Faster-than-Nyquist (FTN) signaling is a classic signaling scheme for improved spectral efficiency compared to the conventional Nyquist signaling at the cost of increased complexity. In this paper, we investigate the FTN transmission with Nyquist receiver sampling (a.k.a. FTN-NR transmission), in order to simplify the receiver processing. Particularly, we derive a closed-form expression on the achievable rates of the FTN-NR transmission with arbitrary shaping pulses and Gaussian constellations. Our analysis reveals that this achievable rate relates closely to both the folded spectrum and folded squared spectrum of the pulse, which incorporate the folding effect of the signal spectrum due to the receiver sampling. Furthermore, we prove that the achievable rate of FTN-NR transmission is no better than that of Nyquist signaling despite the pulse shapes, when Gaussian constellation is applied. However, we then provide a numerical study on the rate with finite-alphabet constellations, and verify that FTN-NR transmission can outperform Nyquist signaling in terms of the achievable rate, especially when the modulation order is low. Our numerical results confirm our conclusions and report a noticeable achievable rate improvement of the FTN-NR transmission compared to Nyquist signaling under QPSK signaling.

Faster-than-Nyquist (FTN) signaling is a non-orthogonal transmission technique offering a promising solution for future generations of communications. This paper studies the capacity of FTN signaling in multiple-input multiple-output (MIMO) channels for high acceleration factors. In our previous study [1], we found the capacity for MIMO FTN channels if the acceleration factor is larger than a certain threshold, which depends on the bandwidth of the pulse shape used. In this paper we extend the capacity analysis to acceleration factors smaller than this mentioned threshold. In addition to capacity, we conduct instantaneous-to-average power ratio (IAPR) analysis and simulation for MIMO FTN for varying acceleration factors for both Gaussian and QPSK symbol sets. Our analysis reveals important insights about transmission power and received signal-to-noise ratio (SNR) variation in FTN. As the acceleration factor approaches 0, if the transmission power is fixed, the received SNR diminishes, or if the received SNR is fixed, IAPR at the transmitter explodes.

Faster-than-Nyquist signaling serves as a promising solution for improving spectral efficiency in future generations of communications. However, its nature of fast acceleration brings highly overlapped pulses that lead to worse peak-to-average power ratio (PAPR) performance. In this paper, we investigate the PAPR behavior of MIMO FTN using Gaussian symbols under optimal power allocation for two power constraints: fixed transmit power and fixed received signal-to-noise-ratio (SNR). Our findings reveal that PAPR is mainly determined by the acceleration factor and the power constraint, but power allocation optimization does not change the PAPR behavior for Gaussian signaling.

The pursuit of higher data rates and efficient spectrum utilization in modern communication technologies necessitates novel solutions. In order to provide insights into improving spectral efficiency and reducing latency, this study investigates the maximum channel coding rate (MCCR) of finite block length (FBL) multiple-input multiple-output faster-than-Nyquist (FTN) channels. By optimizing power allocation, we derive the system's MCCR expression. Simulation results are compared with the existing literature to reveal the benefits of FTN in FBL transmission.

Rate-splitting multiple access (RSMA) has emerged as a powerful transmission scheme to mitigate interference in next generation communication systems. In this paper, we investigate precoding with RSMA for a multiple antenna interference channel based on deep reinforcement learning. Specifically, each transmitter has to effectively optimize precoders and allocate transmit power to common and private streams via multiple decision-makers with high dimensional continuous action space. In order to solve this problem, we employ a multi-agent deep deterministic policy gradient (MA-DDPG) framework. In this framework, decentralized agents have partial observability and learn a centralized critic with a multi-dimensional continuous policy. Simulation results show that the proposed rate-splitting method achieves the information theoretical sum-rate upper bound for the single antenna case. It also has a performance very close to the upper bound for the multiple antenna case and outperforms MA-DDPG with no rate-splitting, maximal ratio transmission, zero-forcing and leakage-based precoding methods in both cases.

Faster-than-Nyquist (FTN) signaling is a non-orthogonal transmission technique, which brings in intentional inter-symbol interference. This way it can significantly enhance spectral efficiency for practical pulse shapes such as the root raised cosine pulses. This paper proposes an achievable rate region for the multiple antenna (MIMO) asynchronous multiple access channel (aMAC) with FTN signaling. The scheme applies waterfilling in the spatial domain and precoding in time. Water-filling in space provides better power allocation and precoding helps mitigate inter-symbol interference due to asynchronous transmission and FTN. The results show that the gains due to asynchronous transmission and FTN are more emphasized in MIMO aMAC than in single antenna aMAC. Moreover, FTN improves single-user rates, and asynchronous transmission improves the sum-rate, due to better inter-user interference management.

