This paper presents an advanced implementation of the single-snapshot 2D-MUSIC algorithm, enhanced by cross-linear antenna arrays, to improve uplink indoor positioning accuracy using OFDM-based 5G networks. The proposed method adeptly handles multipath interference and non-line-of-sight (NLoS) conditions, demonstrating significant advancements over traditional techniques. Our method not only accurately determines the position of user equipment in two dimensions but also extends to 3D positioning. A novel aspect of our research includes addressing the challenge of unknown time of departure, which often complicates the time of flight calculations necessary for precise localization. By using two strategically placed cross-linear antenna arrays, our system compensates for this uncertainty, providing reliable and precise location estimates even without perfect transmitter-receiver synchronization. Simulation results validate the robustness of our approach, showing exceptional localization accuracy and promising potential for complex IoT applications within industrial settings. Provided the separation between multipath components in either range or angle is sufficiently large, the algorithm is capable of detecting the transmitter with sub-centimeter accuracy.

Spectrum scarcity necessitates innovative, spectral-efficient strategies to meet the ever-growing demand for high data rates. Faster-than-Nyquist (FTN) signaling emerges as a compelling spectral-efficient transmission method that pushes transmit data symbols beyond the Nyquist limit, offering en-hanced spectral efficiency (SE). While FTN signaling maintains SE with the same energy and bandwidth as the Nyquist signaling, it introduces increased complexity, particularly at higher modulation levels. This complexity predominantly arises from the detection process, which seeks to mitigate the intentional intersymbol interference generated by FTN signaling. Another challenge involves the generation of reliable log-likelihood ratios (LLRs) vital for soft channel decoders. In this study, we introduce a lookup table (LUT) aided soft output semidefinite relaxation (soSDR) based sub-optimal FTN detector, which can be extended to higher modulation levels. This detector possesses polyno-mial computational complexity, given the negligible complexity associated with soft value generation. Our study assesses the performance of this soft output detector against that of the optimal FTN detector, Bahl, Cocke, Jelinek and Raviv (BCJR) algorithm as the benchmark. The likelihood values produced by our LUT aided semidefinite relaxation (SDR) based FTN signaling detector show promising viability in coded scenario.

This paper studies the application of neural networks to Viterbi detection of Faster-Than-Nyquist (FTN) signals in an intersymbol interference (ISI) channel. In particular, we propose a novel low-complexity neural network structure for calculating the branch metrics, and we explore its suitability for FTN signalling with channel uncertainty. We compare the proposed network to another neural network-based technique for metric calculation, the ViterbiNet, which was originally designed for ISI channels. The simulation results confirm that the proposed neural network outperforms the ViterbiNet, with much lower complexity, and is much more resilient to channel uncertainty than the traditional Viterbi detector, which uses Euclidean distance for metric calculations. We further show that the proposed neural network exhibits robustness to being trained at mismatched SNR values and FTN squeezing parameters, meaning that the number of trained models required can be significantly reduced. Additionally, the results show that the proposed neural network remains a favorable alternative at much higher levels of channel uncertainties, the results also reflect that we can generalize the proposed network to work with different channel models defined by different decaying factors. Finally, we show that we can still achieve a bandwidth efficiency gain of 33% due to FTN by using the proposed network in the presence of channel uncertainty.

Designing multidimensional constellations (MdCs) is an integral part of sparse code multiple access (SCMA). Since the optimal maximum a posteriori (MAP) receiver for SCMA is too complex in most applications, one highly popular technique is the near-optimal message passing algorithm (MPA), where its performance improves with increasing the signal-to-noise ratio (SNR) and the number of iterations. When the number of MPA iterations has to be limited (e.g., low-latency and/or low-complexity and/or energy-sensitive applications), the performance gap between MAP and MPA becomes significant, especially at low-to-medium SNRs. Inspired by the promising features of hypercubes when used along with bit-interleaved coded modulation, we construct novel MdCs which are based on a unitary rotation of a hypercube by a rotation angle that aims to achieve the minimum frame-error-rate (FER). By exploiting special properties of hypercubes, we fit a second-order rational polynomial to a few measured FER samples, and find a close-to-optimal rotation angle at each SNR and MPA iteration. Our proposed MdCs provide substantial performance gains (as much as 2 dB) in comparison to the best known SCMA MdCs in the literature, especially in low-to-medium SNR regions when the number of MPA iterations has to be low, and in the presence of 5G-compliant LDPC codes.

