Diversity-Rate Trade-off for Fading Channels with Power Control

We consider a complex, additive, white Gaussian noise channel with flat fading. We study its diversity order vs transmission rate for some known power allocation schemes. The capacity region is divided into three regions. For one power allocation scheme, the diversity order is exponential throughout the capacity region. For selective channel inversion (SCI) scheme, the diversity order is exponential in low and high rate region but polynomial in mid rate region. For fast fading case we also provide a new upper bound on block error probability and a power allocation scheme that minimizes it. The diversity order behaviour of this scheme is same as for SCI but provides lower BER than the other policies.

Low complexity adaptation for channel shortening equalizers

Since the days of Digital Subscriber Links(DSL), Time Domain Equalizers(TEQ's) have been used to combat time dispersive channels in Multicarrier Systems. In this paper, we propose computationally inexpensive techniques to recompute TEQ weights in the presence of changes in the channel, especially over fast fading channels. The techniques use no extra information except the perturbation itself, and provide excellent approximations to the new TEQ weights. The proposed adaptation techniques are shown to perform admirably well for small changes in channels for OFDM systems.

Adaptive constellation rotation scheme for two-user fading MAC with quantized fade state feedback

With no Channel State Information (CSI) at the users, transmission over the two-user Gaussian Multiple Access Channel with fading and finite constellation at the input, will have high error rates due to multiple access interference (MAI). However, perfect CSI at the users is an unrealistic assumption in the wireless scenario, as it would involve extremely large feedback overheads. In this paper we propose a scheme which removes the adverse effect of MAI using only quantized knowledge of fade state at the transmitters such that the associated overhead is nominal. One of the users rotates its constellation relative to the other without varying the transmit power to adapt to the existing channel conditions, in order to meet certain predetermined minimum Euclidean distance requirement in the equivalent constellation at the destination. The optimal rotation scheme is described for the case when both the users use symmetric M-PSK constellations at the input, where M = 2(gimel), gimel being a positive integer. The strategy is illustrated by considering the example where both the users use QPSK signal sets at the input. The case when the users use PSK constellations of different sizes is also considered. It is shown that the proposed scheme has considerable better error performance compared to the conventional non-adaptive scheme, at the cost of a feedback overhead of just log log(2) (M-2/8 - M/4 + 2)] + 1 bits, for the M-PSK case.

An adaptive modulation scheme for two-user fading MAC with quantized fade state feedback

For transmission over the two-user Gaussian Multiple Access Channel with fading and finite constellation at the inputs, we propose a scheme which uses only quantized knowledge of fade state at users with the feedback overhead being nominal. One of the users rotates its constellation without varying the transmit power to adapt to the existing channel conditions, in order to meet certain pre-determined minimum Euclidean distance requirement in the equivalent constellation at the destination. The optimal modulation scheme has been described for the case when both the users use symmetric M-PSK constellations at the input, where M = 2λ, λ being a positive integer. The strategy has been illustrated by considering examples where both the users use QPSK signal set at the input. It is shown that the proposed scheme has considerable better error performance compared to the conventional non-adaptive scheme, at the cost of a feedback overhead of just [log2 (M2/8 - M/4 + 2)] + 1 bits, for the M-PSK case.

Achievable secrecy sum-rate in a fading MAC-WT with power control and without CSI of eavesdropper

We consider a two user fading Multiple Access Channel with a wire-tapper (MAC-WT) where the transmitter has the channel state information (CSI) to the intended receiver but not to the eavesdropper (eve). We provide an achievable secrecy sum-rate with optimal power control. We next provide a secrecy sum-rate with optimal power control and cooperative jamming (CJ). We then study an achievable secrecy sum rate by employing an ON/OFF power control scheme which is more easily computable. We also employ CJ over this power control scheme. Results show that CJ boosts the secrecy sum-rate significantly even if we do not know the CSI of the eve's channel. At high SNR, the secrecy sum-rate (with CJ) without CSI of the eve exceeds the secrecy sum-rate (without CJ) with full CSI of the eve.

Low complexity joint estimation of synchronization impairments in sparse channel for MIMO-OFDM system

Low complexity joint estimation of synchronization impairments and channel in a single-user MIMO-OFDM system is presented in this paper. Based on a system model that takes into account the effects of synchronization impairments such as carrier frequency offset, sampling frequency offset, and symbol timing error, and channel, a Maximum Likelihood (ML) algorithm for the joint estimation is proposed. To reduce the complexity of ML grid search, the number of received signal samples used for estimation need to be reduced. The conventional channel estimation techniques using Least-Squares (LS) or Maximum a posteriori (MAP) methods fail for the reduced sample under-determined system, which results in poor performance of the joint estimator. The proposed ML algorithm uses Compressed Sensing (CS) based channel estimation method in a sparse fading scenario, where the received samples used for estimation are less than that required for an LS or MAP based estimation. The performance of the estimation method is studied through numerical simulations, and it is observed that CS based joint estimator performs better than LS and MAP based joint estimator. (C) 2013 Elsevier GmbH. All rights reserved.