Faster-than-Nyquist (FTN) signaling is a non-orthogonal transmission technique, which has the potential to provide significant spectral efficiency improvement. This paper studies the capacity of FTN signaling for both frequency flat and for frequency selective (FS) multiple-input multiple-output (MIMO) channels. As FTN is another reason of frequency selectivity, we find that precoding in time (or equivalently spectrum shaping in frequency) and waterfilling in spatial domain is capacity achieving for frequency flat MIMO channels with FTN. Meanwhile, waterfilling in both spatial domain and spectrum domain, followed by spectrum shaping, is capacity achieving for FS MIMO channels with FTN.

Data collection with unmanned aerial vehicles (UAVs) is a novel technology with many practical applications. In this paper, UAV aided data collection in sensor networks for time-critical applications is considered. Maximum age of information (AoI) is used as the performance metric, where both communication time and flight time contribute to AoI. Given that sensors form groups of two, the UAV aims to visit each line segment formed by the two sensors in each group once and to return to the data center. To minimize the maximum AoI, two trajectory design algorithms are proposed. In both algorithms, the UAV communicates with the sensors in each group through a multiple access channel. In the first algorithm, the UAV hovers on the communication time optimal point on the line segment. In the second algorithm, it hovers on the path-length optimal point. The algorithms are compared with time sharing schemes, and also with the case when all sensors are visited individually. The results reveal that multiple access transmission is optimal, when sensors are not too far apart and packet lengths are long, whereas path-length optimal trajectory is better when packet lengths are short.

Wireless communication with unmanned aerial vehicles (UAVs) will become an integral part of future wireless communication systems. In UAVs real-time data transfer is very critical because UAVs need to be controlled from the ground and their data is also transferred in real time. However, aircraft antennas are prone to airframe shadowing. Aircraft surfaces, on which antennas are placed, obscure the main line-of-sight path. In addition, losses used in link budget analyses show great variability in real time. Therefore, observed end-to-end channels, including all impairments, are in general quite different from theoretical calculations in practice. In this work an end-to-end channel link budget, including all effects, is modelled by applying machine learning methods on measured data obtained during past flights. It is observed that ensemble bagged trees (EBT) and exponential Gaussian process regression (GPR) provide the two best results. Pre-processing data and utilizing raw data are also compared. EBT and exponential GPR can predict the amount of end-to-end losses with 7.49% and 8.07% sensitivity respectively using processed data. When raw data is used as input to the EBT method, it can predict the amount of end-to-end loss with a sensitivity of 2.79%, while a theoretical prediction error is 21.9%.

This paper considers precoding for multi-group multicasting with a common message. The multiple antenna base station communicates with K clusters, each with L users. There is a common message destined to all users and a private multicast message for each cluster. We study the weighted sum rate (WSR) maximization problem for two different schemes: 1) the base station transmits the superposition of common and multicast messages and 2) the base station concatenates the multicast message vector with the common message. We also formulate a second problem, weighted minimum mean square error (WMMSE) minimization, and prove that WSR maximization and WMMSE minimization are equivalent at the optimal solution. Inspired by the WMMSE problem, we suggest a suboptimal algorithm, based on alternating optimization. We apply this algorithm to the two transmission schemes and understand that there is a fundamental difference between the two. We compare the results with maximal ratio transmission (MRT) and zero-forcing (ZF) precoding and investigate the effects of the number of base station antennas, the number of groups, and the number of users in a group. Finally, we study imperfect successive interference cancellation (SIC) at the receivers and show that the first transmission scheme is more robust.

In this paper, a downlink wireless communication channel is considered. The base station (BS) has common data for all users, unicast data for a set of intended users, and transmits the superposition of these messages. This setting neither falls into the non-orthogonal multiple access (NOMA) nor into the multi-group multicasting literatures. In NOMA systems, the BS has unicast data for all users, and multiple users share the same resources. In multi-group multicasting, there are non-overlapping groups, each demanding a different multicast message. This paper studies precoder design to achieve maximum weighted sum rate (WSR). It is first shown that the precoders designed for WSR maximization and weighted minimum mean square error (WMMSE) minimization are equivalent. Second, an iterative low complexity algorithm (named WMMSE), based on WMMSE transmit precoders and receivers, is proposed. Another low-complexity precoder, the phase aligned zero forcing (PAZF) precoder, is also introduced. The results show that both algorithms converge fast. The WMMSE algorithm outperforms both PAZF and the zero-forcing (ZF) precoder for all signal-to-noise ratio ranges. It offers better interference management and high coherent combining gains for common data while PAZF finds the optimal phase rotation on the ZF precoder, and increases coherent combining gains.