Sparse code multiple access (SCMA) is a potential non-orthogonal multiple access candidate for future wireless systems. The key performance indicators (KPIs) of uplink SCMA multidimensional constellations (MdCs) that should be considered in their design process have recently been identified in conjunction with the LTE turbo code for different channel scenarios. However, it is questionable whether the same KPIs are applicable to designing MdCs when a different error correcting code is employed. In this paper, we investigate the effect of the high-rate and low-rate 5G low density parity check (LDPC) codes on determining KPIs in designing MdCs for uplink SCMA systems under various channel scenarios. Through simulations, we show that similar results to the LTE turbo coded case occur in the presence of 5G LDPC code, with one notable exception over one specific scenario. The exception is in the performance of one MdC, which has a low number of distinct points; its performance is significantly worse than predicted by the KPIs when the low-rate 5G LDPC code is employed. This phenomenon happens due to the inherent structure of the 5G LDPC code, in which we propose a pseudorandom interleaver to rectify the problem.

Slow fading broadcast channels can model a wide range of applications in wireless networks. Due to delay requirements and the unavailability of the channel state information at the transmitter (CSIT), these channels for many applications are non-ergodic. The appropriate measure for designing signals in non-ergodic channels is the outage probability. In this paper, we provide a method to optimize space-time block codes (STBCs) based on the outage probability at moderate SNRs. Multilevel polar coded-modulation is a new class of coded-modulation techniques that benefits from low-complexity decoders and simple rate matching. In this paper, we derive the outage optimality condition for multistage decoding and propose a rule for determining component code rates. We also derive an upper bound on the outage probability of STBCs for designing the set-partitioning-based labeling. Finally, due to the optimality of the outage-minimized STBCs for long codes, we introduce a novel method for the joint optimization of short-to-moderate length polar codes and STBCs.

Space-time block codes (STBCs) have been designed and used to achieve the diversity and multiplexing gains in multiple antenna systems. STBCs have been typically designed based on rank and determinant criteria which can provide good performance at high signal-tonoise ratios (SNRs). Later, STBCs are designed based on mutual information to provide good performance at a specific SNR corresponding to the forward error correction (FEC) code rate. However, once the FEC code and STBC are concatenated, to achieve the best performance, STBC should be designed by considering the structure of the FEC code and the corresponding decoder in addition to the code rate. Polar codes are a new class of FEC codes that benefit from a variety of low complexity decoders and simple rate matching. Polar codes can be efficiently designed for a specific channel and STBC. Therefore, by changing the parameters of a specific STBC and optimizing the polar code for each new STBC, the best match between polar codes and STBCs can be found. Throughout this paper, we introduce a simple method for joint optimization of polar codes and STBCs and show that it can substantially improve the performance of the concatenated scheme.

As one of the multiple-input-multiple-output (MIMO) techniques that work close to capacity, Hochwald and ten Brink proposed to send forward error correction (FEC) coded two-dimensional symbols from multiple antennas in each time slot and decode them using a maximum likelihood decoder. This can be generally considered as the transmission of multidimensional symbols in each time slot and here is referred to as multi-antenna multidimensional constellations (MMCs). Polar codes are a new class of forward error correction codes that benefit from simple rate matching and low complexity decoders, and therefore, facilitate the design of efficient systems. Due to the availability of partial channel state information at the receiver in time varying fading systems, the performance of uncoded MMCs can be improved by employing MMCs designed for partially coherent systems. However, the choice of the constellation in presence of FEC codes is of importance. In this paper, we propose the concatenation of the polar codes and MMC as a high-performance scheme for time varying fading systems. We further study different methods of design of the scheme in partially coherent systems and discuss the choice of the constellation.

