In this paper, we explore a multiple-input multiple- output (MIMO) system with orthogonal frequency division multiplexing (OFDM) transmissions and study the low peak- to-average power ratio (PAPR) MIMO-OFDM waveform design for integrated sensing and communications (ISAC). This is done by leveraging a weighted objective function on both communication and radar performance metrics under power and PAPR constraints. The formulated optimization problem can be equivalently transformed into several sub-problems which can be parallelly solved by the semi-definite relaxation (SDR) method and the optimal rank-1 solution can be obtained in general. The feasibility, effectiveness, and flexibility of the proposed low-PAPR MIMO-OFDM waveform design method are demonstrated by a range of simulations on communication sum rate, symbol error rate as well as radar beampattern and detection probability.

We propose a method to estimate doubly-selective channels based on the time and frequency correlation of scattered pilots. To reduce the interference at the pilot and data positions, we apply an iterative interference cancellation scheme. Our method is applicable to arbitrary linear modulation techniques, with Orthogonal Frequency Division Multiplexing (OFDM) and Filter Bank Multicarrier Modulation (FBMC), being special cases. Simulations over doubly-selective channels show that our channel estimation method comes close to having perfect channel knowledge available. A downloadable Matlab code supports reproducibility.

We propose a novel modulation scheme which combines the advantages of filter bank multi-carrier (FBMC)-offset quadrature amplitude modulation and single-carrier frequency-division multiple access (SC-FDMA). On the top of a conventional FBMC system, we develop a novel precoding method based on a pruned discrete Fourier transform (DFT) in combination with one-tap scaling. The proposed technique has the same peak-to-average power ratio as SC-FDMA but does not require a cyclic prefix and has much lower out-of-band emissions. Furthermore, our method restores complex orthogonality, and the ramp-up and ramp-down period of FBMC is dramatically decreased, allowing low latency transmissions. Compared to pure SC-FDMA, the computational complexity of our scheme is only two times higher. Simulations over doubly selective channels validate our claims, further supported by a downloadable MATLAB code. Note that pruned DFT-spread FBMC can equivalently be interpreted as a modified SC-FDMA transmission scheme. In particular, the requirements on the prototype filter are less strict than in conventional FBMC systems.

This paper presents a report on mutual information based on measured indoor millimeter-wave (mmWave) channels with multiple antennas at input and output (MIMO). We show that for fixed indoor communication systems, an optimal antenna element spacing can be found such that the measured mutual information almost reaches the capacity of a perfectly orthogonal (theoretical) MIMO channel (with the same number of receiver (RX) and transmitter (TX) antennas). Secondly, we present, that even though the measured channel transfer functions (CTFs) exhibit large fluctuations (i.e., temporal dispersion), the mutual information is mainly determined by the mean singular value of the line-of-sight (LOS) components. Due to their strong variations over frequency mmWave channels are tedious when describing them with classical methods in the frequency domain. An approximation by numerous flat subbands leads to an error in mutual information (MI) by 2bit/s/Hz (for 80% probability). In comparison, our proposed method in the time domain, however, offers a notably smaller error (1bit/s/Hz for 80% probability).

Superior spectral properties of Filter Bank Multi-Carrier (FBMC) techniques make them an interesting choice for future wireless systems. In order to directly apply well known pilot-symbol aided channel estimation in FBMC, however, the intrinsic imaginary interference has to be canceled. Such cancellation method is usually designed for a doubly-flat channel. In this paper, we investigate the effects of doubly-selectivity, that is, time-selectivity and frequency-selectivity, on the channel estimation Mean Squared Error (MSE) in FBMC. The calculation of the MSE is based on a compact matrix description, allowing us also to find an MSE minimizing channel estimation method that takes the underlying waveform into account.

We introduce a novel directional channel sounding concept where we sweep a horn antenna around its phase center. Directional channel measurements are thus carried out at a fixed coordinate in space. To verify our concept, we conducted multi-carrier measurements with 2 GHz of measurement bandwidth. The directional broadband channel was sampled uniformly within a cube of three wavelengths side length. In this contribution, we compare narrowband measurements with spatial averaging to traditional broadband channel sounding. We saw that, spatial filtering through directional antennas leads to a limited number of propagation paths in the channel. We show the difference of both approaches and explain the deviation by spatial correlation. The spatial correlation is evaluated at several two-dimensional slices. We observed wavelength-periodic correlations.