Micro-Doppler signatures can be used not only to recognize different targets, such as vehicles, helicopters, animals, and people, but also to classify varying activities, e.g., walking, running, creeping, and crawling. For this purpose, a plethora of features have been proposed in the literature; however, dozens of features are not required to achieve high classification performance. The topic of feature selection has been under addressed in micro-Doppler studies. Moreover, the optimal feature set is not static but varies under different operational conditions, such as signal-to-noise ratio (SNR), dwell time, and aspect angle. The mutual information of features relative to the classification problem at hand offers a measure for assessing the efficacy of features and thus sets a unique framework for feature selection. In this paper, information-theoretic (IT) feature selection techniques are used to identify essential features and minimize the total number of required features, while maximizing classification performance. It is seen that, although some features are consistently preferred, others are never selected. Results show that for SNRs over 10 dB and at least 1 s of data, this approach yields 96% correct classification when the target moves along the radar line-of-sight and over 65% correct classification for tangential motion.

In this paper, we investigate an efficient scheme for data multicasting in narrowband public safety radio systems. The proposed scheme uses fountain encoding, in order to avoid feedback messages for each individual packet. We first propose a multistage estimation scheme that is based on slotted random access and that does not require any prior knowledge of number of users. The rest of the proposed scheme consists of iterative transmission and feedback/estimation phases. In feedback phases, the base station estimates the number of users that did not decode the data file yet, and determines the number of additional fountain encoded packets required. This phase does not require any channel state information. The proposed scheme lasts until all the users in the group decode the message. We show that the proposed estimation scheme is accurate and computationally efficient. The overall multicast scheme performs very close to an optimistic lower bound, which makes it a promising multicast approach in public safety radio systems such as APCO P25.

As a new achievability scheme, successive refinement coding based compress-and-forward relaying (sCF) is proposed for both discrete memoryless and Gaussian broadcast relay channels (BRC) with one source, two destinations and a dedicated relay. A new outer bound is also provided on the capacity region of physically degraded BRC. Then, the achievability scheme is extended to K-destinations. For the Gaussian BRC, it is shown that the sCF rate region outperforms other CF schemes in the literature. Finally, it is proved that the new achievable scheme is within a half bit of the outer bound on the capacity region for a subset of channel gains.

In this paper, we study the impact of different channel output feedback architectures on the capacity of the two-user interference channel. For a two-user interference channel, a feedback link can exist between receivers and transmitters in nine canonical architectures (see Fig. 3 ), ranging from only one feedback link to four feedback links. We derive the exact capacity region for the symmetric deterministic interference channel and the constant-gap capacity region for the symmetric Gaussian interference channel for all of the nine architectures. We show that for a linear deterministic symmetric interference channel, in the weak interference regime, all models of feedback, except the one, which has only one of the receivers feeding back to its own transmitter, have the identical capacity region. When only one of the receivers feeds back to its own transmitter, the capacity region is a strict subset of the capacity region of the rest of the feedback models in the weak interference regime. However, the sum-capacity of all feedback models is identical in the weak interference regime. Moreover, in the strong interference regime, all models of feedback with at least one of the receivers feeding back to its own transmitter have the identical sum-capacity. For the Gaussian interference channel, the results of the linear deterministic model follow, where capacity is replaced with approximate capacity.

In this work, the broadcast relay channel (BRC) with one source, two destinations and a dedicated relay node is studied for both discrete memoryless and Gaussian channels. Unlike all the existing achievability schemes, which use decode-and-forward (DF) relaying for the BRC, the new achievability schemes are based on compress-and-forward (CF). Three different compression methods are proposed: naive, joint and multiple description coding based. In naive CF (nCF) and joint CF (jCF), the relay forms a single representation, conveying its observation to both destinations at a single quality level. On the other hand, in multiple description coding based CF (mdCF), the relay utilizes multiple description coding and forms two representations, which allows for the two destinations to receive the relay observation at different quality levels. Through Gaussian examples, it is observed that mdCF enlarges nCF and jCF rate regions. Moreover, mdCF is the only scheme, which can achieve both of the single user CF rates achievable in the constituent single user relay channels.