Typically, forward error correction codes are designed based on the minimization of the error rate for a given code rate. However, for applications that incorporates hybrid automatic repeat request (HARQ) protocol, the throughput is a more important performance metric than the error rate. Polar codes, a new class of error correction codes with simple rate matching and low complexity decoders, can be optimized efficiently for maximization of the throughput. In this paper, we first introduce a method to design throughput-maximizing polar codes for successive cancellation decoding (SCD). Furthermore, since the optimized codes for SCD are not optimal for SC list decoders (SCLD), we propose a rate matching algorithm to find the best rate for the SCLD decoders while using the polar codes optimized for SCD. The resulting codes provide throughput close to capacity with low decoding complexity when used with Type-I HARQ.

In this paper, we design and compare multilevel polar coding (MLPC) and bit-interleaved polar coded modulation (BIPCM) for uplink sparse code multiple access (SCMA) systems that operate over fast and block fading channels. Both successive cancellation (SC) and successive cancellation list (SCL) decoding algorithms are considered. Simulation results show that, with either decoder, BIPCM performs better than its MLPC counterpart. Also, both BIPCM and MLPC exhibit a performance advantage over LTE turbo-coded and WiMAX LDPC SCMA systems when the SCL technique is used for decoding.

Polar codes, ever since their introduction, have been shown to be very effective for various wireless communication channels. This together with their relatively low implementation complexity has made polar codes an attractive coding scheme for wireless communications. On the other hand, within the realm of non-coherent wireless MIMO communication, Grassmannian signalling has been shown to approach the ergodic capacity of frequency-flat block fading channels. In this paper, a novel methodology for designing polar codes that works effectively with Grassmannian signalling and a novel set partitioning algorithm for Grassmannian constellations are proposed. We compare the error rate performance of our design with that of existing schemes and show that a gain of over 1 dB over the previously known best technique, which is based on turbo codes, is possible, at much lower decoding complexity.

Utilizing multiple antennas at the transmitter and receiver provides higher data rates and better reliability by exploiting spatial diversity. Space-time block codes (STBCs) is a simple approach for using multiple transmit and receive antennas that has been widely employed in standards. The STBCs introduced in the literature use independent two-dimensional constellations, while the performance of orthogonal STBCs may be improved with multidimensional constellations. These constellations are transmitted by combining multiple space-time resources to form a multidimensional signal space. In this paper, we propose a method for finding optimized multidimensional constellations for orthogonal STBCs. Optimization is performed by minimizing a novel bound on the block or symbol error rate. We show that a substantial improvement in the error probability can be achieved with these novel constellations.

We construct polar codes for the specific purpose of incremental redundancy hybrid automatic repeat request (IR-HARQ) schemes. The rate compatibility of our scheme is ensured by both puncturing and extending of the code. A new puncturing algorithm for polar codes is proposed, and we develop an algorithm for finding good extending sequences for polar codes from any arbitrary punctured rate, with the goal of improving the throughput as much as possible. Simulation results for different types of puncturing and extending algorithms are presented. We show how the proposed extending algorithm, when properly operated with a good puncturing algorithm and a well-chosen puncturing rate, yields IR-HARQ coding schemes which can operate within 1 dB of Shannon capacity over a very wide range of signal-to-noise ratios.