Joint Approximately Sparse Channel Estimation and Data Detection in OFDM Systems Using Sparse Bayesian Learning

It is well known that the impulse response of a wide-band wireless channel is approximately sparse, in the sense that it has a small number of significant components relative to the channel delay spread. In this paper, we consider the estimation of the unknown channel coefficients and its support in OFDM systems using a sparse Bayesian learning (SBL) framework for exact inference. In a quasi-static, block-fading scenario, we employ the SBL algorithm for channel estimation and propose a joint SBL (J-SBL) and a low-complexity recursive J-SBL algorithm for joint channel estimation and data detection. In a time-varying scenario, we use a first-order autoregressive model for the wireless channel and propose a novel, recursive, low-complexity Kalman filtering-based SBL (KSBL) algorithm for channel estimation. We generalize the KSBL algorithm to obtain the recursive joint KSBL algorithm that performs joint channel estimation and data detection. Our algorithms can efficiently recover a group of approximately sparse vectors even when the measurement matrix is partially unknown due to the presence of unknown data symbols. Moreover, the algorithms can fully exploit the correlation structure in the multiple measurements. Monte Carlo simulations illustrate the efficacy of the proposed techniques in terms of the mean-square error and bit error rate performance.

Novel Transmit Precoding Methods for Rayleigh Fading Multiuser TDD-MIMO Systems With CSIT and No CSIR

In this paper, we present novel precoding methods for multiuser Rayleigh fading multiple-input-multiple-output (MIMO) systems when channel state information (CSI) is available at the transmitter (CSIT) but not at the receiver (CSIR). Such a scenario is relevant, for example, in time-division duplex (TDD) MIMO communications, where, due to channel reciprocity, CSIT can be directly acquired by sending a training sequence from the receiver to the transmitter(s). We propose three transmit precoding schemes that convert the fading MIMO channel into a fixed-gain additive white Gaussian noise (AWGN) channel while satisfying an average power constraint. We also extend one of the precoding schemes to the multiuser Rayleigh fading multiple-access channel (MAC), broadcast channel (BC), and interference channel (IC). The proposed schemes convert the fading MIMO channel into fixed-gain parallel AWGN channels in all three cases. Hence, they achieve an infinite diversity order, which is in sharp contrast to schemes based on perfect CSIR and no CSIT, which, at best, achieve a finite diversity order. Further, we show that a polynomial diversity order is retained, even in the presence of channel estimation errors at the transmitter. Monte Carlo simulations illustrate the bit error rate (BER) performance obtainable from the proposed precoding scheme compared with existing transmit precoding schemes.

Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

The impulse response of wireless channels between the N-t transmit and N-r receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., NtNt the channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wireless channels are also group approximately cluster-sparse (gac-sparse), i.e., every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this paper, we cast the problem of estimating the ga-sparse and gac-sparse block-fading and time-varying channels in the sparse Bayesian learning (SBL) framework and propose a bouquet of novel algorithms for pilot-based channel estimation, and joint channel estimation and data detection, in MIMO-OFDM systems. The proposed algorithms are capable of estimating the sparse wireless channels even when the measurement matrix is only partially known. Further, we employ a first-order autoregressive modeling of the temporal variation of the ga-sparse and gac-sparse channels and propose a recursive Kalman filtering and smoothing (KFS) technique for joint channel estimation, tracking, and data detection. We also propose novel, parallel-implementation based, low-complexity techniques for estimating gac-sparse channels. Monte Carlo simulations illustrate the benefit of exploiting the gac-sparse structure in the wireless channel in terms of the mean square error (MSE) and coded bit error rate (BER) performance.

Asymptotic Bounds on the Power-Delay Tradeoff for Fading Point-to-Point Links From Geometric Bounds on the Stationary Distribution of the Queue Length

The optimal power-delay tradeoff is studied for a time-slotted independently and identically distributed fading point-to-point link, with perfect channel state information at both transmitter and receiver, and with random packet arrivals to the transmitter queue. It is assumed that the transmitter can control the number of packets served by controlling the transmit power in the slot. The optimal tradeoff between average power and average delay is analyzed for stationary and monotone transmitter policies. For such policies, an asymptotic lower bound on the minimum average delay of the packets is obtained, when average transmitter power approaches the minimum average power required for transmitter queue stability. The asymptotic lower bound on the minimum average delay is obtained from geometric upper bounds on the stationary distribution of the queue length. This approach, which uses geometric upper bounds, also leads to an intuitive explanation of the asymptotic behavior of average delay. The asymptotic lower bounds, along with previously known asymptotic upper bounds, are used to identify three new cases where the order of the asymptotic behavior differs from that obtained from a previously considered approximate model, in which the transmit power is a strictly convex function of real valued service batch size for every fade state.