In this paper the broadcast relay channel (BRC) is studied. In the BRC model, the source communicates with two destinations with the help of a single relay. The minimum common outage probability for four different transmission protocols, direct transmission (DT), multihop (MH), path selection (PS) and link combination with path selection (LCPS) is investigated under long-term power constraint for constant rate transmission. In addition, the ε-outage rate region for a fixed common outage probability is computed. Based on the cut-set bound (CSB), a lower bound on the minimum common outage probability and an upper bound on the ε-outage rate region are also found. Numerical results suggest that enforcing the relay to help both destinations simultaneously is limiting. The dominant factor in the gains obtained with respect to DT is due to path selection and link combination is not necessary when the relay is close to the source.

In this work, a four-terminal complex Gaussian network composed of a source, a destination, an eavesdropper, and a jammer relay is studied under two different set of assumptions: 1) The jammer relay does not hear the source transmission, and 2) The jammer relay is causally given the source message. In both cases, the jammer relay assists the eavesdropper and aims to decrease the achievable secrecy rates. The source, on the other hand, aims to increase it. To help the eavesdropper, the jammer relay can use pure relaying and/or send interference. Each of the problems is formulated as a two-player, noncooperative, zero-sum continuous game. Assuming Gaussian strategies at the source and the jammer relay in the first problem, the Nash equilibrium is found and shown to be achieved with mixed strategies in general. The optimal cumulative distribution functions (cdfs) for the source and the jammer relay that achieve the value of the game, which is the Nash equilibrium secrecy rate, are found. For the second problem, the Nash equilibrium solution is found and the results are compared to the case when the jammer relay is not informed about the source message.

In this paper the fading multiple antenna (MIMO) wire-tap channel is investigated under short term power constraints. The secret diversity gain and the secret multiplexing gain are defined. Using these definitions, the secret diversity-multiplexing tradeoff (DMT) is calculated analytically for no transmitter side channel state information (CSI) and for full CSI. When there is no CSI at the transmitter, under the assumption of Gaussian codebooks, it is shown that the eavesdropper steals both transmitter and receiver antennas, and the secret DMT depends on the remaining degrees of freedom. When CSI is available at the transmitter (CSIT), the eavesdropper steals only transmitter antennas. This dependence on the availability of CSI is unlike the DMT results without secrecy constraints, where the DMT remains the same for no CSI and full CSI at the transmitter under short term power constraints. A zero-forcing type scheme is shown to achieve the secret DMT when CSIT is available.

In a two-user interference channel, there are four possible feedback paths - two from each receiver to the transmitters. This leads to 16 possible models of feedback. In this paper, we derive the sum capacity of two user deterministic interference channel for all sixteen cases. We find that whenever any of the direct link feedback from a receiver to its own transmitter is present, the sum-capacity is the same as when all four feedback links are present. Further when no direct link feedback is present, the sum capacity with one cross-link feedback and two cross-links of feedback is the same. This sum-capacity is the same as the sum-capacity when there is no feedback except in the regime of interference in which both interfering links are weaker than both the direct-links in which case the sum-capacity is the same as sum-capacity of the feedback model with all four feedback links.

A four terminal Gaussian network composed of a source, a destination, an eavesdropper and a jammer relay is investigated when the jammer relay is causally given the source message. The source aims to increase the achievable secrecy rates, whereas the jammer relay aims to decrease it. To help the eavesdropper and to decrease achievable perfect secrecy rates, the jammer relay can use pure relaying and/or send interference to assist eavesdropping. The problem is formulated as a zero-sum game and the saddle point solutions are found. The results are compared to the case when the jammer relay is not informed about the source message.

In this paper, we investigate the diversity-multiplexing tradeoff (DMT) of the multiple-antenna (MIMO) static half-duplex relay channel. A general expression is derived for the DMT upper bound, which can be achieved by a compress-and-forward protocol at the relay, under certain assumptions. The DMT expression is given as the solution of a minimization problem in general, and an explicit expression is found when the relay channel is symmetric in terms of number of antennas, i.e., the source and the destination have n antennas each, and the relay has m antennas. It is observed that the static half-duplex DMT matches the full-duplex DMT when the relay has a single antenna, and is strictly below the full-duplex DMT when the relay has multiple antennas. Besides, the derivation of the upper bound involves a new asymptotic study of spherical integrals (that is, integrals with respect to the Haar measure on the unitary groupU(n)), which is a topic of mathematical interest in itself.