The design of an efficient hybrid automatic repeat request (ARQ) scheme based on rate compatible low density parity check (LDPC) codes is considered. It has been shown that extending as well as puncturing of LDPC codes can produce good rate compatible LDPC codes for the additive white Gaussian noise channel. One issue with the traditional LDPC-based hybrid ARQ methods is that the throughput drops off significantly at low signal-to-noise ratios (SNRs). In this paper we introduce a coding scheme which is capable of using puncturing, extending and feedback at the same time to address this issue. Appropriate choice of feedback functions along with optimum combining of received signals for the belief propagation decoder mitigates the throughput drop- off issue at low SNRs, while having a small feedback overhead from the receiver. A powerful mother code is generated via the progressive edge growth algorithm and is used for puncturing and extending in the proposed scheme. Clustering the codewords of the longest codebook is used to decrease the overhead of the feedback connection. Simulation analysis of the throughput shows that our scheme could get as close as 0.5 dB to the Shannon limit while having up to 2 dB gain compared to previous works at low SNRs.

The design of a simplified detector for signal in Middleton's class-A noise is considered. The optimal detector is impractical due to the complexity of the probability density function of the noise. The conventional Gaussian detector (known as the matched filter or the correlator) has near-optimal performance only with relatively high SNR values. Different suboptimal detectors have been proposed to give robust performance with different levels of complexity such as the locally optimal Bayesian detector. In this paper, we propose a unified simple approach to design a near- optimal detector with considerably low complexity by linearly approximating the optimal log-likelihood ratios of the received symbols. The resultant detector has near-optimal performance with low complexity.

The design of detectors for binary signals in symmetric alpha-stable noise is considered. Since the optimal detector is impractically complex, many suboptimal detectors have been proposed such as the Gaussian, soft limiter, myriad and Cauchy detectors. However, no adequate explanation for the difference in performance between these detectors has been proposed. In this paper, we propose a novel framework, based on the optimal decision regions, that is used to justify the performance of many suboptimal detectors and compare them to the optimal one. Moreover, the analysis of the framework provides a novel method to significantly improve the performance of the soft limiter detector by employing an adaptive threshold that is a function of the signal level. As the number of samples per symbol increases, the performance of the proposed adaptive detector approaches the optimal performance at almost no additional complexity over the conventional Gaussian detector.

In this paper we investigate the effectiveness of iterative (turbo) synchronization at improving the link reliability of digital video broadcasting return channel via satellite (DVB-RCS) for different modulation schemes in the presence of strong phase noise. We also propose a multi-user scheme that enables two remote terminals, each using QPSK, to simultaneously use the same frequency band. All additional complexity is located at the central hub receiver, while remote terminals use traditional DVB-RCS transceivers. The new scheme achieves the same system throughput as a single-user with 16APSK, thought of for second generation DVB-RCS (DVB-RCS 2), but with existing DVB-RCS remote terminals, and can be used with future DVB-RCS 2 systems to provide more scheduling flexibility.

The design of near-optimal detectors for binary signals in α-stable interference using two receive antennas is considered. The optimal detector requires more complex computation, whereas the linear (Gaussian) detector is practically simple but suffers from performance degradation with α-stable noise. In this paper, based on the optimal decision regions analysis, we propose to approximate the optimal decision boundaries by using linear segments which results in a novel piecewise detector. The proposed detector has much less complexity over the optimal detector. Also, the analytical evaluation shows near-optimal performance of the piecewise detector. Moreover, simulation results show that the proposed detector has robust performance for different values of α.

The design of detectors for binary signals in interference modeled using the symmetric α-stable distribution is considered. Since the optimal detector is impractically complex, many suboptimal detectors have been proposed such as the linear, soft limiter and Cauchy detectors. However, no adequate explanation for the difference in performance between these detectors has been proposed. In this paper, we propose a novel framework, based on the optimal decision regions, that is used to justify the performance of many suboptimal detectors and compare them to the optimal one. Moreover, the analysis of the framework provides a novel method to significantly improve the performance of the soft limiter detector by employing an adaptive threshold that is a function of the signal level and noise dispersion. As the number of samples per symbol increases, the performance of the proposed adaptive detector approaches the optimal performance at almost no additional complexity over the conventional linear (Gaussian) detector.