Near-Optimal Detection Thresholds for Bayesian Spectrum Sensing Under Fading

This paper considers the problem of energy-based, Bayesian spectrum sensing in cognitive radios under various fading environments. Under the well-known central limit theorem based model for energy detection, we derive analytically tractable expressions for near-optimal detection thresholds that minimize the probability of error under lognormal, Nakagami-m, and Weibull fading. For the Suzuki fading case, a generalized gamma approximation is provided, which saves on the computation of an integral. In each case, the accuracy of the theoretical expressions as compared to the optimal thresholds are illustrated through simulations.

Error exponent analysis of energy-based Bayesian decentralized spectrum sensing under fading

This paper considers decentralized spectrum sensing, i.e., detection of occupancy of the primary users' spectrum by a set of Cognitive Radio (CR) nodes, under a Bayesian set-up. The nodes use energy detection to make their individual decisions, which are combined at a Fusion Center (FC) using the K-out-of-N fusion rule. The channel from the primary transmitter to the CR nodes is assumed to undergo fading, while that from the nodes to the FC is assumed to be error-free. In this scenario, a novel concept termed as the Error Exponent with a Confidence Level (EECL) is introduced to evaluate and compare the performance of different detection schemes. Expressions for the EECL under general fading conditions are derived. As a special case, it is shown that the conventional error exponent both at individual sensors, and at the FC is zero. Further, closed-form lower bounds on the EECL are derived under Rayleigh fading and lognormal shadowing. As an example application, it answers the question of whether to use pilot-signal based narrowband sensing, where the signal undergoes Rayleigh fading, or to sense over the entire bandwidth of a wideband signal, where the signal undergoes lognormal shadowing. Theoretical results are validated using Monte Carlo simulations. (C) 2015 Elsevier B.V. All rights reserved.

Modeling of Channel Potential and Subthreshold Slope of Symmetric Double-Gate Transistor

A new physically based classical continuous potential distribution model, particularly considering the channel center, is proposed for a short-channel undoped body symmetrical double-gate transistor. It involves a novel technique for solving the 2-D nonlinear Poisson's equation in a rectangular coordinate system, which makes the model valid from weak to strong inversion regimes and from the channel center to the surface. We demonstrated, using the proposed model, that the channel potential versus gate voltage characteristics for the devices having equal channel lengths but different thicknesses pass through a single common point (termed ``crossover point''). Based on the potential model, a new compact model for the subthreshold swing is formulated. It is shown that for the devices having very high short-channel effects (SCE), the effective subthreshold slope factor is mainly dictated by the potential close to the channel center rather than the surface. SCEs and drain-induced barrier lowering are also assessed using the proposed model and validated against a professional numerical device simulator.

Spatial B-jump at sudden channel enlargements with abrupt drop

An analytical and experimental study of the hydraulic jump in stilling basins with abrupt drop and sudden enlargement, called the spatial B-jump here, is carried out for finding the sequent depth ratio and resulting energy dissipation. The spatial B-jump studied has its toe downstream of the expansion section, and the stream lines at the toe are characterized by downward curvature. An expression is obtained for the sequent depth ratio based on the momentum equation with suitable assumptions for the extra pressure force term because of the abrupt drop in the bed and sudden enlargement in the basin width. Predictions compare favorably with experiments. It is shown that the spatial B-jump needs less tailwater depth, thereby enhancing the stability of the jump when compared either with spatial jump, which forms in sudden expanding channels, or with B-jump, which forms in a channel with an abrupt drop in bed. It is also shown that there is a significant increase in relative energy loss for the spatial B-jump compared to either the spatial jump or B-jump alone.

Helix-sheet interconversion in a synthetic pore lining peptide derived from a designed ion channel

We have designed a four-helix protein that is expected to tetramerize in the membrane to form an ion channel with a structurally well defined pore. A synthetic peptide corresponding to the channel lining helix facilitates ion transport across liposomal membranes and largely helical in membranes. Detailed circular dichroism studies of the peptide in methanol, water and methanal-water mixtures reveal that it is helical in methanol, beta-structured in 97.5% water and a combination of these two structures at intermediate compositions of methanol and water. A fluorescence resonance energy transfer study of the peptide shows that the peptide is monomeric in methanol but undergoes extensive anti-parallel aggregation in aqueous solution.