Future wireless systems will be characterized by a large range of possible uses cases. This requires a flexible allocation of the available time-frequency resources, which is difficult in conventional orthogonal frequency division multiplexing (OFDM). Thus, modifications of OFDM, such as windowing or filtering, become necessary. Alternatively, we can employ a different modulation scheme, such as filter bank multi-carrier (FBMC). In this paper, we provide a unifying framework, discussion, and performance evaluation of FBMC and compare it with OFDM-based schemes. Our investigations are not only based on simulations, but are substantiated by real-world testbed measurements and trials, where we show that multiple antennas and channel estimation, two of the main challenges associated with FBMC, can be efficiently dealt with. In addition, we derive closed-form solutions for the signal-to-interference ratio in doubly-selective channels and show that in many practical cases, one-tap equalizers are sufficient. A downloadable MATLAB code supports reproducibility of our results.

Filter bank multicarrier modulation is considered as a possible candidate for 5G. In this paper, we consider pilot-symbol aided channel estimation and address the problem of canceling the imaginary interference at the pilot positions. We develop a matrix formulation for the transmission system which allows us to formulate general conditions on the auxiliary pilot symbols, capturing also the interde-pendency of closely spaced pilots and an arbitrary number of auxiliary pilot symbols. By using two auxiliary symbols per pilot instead of one, we are able to improve the peak-to-average power ratio as well as the achievable capacity for small to medium signal-to-noise ratios. The achievable capacity can further be increased by interference cancellation based on linear precoding for which we propose an algorithm to find the coding matrix required. Finally, we compare auxiliary pilot symbols and linear precoding in terms of complexity and performance.

Filter Bank MultiCarrier (FBMC) might replace Orthogonal Frequency Division Multiplexing (OFDM) in 5G. For such FBMC system, we derive closed-form expressions for the Bit Error Probability (BEP) including channel estimation, whereas we focus on the comparison of FBMC with OFDM. We assume additive white Gaussian noise and a Rayleigh fading channel with low delay spread and low Doppler spread, so that the channel induced interference can be neglected compared to the noise. Our channel estimation is based on pilot symbols whereby the imaginary interference, inherently caused in FBMC, is canceled at the pilot positions either by auxiliary symbols or through coding. Moreover, we propose an optimal power allocation between pilot symbols and data symbols to minimize the BEP.

In high mobility orthogonal frequency division multiplexing systems, subcarriers are no longer orthogonal, causing Inter-Carrier Interference (ICI). Equalization then becomes more challenging and requires an accurate estimate of the time-variant channel. In this paper, we propose a novel Minimum Mean Squared Error (MMSE) estimation of the sampled time-variant transfer function. Based on such channel estimation, we propose an iterative three step ICI mitigation technique whereby each step increases the channel estimation accuracy and, consequently, the performance of our MMSE equalization. In Step 1, we consider ICI as an additional noise term. In Step 2, we reduce the ICI at pilot positions and finally, in Step 3, we treat all estimated data symbols, obtained from Step 2, as if they were pilot symbols. We evaluate the Bit Error Ratio (BER) of our ICI mitigation technique by means of simulation and testbed measurements (up to 400 km/h). In both cases, we achieve a BER close to perfect channel knowledge and zero ICI.

In this paper, we derive closed-form capacity expressions for a low complexity bit-interleaved coded modulation system with uniform inputs in a Rayleigh fading channel with additive white Gaussian noise. Additionally, we include pilot-symbol assisted channel estimation in our considerations. Finding a closed-form solution is enabled by assuming quantization and that the decoder has no channel state information. The effects of these assumptions on the capacity are investigated separately. To verify our closed-form expressions and to show the applicability of our system model to real world physical channels, we perform measurements using the Vienna Wireless Testbed.

For an orthogonal frequency-division multiplexing system with pilot-symbol aided channel estimation, we compare the measured bit error ratio to the theoretical bit error probability. In order to measure mobile physical systems, we utilize the Vienna Wireless Testbed which has been augmented by a rotation wheel unit. The analytical solution assumes Rayleigh fading, additive Gaussian noise, and an arbitrary linear interpolation method to estimate the unknown channel taps. Our measurements confirm our assumptions and demonstrate convincingly that our theoretical expressions accurately model the true physical behavior, even for speeds of up to 100\,km/h.