The design of Viterbi decoders for signals in noise modeled using the symmetric α-stable distribution is considered. The traditional Viterbi decoder, which has a branch metric optimized for Gaussian noise, performs poorly in symmetric α-stable noise. Since the optimal maximum likelihood branch metric is impractically complex, many suboptimal metrics have been proposed, such as the hard decision, p-norm and absolute (1-norm) metric. A Viterbi decoder that uses the absolute branch metric has better performance and lower complexity, however, its performance degrades when α decreases. In this paper, the effects of the suboptimal metrics on the performance of the Viterbi decoder are analyzed, and a clear justification for the performance of the decoder that uses the Gaussian and absolute metrics is provided. Moreover, this analysis is used to design a low complexity suboptimal branch metric that improves the performance of the Viterbi decoder by about 0.75 to 2 dB compared to the absolute branch metric for different values of α, at almost no additional complexity.

By using rate-compatible (RC) low density parity-check (LDPC) codes with adaptive modulation, we propose an adaptive, discrete-rate multiple-input multiple-output (MIMO) communications system. Given the high spectral efficiency of MIMO and the flexibility of an incremental redundancy (IR) protocol, combined with adaptive coding and modulation (ACM), the designed communications system is capable of achieving high data rates, for a low amount of overhead. A novel ACM power- and bit-allocation protocol is proposed to implement this system. We adapt the existing water-filling algorithm (WFA) to the discrete and finite bit rate constraints inherent in any communications system. This constrained WFA is shown to significantly improve the throughput performance of the communications system, over the case where a regular WFA is used. The results given in this paper show that the combination of IR and ACM with MIMO creates a wireless communications system that can easily adapt to channel fluctuations and provide high-data rates.

Raptor codes and rate-compatible low-density parity-check (RC-LDPC) codes have drawn much attention in recent years as they can approach channel capacity without requiring channel information at the transmitter. Raptor codes have been shown to uniformly approach the binary-input AWGN channel capacity, especially at low SNR's, whereas RC-LDPC codes have the potential to provide higher throughput than Raptor codes at high SNR's. In this paper, we use different message word sizes to compare the throughput of three rateless codes, namely, Raptor codes, rate-compatible irregular repeat-accumulate (RC-IRA) codes, and the rate-compatible quasi-cyclic LDPC (RC/QC-LDPC) codes proposed in the 3GPP2 and 802.20 standards. The comparison is focused on short message word lengths under 16-symbol quadrature amplitude modulation (16-QAM). The simulation results in the AWGN channel show that RC-IRA and RC/QC-LDPC codes outperform Raptor codes at high SNR's. Under frequency flat Rayleigh fading channels, RC-IRA codes outperform RC/QC-LDPC codes at high SNR's and perform slightly worse at low SNR's. We also show that for short block lengths, the throughput of RC-IRA codes is not particularly sensitive to the mother code rate, the belief propagation (BP) algorithm scheduling, the existence of parallel edges during check node combining, and the symbol degree distribution (for fixed average left degree).

In this paper, we study the benefits of using iterative multi-user detectors for co-channel interference suppression in wireless cellular systems. We show that with a single receive antenna a receiver is capable of detecting and cancelling a single in-band interferer using the same modulation and coding scheme as the desired signal. We investigate the benefits of using such an interference canceller at the mobile unit in the downlink scenario of wireless cellular networks. Significant improvements in terms of the average system throughput and outage probability are achieved with iterative interference cancellation. The effectiveness of the interference canceller allows us to consider more aggressive frequency reuse schemes, such as using smaller cluster sizes, and using three-sectored cells where all sectors share the same frequency band.

