Ramesh Annavajjala

Achieving near-exponential diversity on uncoded low-dimensional MIMO, multi-user and multi-carrier systems without transmitter CSI

It is well-known that for single-input and singleoutput (SISO) narrow-band transmission on frequency-flat fading channels, uncoded communication with only receiver channel state information (Rx-CSI) leads to extremely poor reliability performance whereas transmitter CSI (Tx-CSI) allows us approach the reliability of an additive white Gaussian noise (AWGN) channel via power control. In this paper, we propose a novel approach to achieve reliability close to the AWGN channel for uncoded transmissions on SISO frequency-flat Rayleigh fading channels without Tx-CSI. Our approach employs pseudo-random phase precoding (PRPP) of modulation symbols prior to temporal multiplexing, and joint-detection at the receiver that has polynomial complexity in the precoder size. With a precoder size of 400 binary symbols, we demonstrate that the proposed system achieves performance within 0.1 dB of the AWGN channel at a bit error rate of 10−5, and is also robust to fading correlation and channel estimation errors. Furthermore, we present extensions to multiple-user multiple-input and multiple-output (MU-MIMO) systems and wideband transmission schemes such as orthogonal frequency-division multiplexing (OFDM) and single-carrier frequency-domain multiple access (SC-FDMA) systems. We show, through extensive simulations, that i) with an 8-by-8 MIMO system per-stream AWGN channel reliability is achieved with 8 spatial streams and 50 channel uses, ii) for a 5 user multiple-access channel with one antenna per user and 5 antennas at the receiver, 80 channel uses eliminates fading and interference completely while simultaneously providing a power gain of approximately 6.9 dB, and iii) for OFDM and SC-FDMA systems with single antenna at the transmitter and two antennas at the receiver, within 0.1 and 0.3 dB of the matched-filter bound performance is achieved with a precoder size of 96 and 400 symbols, respectively.

Multiantenna Analog Network Coding for Multihop Wireless Networks

This paper proposes a two-phase minimum mean-square-error bidirectionalnamplify-and forward (MMSE-BAF) relaying protocol to allow two sourcesnexchange independent messages via a relay node equipped with multiple antennas.nMMSE-BAF performs a joint linear MMSE filtering of the received signal afternthe multiple access phase before amplifying and forwarding the filtered signalnusing a single transmit antenna, possibly through a specific antenna selectionnprocedure, during the broadcast phase. The proposed protocol extends upon thenso-called analog network coding schemes in the literature in that it inherentlynexploits the multiple antennas at the relay station to reduce the noise enhancementntypical of an AF protocol, and can also compensate for link imbalances betweennthe relay and the sources and is agnostic to sources modulation and codingnschemes. We derive the instantaneous signal-to-noise ratio expressions for thenreceived signal by the sources in the downlink and provide extensive link-levelnsimulations for the MMSE-BAF protocol subject to both frequency flat andnselective fading. Furthermore, we pinpoint the modifications to be incorporatedninto the IEEE 802.16e orthogonal-frequency-division multiple access (OFDMA)ncellular standard (mobile WiMax) to enable support of multiantenna bidirectionalncommunications and show that MMSE-BAF is a viable solution within thatnframework.

Physical Layer Data Fusion Via Distributed Co-Phasing With General Signal Constellations

This paper studies a pilot-assisted physical layer data fusion technique known as Distributed Co-Phasing (DCP). In this two-phase scheme, the sensors first estimate the channel to the fusion center (FC) using pilots sent by the latter; and then they simultaneously transmit their common data by pre-rotating them by the estimated channel phase, thereby achieving physical layer data fusion. First, by analyzing the symmetric mutual information of the system, it is shown that the use of higher order constellations (HOC) can improve the throughput of DCP compared to the binary signaling considered heretofore. Using an HOC in the DCP setting requires the estimation of the composite DCP channel at the FC for data decoding. To this end, two blind algorithms are proposed: (1) power method, and (2) modified K-means algorithm. The latter algorithm is shown to be computationally efficient and converges significantly faster than the conventional K-means algorithm. Analytical expressions for the probability of error are derived, and it is found that even at moderate to low SNRs, the modified K-means algorithm achieves a probability of error comparable to that achievable with a perfect channel estimate at the FC, while requiring no pilot symbols to be transmitted from the sensor nodes. Also, the problem of signal corruption due to imperfect DCP is investigated, and constellation shaping to minimize the probability of signal corruption is proposed and analyzed. The analysis is validated, and the promising performance of DCP for energy-efficient physical layer data fusion is illustrated, using Monte Carlo simulations.

Communication over non-Gaussian channels - Part I: Mutual information and optimum signal detection

Gaussian distribution as a source of additive noise is a wellknown modeling assumption, which lead to important and insightful results on the channel capacity, detection reliability, and estimation accuracy. It is also well-recognized that in many practical settings the Gaussian distribution may not be adequate to model the underlying noise phenomenon, and various non-Gaussian noise models are employed for the design and performance analysis of communication systems. However, existing non-Gaussian noise models can be cumbersome to use as it is difficult to prescribe the model parameters and estimate them prior to signal detection, and hard to perform analysis and optimization of communication systems with realistic channel estimation. With the above challenges in mind, in the first part of our work, we introduce a model for the additive non-Gaussian channel (ANGC) with a focus on simplicity, robustness, and ease of analytical tractability. Specifically, we consider a compound noise distribution that is composed of a conditionally additive white Gaussian noise (AWGN) and a Gamma distributed noise variance. This model reduces to the traditional AWGN model when the shape parameter of the Gamma distribution tends to infinity, and the detection and estimation performances on ANGC can easily be reduced to their counterparts on the AWGN channel. With this model, we first present the average mutual information when multiple antennas are employed at the transmitter and the receiver. Next, we derive closed-form expressions for the average probability of error for binary and higher-order modulations when the receiver has perfect channel state information. In the second part of our work, we consider noise variance estimation, pilot-assisted channel estimation (PACE), signal detection with PACE, and coded sequence detection with a mismatched decoding metric.

