We introduce multiple access schemes for a novel non-coherent single-carrier (SC) modulation, called modulation on conjugate-reciprocal zeros (MOCZ), to enable a high-spectral efficient and mobile machine-type-communication for up- and downlink transmissions. The modulation can be used for a time-division and frequency-division multiple access (FDMA). To utilize FDMA we will adapt SC-FDMA techniques and demonstrate that a time-overlay of multiple users (MU) can significantly reduce the peak-to-average-ratio (PAPR) in the downlink. Furthermore, we compare the MU-MOCZ schemes to standard modulations in narrow-band-Internet-of-things (NBIoT) scenarios with smallest transport block size in the LTE bands. To adapt the standard numerology of the transport channel we introduced soft decoding for higher order MOCZ designs. We demonstrate that our proposed schemes outperforms the standardized scheme in highly mobile and frequency-selective fading channels by a slight PAPR reduction in the downlink.

To provide a reliable wireless uplink for users in a given ground area, one can deploy Unmanned Aerial Vehicles (UAVs) as base stations (BSs). In another application, one can use UAVs to collect data from sensors on the ground. For a power-efficient and scalable deployment of such flying BSs, directional antennas can be utilized to efficiently cover arbitrary 2-D ground areas. We consider a large-scale wireless path-loss model with a realistic angle-dependent radiation pattern for the directional antennas. Based on such a model, we determine the optimal 3-D deployment of N UAVs to minimize the average transmit-power consumption of the users in a given target area. The users are assumed to have identical transmitters with ideal omnidirectional antennas and the UAVs have identical directional antennas with given half-power beamwidth (HPBW) and symmetric radiation pattern along the vertical axis. For uniformly distributed ground users, we show that the UAVs have to share a common flight height in an optimal power-efficient deployment, by simulations. We also derive in closed-form the asymptotic optimal common flight height of N UAVs in terms of the area size, data-rate, bandwidth, HPBW, and path-loss exponent.

We investigate practical aspects of a recently introduced blind (noncoherent) communication scheme, called modulation on conjugate-reciprocal zeros (MOCZ). MOCZ is suitable for a reliable transmission of sporadic and short-packets at ultra-low latency and high spectral efficiency via unknown multipath channels, which are assumed to be static over the receive duration of one packet. The information is modulated on the zeros of the transmitted discrete-time baseband signal's z- transform. Because of ubiquitous impairments between the transmitter and receiver clocks, a carrier frequency offset occurs after down-conversion to the baseband. This results in a common rotation of the zeros. To identify fractional rotations of the base angle in the zero-pattern, we propose an oversampled direct zero-testing decoder to identify the most likely one. Integer rotations correspond to cyclic shifts of the binary message, which we determine by cyclically permutable codes (CPC). Additionally, the embedding of CPCs into cyclic codes, enables additive error-correction which reduces the bit-error-rate tremendously. Furthermore, we exploit the trident structure in the signal's autocorrelation for an energy based detector to estimate timing offsets and the effective channel delay spread. We finally demonstrate how this joint data and channel estimation can be largely improved by receive antenna diversity at low SNR.

In many quantization problems, the distortion function is given by the Euclidean metric to measure the distance of a source sample to any given reproduction point of the quantizer. We will in this work regard distortion functions, which are additively and multiplicatively weighted for each reproduction point resulting in a heterogeneous quantization problem, as used for example in deployment problems of sensor networks. Whereas, normally in such problems, the average distortion is minimized for given weights (parameters), we will optimize the quantization problem over all weights, i.e., we tune or control the distortion functions in our favor. For a uniform source distribution in one-dimension, we derive the unique minimizer, given as the uniform scalar quantizer with an optimal common weight. By numerical simulations, we demonstrate that this result extends to two-dimensions where asymptotically the parameter optimized quantizer is the hexagonal lattice with common weights. As an application, we will determine the optimal deployment of unmanned aerial vehicles (UAVs) to provide a wireless communication to ground terminals under a minimal communication power cost. Here, the optimal weights relate to the optimal flight heights of the UAVs.