This paper studies selective relaying schemes based on signal-to-noise-ratio (SNR) to minimize the end-to-end (e2e) bit error rate (BER) in cooperative digital relaying systems using BPSK modulation. In the SNR-based selective relaying, the relay either retransmits or remains silent depending on the SNRs of the source-relay, relay-destination, and source-destination links. Different models assuming the availability of different sets of instantaneous and average SNR information at the relay are studied. For each model, the optimal strategy to minimize the e2e BER is a different threshold rule on the source-relay SNR, if the link SNRs are uncorrelated in time and space. Approximations for the optimal threshold values that minimize the e2e BER and the resulting performance are derived analytically for BPSK modulation. Using the derived threshold the e2e BER can be reduced significantly compared to simple digital relaying. By studying the performance under different models, it is shown that knowledge of the instantaneous source-destination SNR at the relay can be exploited. The gain from this knowledge is higher when the average source-destination SNR is large. However, knowledge of the instantaneous relay-destination SNR at the relay does not change performance significantly.

Mobile users scattered in a microcell and communicating with co-located base station antennas, may cause a severe near-far problem for an uplink space division multiple access (SDMA) system. Also correlations within the multi-input multi-output (MIMO) channel matrix, in such uplink SDMA propagation scenario, can cause significant degradation in system performance. In this paper, we investigate the above problems. We propose to distribute the base station antennas, as multi- antenna arrays, at different sites in the microcell and deploy a correlation reduction algorithm. A significant improvement in the performance of the SDMA system is evident.

Space-division multiple-access (SDMA) is a communication technique that enables a base station to communicate with several mobile users simultaneously. The ability of the base station to spatially separate several users depends on the pairwise cross correlations between the channel matrices of the users (the inter-user correlation). In this paper, we propose an improved null steering downlink multiple-input-multiple-output-orthogonal frequency-division multiplexing (OFDM) system that reduces both the inter-user correlation and the near-far problem resulting in a significant enhancement in system performance. In this system, several base station multiantenna arrays are distributed in a given area. Each array communicates with the base station via optical fiber links, and all transmitter signal processing is performed at the base station. Multiantenna users are spatially separated such that only a subset of the users is served by each tone of the OFDM symbol. The served users are selected based on an algorithm that reduces the inter-user correlations. Distributing the arrays around the users also balances the channel matrix leading to significant reduction in the effect of the near-far problem. The channel matrix of each user is assumed correlated and Ricean distributed. Several data symbols can be spatially multiplexed to each user over each OFDM tone with high reliability and with good total system capacity.

Differential encoding is often used in conjunction with noncoherent demodulation to overcome carrier phase synchronization problems in communication systems employing M-ary phase-shift keying (M-PSK). It is generally acknowledged that differential encoding leads to a degradation in performance over absolutely encoded M-PSK systems with perfect carrier synchronization. In this paper, we show that when differential encoding is combined with convolutional encoding and interleaving, this degradation does not necessarily occur. We propose a novel noncoherent receiver for differentially encoded M-PSK signals that is capable of significantly outperforming optimal coherent receivers for absolutely encoded M-PSK using the same convolutional code. This receiver uses an iterative decoding technique and is based on a multiple differential detector structure to overcome the effect of the carrier phase error. In addition, to better illustrate the benefits of the powerful combination of convolutional encoding, interleaving, and differential encoding, we also present an iterative coherent receiver for differentially encoded M-PSK.

A new technique for iterative decoding of parallel concatenated convolutional (turbo) codes (PCCCs) for the correlated fast Rayleigh fading channel is proposed and evaluated. This technique is based upon the use of a multiple differential detector (MDD) receiver structure which exploits the statistical characteristics of the fading process to overcome the effects of the rapid phase and amplitude variations. Since traditional MDD receivers cannot be used with PCCCs because they do not produce soft output and are not compatible with channel interleaving, a novel MDD receiver structure is derived which overcomes these shortfalls. In addition, with careful use of extrinsic information related to the a posteriori probability distribution function of the transmitted symbols, the receiver is designed in such a fashion as to allow channel estimation to improve with each iteration. Evaluation of the proposed receiver by means of computer simulation has shown dramatic performance improvements in fast Rayleigh fading channels as compared to long constraint-length conventional convolutional codes using both single and traditional MDD receiver structures.