Orthogonal frequency-division multiplexing (OFDM) and single-carrier frequency-domain equalization (SC-FDE) are the two commonly adopted modulation schemes for frequency-selective channels. Compared to SC-FDE, OFDM generally achieves higher data rates but at the cost of higher transmit signal peak-to-average power ratio (PAPR), which leads to lower power-amplifier efficiency. This paper studies a multi-group single carrier modulation scheme, termed flexible multi-group single carrier (FMG-SC), which encapsulates both OFDM and SC-FDE as special cases, thus achieving more flexible rate-PAPR tradeoffs between them. Specifically, in FMG-SC, the total bandwidth is divided into a set of orthogonal subcarriers that, based on the channel gains, are flexibly mapped to multiple non-overlapping groups, and SC-FDE is applied over each group independently to send multiple data streams in parallel. We investigate the joint subcarrier grouping and power allocation optimization problem to maximize the achievable rate of our proposed FMG-SC scheme for both the cases with Gaussian signaling and with practical modulation constellation (e.g., quadrature amplitude modulation), respectively. For both cases, the optimization problem is non-convex in general, for which we propose a two-step approach for finding a high-quality approximate solution efficiently. First, with any given subcarrier grouping, we show that the optimal power allocation can be obtained via convex optimization techniques. Second, with fixed power allocation, we propose low-complexity algorithms for the subcarrier grouping design catering to the SC-FDE receiver. Numerical results show that our proposed algorithms perform close to the optimal solution obtained via exhaustive search over all subcarrier groupings yet with substantially reduced complexity. Moreover, the achievable rate of our proposed FMG-SC scheme with Gaussian signaling approaches the OFDM channel capacity and significantly outperforms that of SC-FDE. Furthermore, with practical modulation constellation, numerical results show that our proposed FMG-SC scheme greatly outperforms the existing single carrier frequency-division multiple access in terms of achievable rate but with moderately increased PAPR.

This paper presents a low complexity implementation of carrier phase and symbol timing synchronization on an OMAP-LI37 DSP-ARM dual core processor for a M -ary phase-shift-keying (M -PSK) based fully digital downhole telemetry system. The synchronization uses a data-aided algorithm (DA) that exploits information from the pilot symbols (PS) in each transmission to retrieve the timing epoch and carrier phase. Its implementation, in conjunction with the rest of the modem functionality, uses only the optimized TMS320C67x DSP and Math libraries to shorten the development time and reduce implementation complexity. Simulation results confirm its convergence to the modified Cramer-Rao bound (MCRB). Moreover, real-time implementation on a mono-conductor telemetry system employing quadrature phase-shfit keying (QPSK) modulation is performed to demonstrate its effectiveness in real-world environments.

Orthogonal frequency division multiplexing (OFDM) and single-carrier frequency domain equalization (SC-FDE) are two commonly adopted modulation schemes for frequency-selective channels. Compared to SC-FDE, OFDM generally achieves higher data rate, but at the cost of higher transmit signal peak-to-average power ratio (PAPR) that leads to lower power amplifier efficiency. This paper proposes a new modulation scheme, called flexible multi-group single-carrier (FMG-SC), which encapsulates both OFDM and SC-FDE as special cases, thus achieving more flexible rate-PAPR trade-offs between them. Specifically, a set of frequency subcarriers are flexibly divided into orthogonal groups based on their channel gains, and SC-FDE is applied over each of the groups to send different data streams in parallel. We aim to maximize the achievable sum-rate of all groups by optimizing the subcarrier-group mapping. We propose two low-complexity subcarrier grouping methods and show via simulation that they perform very close to the optimal grouping by exhaustive search. Simulation results also show the effectiveness of the proposed FMG-SC modulation scheme with optimized subcarrier grouping in improving the rate-PAPR trade-off over conventional OFDM and SC-FDE.