In this work, we investigate the diversity-multiplexing tradeoff (DMT) of the multiple-antenna (MIMO) static half-duplex relay channel. The relay channel is assumed to be symmetric in terms of number of antennas, i.e. the source and the destination have n antennas each, and the relay has m antennas. A general expression is derived for the DMT upper bound, which can be achieved by a compress-and-forward protocol at the relay, under certain assumptions. It is observed that the static half-duplex DMT matches the full-duplex DMT when the relay has a single antenna, and is strictly below the full-duplex DMT when the relay has multiple antennas.

We study the multiple antenna half-duplex relay channel from the diversity-multiplexing tradeoff (DMT) perspective. We find performance upper bounds and show that compress-and-forward (CF) protocol achieves the upper bound. We argue that although it is hard to find the exact DMT expressions for decode-and-forward (DF) type protocols, they would be suboptimal in the multiple antenna case. We also study the multiple-access relay channel (MARC), and evaluate how CF works in this system. Our results show that CF is a robust strategy, which performs well in different relay networks and multiple antenna scenarios.

We consider a general multiple-antenna network with multiple sources, multiple destinations, and multiple relays in terms of the diversity–multiplexing tradeoff (DMT). We examine several subcases of this most general problem taking into account the processing capability of the relays (half-duplex or full-duplex), and the network geometry (clustered or nonclustered). We first study the multiple-antenna relay channel with a full-duplex relay to understand the effect of increased degrees of freedom in the direct link. We find DMT upper bounds and investigate the achievable performance of decode-and-forward (DF), and compress-and-forward (CF) protocols. Our results suggest that while DF is DMT optimal when all terminals have one antenna each, it may not maintain its good performance when the degrees of freedom in the direct link are increased, whereas CF continues to perform optimally. We also study the multiple-antenna relay channel with a half-duplex relay. We show that the half-duplex DMT behavior can significantly be different from the full-duplex case. We find that CF is DMT optimal for half-duplex relaying as well, and is the first protocol known to achieve the half-duplex relay DMT. We next study the multiple-access relay channel (MARC) DMT. Finally, we investigate a system with a single source–destination pair and multiple relays, each node with a single antenna, and show that even under the ideal assumption of full-duplex relays and a clustered network, this virtual multiple-input multiple-output (MIMO) system can never fully mimic a real MIMO DMT. For cooperative systems with multiple sources and multiple destinations the same limitation remains in effect.

We study the diversity-multiplexing tradeoff (DMT) for the full-duplex relay channel when the source and the destination have multiple antennas, and the relay has 1 or more. We find DMT upper bounds and investigate the achievable performance of decode-and-forward (DF), partial decode-and-forward (PDF), and compress-and-forward (CF) protocols. We study the effect of increased degrees of freedom in the direct link and the source-relay channel when multiple antennas are introduced. Our results suggest that while DF is DMT optimal when all terminals have one antenna each, it cannot maintain its good performance when the degrees of freedom in the direct link is increased. CF proves to be a more robust strategy, which works well in multi-antenna scenarios studied in this paper. We also extend our results for clustered relay networks to find DMT upper bounds and achievable performances

We consider a wireless system consisting of one source, one destination and M relays. Assuming path loss and Rayleigh fading, we use the cutset upper bound to show that no matter where the relays are located, the maximum diversity one can obtain is M+1. However, one can achieve a higher diversity gain, namely /spl lfloor/(M+2/2)/sup 2//spl rfloor/, if /spl lfloor/M/2/spl rfloor/ of the relays are clustered with the source and /spl lceil/M/2/spl rceil/ with the destination. This result utilizes the observation that if two wireless nodes are very close, Rayleigh assumption breaks and the proper channel model is additive white Gaussian noise (AWGN). Hence to realize a virtual multiinput multioutput (MIMO) system, clustering is essential.

We examine a network consisting of one source, one destination and two amplifying and forwarding relays and consider a scenario in which destination and relays can have various processing limitations. For all possible diversity combining schemes at the relays and at the destination, we find diversity order results analytically and confirm our findings through numerical calculations of bit error rate (BER) versus signal-to-noise-ratio (SNR) curves. We compare our results with direct transmission, well known transmit diversity methods and traditional multihop transmission and conclude that diversity reception in multihop networks provides the lowest error rate.