We consider the problem of dynamically optimizing a multiple-input multiple-output (MIMO) wireless waveform in a given potentially heavily utilized fixed frequency band with applications in near-field or far-field autonomous machine-to-machine communications. In particular, we find the transmitter beam weight vector and the pulse code sequence that maximize the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum SINR joint space-time receiver filter. We propose and derive two novel model-based solutions: (a) Disjoint, space first (transmit weight vector) then time (pulse code sequence) waveform optimization and (b) jointly optimal transmit weight vector and pulse code sequence optimization (a mixed integer programming problem.) The proposed formally derived algorithmic solutions are studied in extensive simulations under varying waveform code length, near-field/far-field and spread-spectrum/ non-spread-spectrum interference, in light and dense interference scenarios. Our findings highlight the effectiveness of the described methods compared to static conventionally designed MIMO links and the remarkable ability of the joint space-time optimized waveforms to avoid heavy interference.

Fast, robust, high-accuracy localization is a key enabler for future location-aware applications in streetscape communication networks and next-generation networked autonomous agents. Specifically, massive multiple-input and multiple-output (MIMO) antenna systems have received increasing attention due to high angular resolution. However, in dense multipath environments, such as urban areas, pure direction-of-arrival (DoA)-based techniques have not been very popular due to large localization errors.In this paper, we present and evaluate, on real measurements from the POWDER-RENEW platform, a novel method to carry out DoA estimation from just one antenna array snapshot. The measurements are taken from an indoor testbed that is based on a massive MIMO orthogonal frequency-division multiplexing (OFDM) system. Experimental results – in the presence of spatial aliasing – show that for certain emitter locations our proposed universal one-shot DoA estimator outperforms in azimuth/elevation accuracy state-of-the-art subspace-based methods that involve collection of a sufficiently large data record of antenna array snapshots.

Spreading codes are the core of the spread spectrum transmission. In this paper, a novel channel-dependent code allocation procedure for enhancing security in multi-carrier code division multiple access (MC-CDMA) system is proposed and investigated over frequency-selective fading. The objective of the proposed technique is to assign the codes to every subcarrier of active/legitimate receivers (Rxs) based on their channel frequency response (CFR). By that, we ensure security for legitimate Rxs against eavesdropping while preserving mutual confidentiality between the legitimate Rxs themselves. To do so, two assigning modes; fixed assigning mode (FAM) and adaptive assigning mode (AAM), are exploited. The effect of the channel estimation error and the number of legitimate Rxs on the bit error rate (BER) performance is studied. The presented simulations show that AAM provides better security with a complexity trade-off compared to FAM. While the latter is more robust against the imperfection of channel estimation.