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AbstractA data classification model in which the average mutual information between source objects and made decisions is a function of the error probability is investigated. Optimization of the model consists in finding a tradeoff “mutual information–error probability” (MIEP) relation between the minimal average mutual information and the error probability, which is analogous to the well-known rate distortion function for source coding with a given fidelity in the case of a noisy observation channel. A lower bound for the MIEP relation is constructed, which provides a lower bound for the classification error probability on a given set of objects for any fixed value of the average mutual information. The MIEP relation and its lower bound are generalized to ensembles of sources. The obtained bounds are useful for estimating the error probability redundancy for decision algorithms with given sets of discriminant functions.

We consider the problem of detecting (testing) Gaussian stochastic sequences (signals) with imprecisely known means and covariance matrices. An alternative is independent identically distributed zero-mean Gaussian random variables with unit variances. For a given false alarm (1st-kind error) probability, the quality of minimax detection is given by the best miss probability (2nd-kind error probability) exponent over a growing observation horizon. We study the maximal set of means and covariance matrices (composite hypothesis) such that its minimax testing can be replaced with testing a single particular pair consisting of a mean and a covariance matrix (simple hypothesis) without degrading the detection exponent. We completely describe this maximal set.

Reconfigurable intelligent surface (RIS)‐empowered communications is on the rise and is a promising technology envisioned to aid in 6G and beyond wireless communication networks. RISs can manipulate impinging waves through their electromagnetic elements enabling some sort of control over the wireless channel. The potential of RIS technology is explored to perform a sort of virtual equalization over‐the‐air for frequency‐selective channels, whereas equalization is generally conducted at either the transmitter or receiver in conventional communication systems. Specifically, using an RIS, the frequency‐selective channel from the transmitter to the RIS is transformed to a frequency‐flat channel through elimination of inter‐symbol interference (ISI) components at the receiver. ISI is eliminated by adjusting the phases of impinging signals particularly to maximize the incoming signal of the strongest tap. First, a general end‐to‐end system model is provided and a continuous to discrete‐time signal model is presented. Subsequently, a probabilistic analysis for elimination of ISI terms is conducted and reinforced with computer simulations. Furthermore, a theoretical error probability analysis is performed along with computer simulations. It is analysed and demonstrated that conventional RIS phase alignment methods can successfully eliminate ISI, and the RIS‐aided communication channel can be converted from frequency‐selective to frequency‐flat.

In this letter, a novel multiple‐input multiple‐output transceiver technique, named space–time line coded spatial modulation (STLC‐SM) is proposed, where two modulation symbols are transmitted through one of the multiple transmit antennas determined by the incoming information bits after constellation‐rotated STLC encoding. The receiver decodes the transmitted modulation symbols and the activated antenna index through an optimal joint maximum‐likelihood detector. As a main result, the closed‐form upper‐bound of bit‐error‐rate of the proposed STLC‐SM system in general antenna configurations is mathematically analysed. Finally, it is validated that the STLC‐SM significantly outperforms the conventional STLC in terms of the bit‐error‐rate.

This letter derives an approximate average bit error rate (BER) expression of M‐ary phase shift keying with a noisy phase reference in a Nakagami‐m fading channel. The proposed closed‐form expression is general for the M‐ary case, including previous results for both binary and quadrature phase shift keying. The accuracy of the proposed average BER expression is verified through a comparison with the exact BER.

It is numerically shown that bit error rate (BER) performance of probabilistic amplitude shaping (PAS) applying a bit‐to‐symbol mapping of non‐Gray natural binary code assigned to 64‐quadrature amplitude modulation is significantly improved by bit‐interleaved coded modulation with iterative detection (BICM‐ID). The obtained BER performance outperforms the PAS using a standard Gray code mapping. Furthermore, it has been numerically verified that the non‐Gray natural binary code mapping is suitable for BICM‐ID by analysing the extrinsic information transfer chart. In addition, two degradation factors, the shaping and the coding gaps are estimated, from the Shannon limit by analysing mutual information characteristics. The obtained results quantitatively show that BICM‐ID can effectively suppress the coding gap of the PAS applying non‐Gray mapping in BER performance.

This letter derives the probability distribution function (PDF) of received symbols for orthogonal frequency‐division multiplexing (OFDM) based massive multiple‐input, multiple‐output (MMIMO) systems, which uses maximal‐ratio combining (MRC) detection. The effects of noise and interferences are evaluated through random variables, and the PDF is then derived from their joint probability and characteristic functions. The bit error rate (BER) using Binary and Quadrature Phase Shift Keying (BPSK, QPSK), and M‐ary Quadrature Amplitude Modulation (QAM) waveforms is then analyzed by using this PDF. Simulation and analytical results confirm that the derived equations provided accurate PDF and BER, and therefore, can be used efficiently to evaluate performance of OFDM‐MMIMO systems.

The bit error rate (BER) computation for coherently detected orthogonal signals in additive white Gaussian noise requires numerical integration, which can be cumbersome in low‐complexity devices. Here, a BER computation approach that circumvents the need for repeated numerical integration is proposed. First, a low‐complexity BER approximation formula is selected, with unknown parameters to be determined. Second, this letter determines the unknown parameters by fitting the BER approximation to a few BER values known in advance. The BER comparison with the exact results shows that the accuracy of the proposed low‐complexity approach is satisfactory for several constellation sizes of interest. This enables the possibility of BER self‐computation in low‐complexity devices that use orthogonal signals, like those used in the Internet of Things (IoT).

Puncturing and shortening are two common ways to achieve rate‐compatible non‐systematic polar codes (NSPCs). Systematic polar codes (SPCs) have been shown to outperform NSPCs with the same encoding and decoding complexity. However, rate‐compatible SPCs have never been comprehensively studied in previous work. In this paper, two rate‐compatible algorithms for SPCs are first proposed: uniform puncturing (UP) algorithm and uniform shortening (US) algorithm, which are referred to as SPC‐UP and SPC‐US, respectively. In order to effectively estimate the maximum likelihood decoding performance of punctured and shortened polar codes, subsequently, a distance spectrum calculation algorithm based on successive cancellation list (SCL) decoder for rate‐compatible polar codes is proposed. Simulation results show that rate‐compatible SPCs yield better bit error rate performance than rate‐compatible NSPCs while they have the same frame error rate performance under different code rates and decoding algorithms. Eventually, union bounds that are obtained by the distance spectrum to provide the theoretical explanation for the superiority of rate‐compatible SPCs are utilised.

The authors investigate the performance of multiple-input–multiple-output multicarrier direct sequence code division multiple access system operating over arbitrarily and equally correlated η–µ fading channels in terms of average bit error probability and average symbol error probability. Closed form expressions for average error probability using moment generating function-based approach are derived and expressed in terms of Lauricella's multivariate hypergeometric functions. Furthermore, based on numerical results, they observe that the performance of the system improves when the number of multipath clusters increases as well as the number of subcarriers (frequency diversity). Similarly, substantial enhancement in system performance is observed due to the effect of spatial diversity. Finally, they verify the results via Monte Carlo simulation-based method to support the accuracy of the analytical approach and also compare with already published ones.