We introduce a novel blind (noncoherent) communication scheme, called modulation on conjugate-reciprocal zeros (MOCZ), pronounced as “Moxie,” to reliably transmit sporadic short-packets over unknown wireless multipath channels. In MOCZ, the information is modulated onto the zeros of the transmitted discrete-time baseband signal's z-transform, which yields to a codebook of non-orthogonal signals. In the absence of additive noise, the zero structure of the signal is perfectly preserved at the receiver, no matter what the channel impulse response (CIR) is. Furthermore, by a proper selection of the zeros, we show that MOCZ is not only invariant to the CIR but also robust against additive noise. Starting with the maximum-likelihood estimator, we define a low complexity and reliable decoder and compare it to various state-of-the-art noncoherent multipath schemes, such as OFDM index-modulation (IM), OFDM pilot-aided, OFDM differential-modulation, and pulse-position-modulation. Our scheme outperforms all schemes and maintains its performance even if the length becomes shorter than the CIR.

Based on recent results on the challenges of identifiability in blind deconvolution and new methods for blind deconvolution with the knowledge of autocorrelation functions, a novel approach to secure communication over wireless channels is provided by using the Binary Modulation on Conjugated Zeros design. In particular, the blind deconvolution of a transmitted sequence via a wireless channel with Rayleigh fading is rendered impossible through the introduction of common zeros. A signal codebook design is provided as well as a decoding strategy with a shared secret key for the legitimate user. The probability of an eavesdropper guessing the correct key is computed and shown to converge to zero nearly exponentially with an increasing length of the key.

Providing short-message communication and simultaneous channel estimation for sporadic and fast fading scenarios is a challenge for future wireless networks. In this work we propose a novel blind communication and deconvolution scheme by using Huffman sequences, which allows to solve three important tasks at once: (i) determination of the transmit power (ii) identification of the instantaneous discrete-time FIR channel if the channel delay is less than L/2 and (iii) simultaneously communicating L-1 bits of information. Our signal reconstruction uses a recent semi-definite program that can recover two unknown signals from their auto-correlations and cross-correlations. This convex algorithm shows numerical stability and operates fully deterministic without any further channel assumptions.

In this note we show that stable recovery of complex-valued signals x ϵ Cnup to a global sign can be achieved from the magnitudes of 4n - 1 Fourier measurements when a certain symmetrization and zero-padding is performed before measurement (4n - 3 is possible in certain cases). For real signals, symmetrization itself is linear and therefore our result is in this case a statement on uniform phase retrieval. Since complex conjugation is involved, such measurement procedure is not complex-linear but recovery is still possible from magnitudes of linear measurements on, for example, (Re(x), Im(x)).

In this paper we show that convolutions of sufficiently sparse signals always admit a non-zero lower bound in energy if oversampling of its Fourier transform is employed. This bound is independent of the signals and the ambient dimension and is determined only be the sparsity of both input signals. This result has several implications for blind system and signal identification and detection, noncoherent communication of sporadic and short-message type user data and strategies for its compressive reception. Furthermore, we give some first insights into the combinatorial nature of this problem, its scaling behavior and present numerical results as well.

For several communication models, the dispersive part of a communication channel is described by a bilinear operation T between the possible sets of input signals and channel parameters. The received channel output has then to be identified from the image T(X, Y) of the input signal difference sets X and the channel state sets Y. The main goal in this contribution is to characterize the compressibility of T(X, Y) with respect to an ambient dimension N. In this paper we show that a restricted norm multiplicativity of T on all canonical subspaces X and Y with dimension S resp. F is sufficient for the reconstruction of output signals with an overwhelming probability from O((S + F) log N) random sub-Gaussian measurements. Thus, in this case, the number of degrees of freedom of each output grows only additively instead of multiplicatively with the input dimensions (sparsity) S and F. This is a relevant improvement in the output compressibility and suggests a substantially reduced rate in compressed sampling algorithms.

In this contribution we present a novel method for constructing orthogonal pulses for UWB impulse radio transmission under the FCC spectral mask constraint. In contrast to previous work we combine a convex formulation of the spectral design with Lowdin's orthogonalization method [1], which delivers a shift--orthogonal basis optimally close (in energy) to the initial pulse, which generates (in a stable way) the shift--invariant space. The convex formulation of the spectral design is achieved by approximating the FCC mask with a finite--order filter matched to Gaussian monocycles as input. The output pulse then has high energy concentration in the passband (NESP value). Using Lowdin's orthogonalization we compute the corresponding shift--orthogonal pulse. We show that our approach is able to generate for finitely many shifts, orthogonal equal energy pulses with nearly the same NESP value. Furthermore, we show that the orthogonalization procedure can be well approximated using the Zak transform allowing for an efficient implementation with the discrete Fourier transform. Surprisingly, we could observe, that for certain parameters, this approximation yields almost the same performance as the exact Lowdin method.