Level crossing rates and average outage durations of SINR with multiple co-channel interferers

Knowledge of the level crossing rates (LCR) and average outage durations (AOD) of the received signal-to-interference-plus-noise ratio (SINR) is very useful in designing and analyzing the communication system performance in a cellular environment with co-channel interference (CCI). In this paper, we study the analytical LCR and the AOD of the received SINR on Rayleigh fading channels with CCI. A closed-form expression for the LCR and the AOD is obtained for the general case of multiple co-channel interferers, traveling at different speeds, with unequal powers and with additive white Gaussian noise. We also specialize the derived results to the case of both interference-limited and noise-limited scenarios.

Design and analysis of distributed co-phasing with arbitrary constellations

In this paper, we design and analyze pilot-assisted Distributed Co-Phasing (DCP) schemes for information fusion in a wireless sensor network. First, using a cutoff rate analysis, we show that higher order constellations significantly improve the throughput performance of DCP in comparison with the binary constellation considered in past work. However, using a higher order constellation in the DCP setting requires estimation of the composite channel from the sensors at the Fusion Center (FC), which is not available in current DCP schemes. We propose two blind algorithms for channel estimation, namely, a power method and a modified K-means algorithm. In particular, the latter is computationally efficient and converges significantly faster and more accurately than the conventional K-means algorithm. We derive closed-form expressions for the probability of symbol error and study the performance of DCP both analytically and through simulations. Our simulation results show that even at moderate to low SNRs, the modified K-means algorithm achieves a probability of error comparable to that achievable with a perfect channel estimate at the FC. The proposed DCP and blind channel estimation schemes are thus a promising technique for energy-efficient data fusion in wireless sensor networks.

Pilot-Assisted Distributed Co-Phasing for Wireless Sensor Networks

This paper addresses the design and analysis of practical distributed beamforming techniques for the uplink communication over a wireless sensor network. Since the conventional frequency-division duplexing techniques require a large feedback overhead, we focus on a time-division duplexing approach, and exploit the channel reciprocity to reduce the channel feedback requirement. We consider periodic broadcast of known pilot symbols by the fusion center, and maximum likelihood estimation of the channel phase by the sensor nodes for the subsequent uplink co-phasing transmission. For simplicity, we study binary signaling over frequency-flat fading channels, and quantify the system performance such as the expected gains in the received signal-to-noise ratio (SNR) and the average probability of error at the fusion center, as a function of the number of sensor nodes and the pilot overhead. Our results show that a modest amount of accumulated pilot SNR is sufficient to realize a large fraction of the maximum possible beamforming gain.

Wireless Cooperative Networks

1 Engineering Department in Ferrara (ENDIF), University of Ferrara, 44100 Ferrara, Italy 2Department of Electronics, University of Kent, Canterbury, Kent CT2 7NT, UK 3Department of Radio Communication Engineering, School of Electronics and Information, Kyung Hee University, Gueonggi-Do 449-701, South Korea 4Mitsubishi Electric Research Laboratories, 201 Broadway, Cambridge, MA 02139, USA 5Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

Communication over non-Gaussian channels - Part II: Channel estimation, mismatched receivers, and error performance with coding

Limited wireless spectrum coupled with the need to support co-existence mechanisms call for robust receivers and improved interference management. With a spectrum sharing operating mode, it is hard to model dynamic interference conditions in wireless networks. In the first part of this work, we have introduced an additive non-Gaussian channel (ANGC) model that captures a variety of interference sources, and presented average mutual information and average probability of error expressions when the receiver has perfect channel estimates and no knowledge of the noise statistics. The primary goal of introducing this model is to compactly represent a wide range of non-Gaussian noise sources in a robust and simple manner. As a continuation of that work, in this paper, we consider the problem of noise variance estimation, signal detection with pilot-assisted channel estimation (PACE), and coded sequence detection with a mismatched decoding metric. We derive the joint maximum-likelihood estimates of the Gaussian noise variance and the non-Gaussian parameter, and expressions for the outage probability and the average bit error probability for uncoded binary signaling. We also derive expressions for the average pairwise error probability with coding and PACE on ANGC. Numerical and simulation results are presented to validate the analysis presented in this paper.

Non-coherent ToA estimation for UWB multipath channels using max-eigenvalue detection

Due to the fine delay resolution in ultra-wideband (UWB) wireless propagation channels, a large number of multipath components (MPC) can be resolved; and the first arriving MPC might not be the strongest one. This makes time-of-arrival (ToA) estimation, which essentially depends on determining the arrival time of the first MPC, highly challenging. In this paper, we consider non-coherent ToA estimation given a number of measurement trials, at moderate sampling rate and in the absence of knowledge of pulse shape. The proposed ToA estimation is based on detecting the presence of a signal in a moving time delay window, by using the largest eigenvalue of the sample covariance matrix of the signal in the window as the test statistic. We show that energy detection can be viewed as a special case of the eigenvalue detection. Max-eigenvalue detection (MED) generally has superior performance, due to the following reasons: 1) MED collects less noise, namely only the noise contained in the signal space, and 2) if multiple channel taps fall into the time window, the MED detector can collect energy from all of them. Simulation results confirm that MED outperforms the energy detection in IEEE 802.15.3a and 802.15.4a channels. Finally, the selection of the threshold of the MED is studied both by simulations and by random matrix theory.