OFDMA, and study its potential for uplink smart meter transmission on power lines. Finally, simulation results also corroborate the advantages of SC-FDMA to OFDMA.

OFDM-IDMA with User Grouping

A generalized version of orthogonal frequency division multiplexing interleave division multiple access (OFDM-IDMA) referred to as grouped OFDM-IDMA (G-OFDM-IDMA) is introduced in this paper. By dividing users into groups and transmitting each groups data only on some (as opposed to all) subcarriers, G-OFDM-IDMA can have much lower decoding complexity compared with conventional OFDM-IDMA while preserving the bit error probability (BEP) performance and the bandwidth efficiency. The user grouping problem is formulated into an integer linear programming problem whose suboptimal solution is proposed and compared with the lower bound. The optimization complexity issue is also addressed. Simulations are carried out to test the performance of G-OFDM-IDMA under various system configurations. It is observed that up to 80% complexity could be saved when the conventional OFDM-IDMA is substituted by G-OFDM-IDMA configured according to the suboptimal grouping solution.

Optimizing the battery energy efficiency in wireless sensor networks

In wireless sensor networks (WSN), battery energy efficiency is a crucial issue since the sensor nodes in WSNs are generally driven by nonrenewable batteries. In recent years, there has been an increasing trend of incorporating special battery characteristics into network protocol design and optimization. This paper provides the overview of battery energy consumption optimization for two specific communication tasks. To do that, we introduce a realistic node model incorporating circuit power consumptions and battery nonlinearity. Based on this model, one can choose a more battery-energy-efficient modulation scheme for the entire network. By a case study, we show that the modulation selection depends on the internode distance. Then, for specific communication links within the network, one can either use single-hop direct link communication or multi-hop communication by utilizing intermediate nodes for information relaying. Our analyses show that from the battery energy efficiency perspective, the choice of relaying depends on the transmission distance and the relay node position.

On the Optimality of Timing with Dirty Templates

Rapid and accurate timing synchronization is the first and foremost task in ultra-wideband (UWB) systems. The timing with dirty templates (TDT) algorithm introduced in [10] is a promising method with low complexity and relaxed operation conditions in the presence of unknown time hopping and multipath channel. Its optimality, however, remains unexplored. In this paper, we develop the maximum-likelihood (ML) timing algorithm and obtain its optimum training sequence. We show that the optimum training sequence of the ML timing estimator coincides with that of the TDT algorithm. In addition, we prove that, using this training sequence, the ML algorithm can be simplified, and that the simplified ML (SML) is equivalent to TDT.

On the Optimality of Data-Aided Coarse Timing With Dirty Templates

Rapid and accurate timing synchronization is a critical task in ultrawideband (UWB) systems. Yang and Giannakis introduced a promising algorithm, i.e., data-aided timing with dirty templates (TDT), which is known for low complexity and relaxed operation conditions in the presence of unknown time hopping and multipath channels. In this paper, we will explore the optimality of TDT. We develop a maximum-likelihood (ML) timing algorithm and obtain its optimum training sequence. It is shown that the optimum training sequence of the ML timing estimator coincides with that of the TDT algorithm. In addition, we prove that the ML algorithm can be simplified using this training sequence and that the simplified ML (SML) is equivalent to TDT.

Communication-inspired sensing

Information theory, and particularly the mutual information (MI) has provided fundamental guidance for communications research. In, the MI was first applied to radar waveform design. However, the practical meaning of MI in the sensing context remains unclear. Recently, shows that under the white noise assumption, the water-filling scheme simultaneously maximizes the MI and minimizes the minimum MSE (MMSE). Such an equivalence disappears when the target parameter statistics are not perfectly known. To further the understanding of the practical meaning of MI and to establish a connection between MI and commonly adopted MSE measures for sensing, this paper takes a fresh look at the target estimation problem, by considering the general colored noise, incorporating the normalized MSE (NMSE), and establishing joint robust designs for both the transmitter (waveforms) and the receiver (estimator) under various target and noise uncertainty levels. Our results show that: i) the optimum waveform designs resulted from the MI, MMSE and NMSE criteria are all different; and ii) compared to MMSE, the NMSE-based designs share more similarities with the MI-based ones, especially when the target and noise statistics are not perfectly known.