This paper consider the problem of relaxing the spatial coverage requirement on the mechanical rotation in the direction finding (DF) approach based on the received power measurements from single antenna pointing to different directions. Under incomplete spatial coverage, we show that the least square (LS) solution used to transform the problem into its spectral form is no longer accurate due to its ill-conditioned system matrix. To overcome this, we propose an approach based on spatial remodeling of the spatial power measurements such that its spatial periodicity can be adjusted according to the spatial coverage. The approach also incorporates the Tikhonov regularization in calculating the LS solution based on the new system matrix. Upon arriving at the new spectral form, the Cadzow-annihilating filter method can then be used to estimate the direction-of-arrival. Both simulation and experimental results are presented to show the efficacy of the proposed method.

In many array processing, the received signals are nonstationary, or in particular, noncircular. Widely linear minimum variance distortionless response (WL MVDR) beamformers can exploit the noncircularity of received signals and improve the performance of the conventional MVDR beamformer. However, in the optimum WL MVDR beamformer, the array steering vector (ASV) and the signal noncircularity coefficient should be known a priori for the signal of interest. This requirement puts strict limitation to the implementation of this beamformer. We therefore in this paper propose a robust approach to the optimal WL MVDR beamformer that can deal with the uncertainties in the ASV and noncircularity coefficient. Two variants of the proposed approach are developed based on the treatment of the uncertainties. By doing so, the requirement on the exact information is relaxed while the performance improvement can still be obtained. Simulation studies are also provided to illustrate the performance of the proposed approach.

This paper considers the problem of extending the single antenna power measurements based direction finding to the two-dimensional (2D) case, and proposes a method to estimate the azimuth-elevation direction-of-arrival (DOA) from a matrix of received power. Exploiting the fact that the azimuth-elevation antenna pattern is 2D bandlimited, the problem can be transformed into a 2D spectral analysis problem. The proposed method first decomposes the 2D spectral analysis problem into one-dimensional case and then solved them independently. As the solution does not ensure that the estimated azimuth and elevation is in correct order, the solution is subjected to permutation ambiguity. This can then be solved by finding the permutation that best matches the 2D spectral representation. Simulation results demonstrating the high-resolution capability of the proposed method in two-source case and the effectiveness in fivesource case are also presented in this paper.

In this paper, we present an approach to design passive coupling matrix to overcome the performance limitation of direction finding using small aperture array. This approach is inspired by the sound localization acuity of a parasitic fly called Ormia ochracea. Motivated by the requirement from practical implementation that each element of the coupling matrix is realized as a passive analog phase shifter and attenuator in a similar fashion as that of conventional analog beamforming, in the proposed approach we confine the magnitude of each element to being no larger than 1. By taking the advantage of the coupling mechanism, this approach can design compact aperture antenna array yet with much improved direction finding performance. Furthermore, the proposed design is applicable to arbitrary array geometry. Numerical examples illustrate the effectiveness of the proposed approach and show a performance gain of 30 over the uncoupled array of the same aperture of 10 cm diameter at 40 MHz.

Two new approaches to adaptive beamforming in sparse subarray-based sensor arrays are proposed. Each subarray is assumed to be well calibrated but the intersubarray gain and/or phase mismatches are assumed to remain unknown or imperfectly known. Our first approach is based on a worst-case beamformer design that, unlike the existing worst-case designs, exploits a structured ellipsoidal uncertainty model for the signal steering vector. Our second approach exploits the idea of estimating the signal steering vector by maximizing the output power of the minimum variance beamformer. Several modifications of our second approach are developed for the cases of gain-and-phase and phase-only intersubarray distortions.

This paper proposes an iterative robust capon beamformer (IRCB) with adaptive uncertainty level. The approach iteratively estimates the actual steering vector based on conventional RCB formulation. Instead of using a fixed uncertainty level, we adaptively update the uncertainty level at each iteration. The uncertainty is updated based on the projection of the presumed steering vector onto the noise subspace. The iteration converges when the noise subspace projection is zero. We additionally impose a constraint that restricts the estimated steering vector to be within a spatial sector in order to overcome inappropriate updating of the uncertainty due to subspace swap at low signal-to-noise ratio (SNR) case. Simulation results show that the adaptive uncertainty based IRCB converges faster than the fixed uncertainty based IRCB. Besides alleviating the need to assume any knowledge on the mismatch, the proposed beamformer requires lower computational cost as compared to the convex optimization based beamformer design.