Non-Terrestrial Networks (NTNs) play a critical role in ensuring uninterrupted communication services during emergencies. However, in dense urban environments, complex propagation conditions, such as obstructions from buildings, significantly degrade the link performance between satellites and ground users. To address this issue, this study proposes the integration of Drone Base Stations (DBSs) as the aerial segment and Reconfigurable Intelligent Surfaces (RISs) as the ground segment within satellite communication networks, forming a space-air-ground integrated network (SAGIN). DBSs leverage their flexibility and ability to transmit via line-of-sight (LoS), act as wireless relay stations, effectively enhancing the satellite signal transmission and improving the quality of service (QoS). Meanwhile, RIS significantly enhances the strength of reflected signals by dynamically adjusting the amplitudes and the phases, enabling stable and efficient communication networks. This study employs a deep reinforcement learning (DRL) techniques to optimize the 3D DBS position and RIS phase configurations, based on the dynamic spatial distribution of ground users. Simulation results demonstrate that this approach significantly improves network throughput and communication efficiency, providing essential theoretical foundations and technical references for achieving reliable and efficient SAGIN systems.

To reuse the scarce spectrum efficiently, a large full-duplex cellular network with integrated sensing and communication (ISAC) is studied. Monostatic detection at the base station (BS) is considered. At the BS, we receive two signals: the communication-mode uplink signal to be decoded and the radar-mode signal to be detected. After self-interference cancellation (SIC), inspired by NOMA, successive interference cancellation (SuIC) is a natural strategy at the BS to retrieve both signals. However, the ordering of SuIC, usually based on some measure of channel strength, is not clear as the radar-mode target is unknown. The detection signal suffers a double path-loss making it vulnerable, but the uplink signal to be decoded originates at a user which has much lower power than the BS making it weak as well. Further, the intercell interference from a large network reduces the channel disparity between the two signals. We investigate the impact of both SuIC orders at the BS, i.e., decoding 1stor detecting 1stand highlight the importance of careful order selection. We find the existence of a threshold target distance before which detecting 1stis superior and decoding 2nddoes not suffer much. After this distance, both decoding 1stand detecting 2ndis superior. Similarly, a threshold UE power exists after which the optimum SuIC order changes. We consider imperfections in SIC; this helps highlight the vulnerability of the decoding and detection in the setup.

In this work, we provide a system level analysis of integrated sensing and communication (ISAC) systems, where a setup with a mono-static dual-functional radar communication base station is assumed. We derive the ISAC signal-to-noise ratio (SNR) equation that relates communication and radar SNRs for different distances. We also derive the ISAC range equation, which can be used for sensing-assisted beamforming applications. Specifically, we show that increasing the frequency and bandwidth is more favorable to the radar application in terms of relative SNR and range while increasing the transmit power is more favorable to communications. Numerical examples reveal that if the range for communication and radar is desired to be in the same order, the ISAC system should operate in mmWave or sub-THz bands, whereas sub-6 GHz allows scenarios where the communication range is of orders of magnitude higher than that of radar.

Security is an issue in non-orthogonal multiple access (NOMA) and partial-NOMA because a user may decode the message of its paired-user with which it shares a resource element (RE). Three scenarios are studied where, of the paired-users, the eavesdropper is: 1) an actively malicious strong-user, 2) a passive strong-user, 3) an actively malicious weak-user. We define the event of secure-communication in each scenario and derive the corresponding secrecy probabilities for partial-NOMA and NOMA. Our results highlight that with careful selection of the RE’s overlap α, partial-NOMA can significantly outperform NOMA in terms of secrecy probability. Further, careless selection of α can cause partial-NOMA to perform worse than NOMA. We show the non-trivial impact of incorporating the impact of intercell interference on secrecy. Our results shed light on parameter-selection if knowledge of the eavesdropper type is available highlighting that security can be improved without traditional techniques such as jamming that increase power consumption and interference. While NOMA decoding uses successive-interference-cancellation (SIC), partial-NOMA decoding employs receive-filtering followed by flexible-SIC (FSIC). We show that not employing receive-filtering or using SIC instead of FSIC can have a drastic negative impact on secrecy, highlighting the role of the partial-NOMA decoding approach in enhancing secure-communication.

A large network employing integrated sensing and communication (ISAC) where a single transmit signal by the base station serves both the radar and communication modes is studied. The radar-mode uses bistatic detection at a passive radar. Radar-mode performance, in general, is significantly more vulnerable than the communication-mode due to the double path loss in the signal component while interferers have direct links. To combat this, we propose a novel dynamic transmission strategy (DTS) where the quantity of radar-mode detection is traded for quality. We analyze the performance both the radar and communication modes with and without DTS and benchmark it with a traditional radar-only network. Our results highlight that with DTS we are able to significantly improve quality of radar detection at the cost of quantity. Further, DTS causes some performance deterioration to the communication-mode due to increased interference; however, the radar-mode gains attained are much higher. We show that dense deployment of low-cost passive radars offers superior detection for farther off targets, particularly compared to a radar-only network. With DTS, ISAC can further improve radar gains from its traditional counterpart.

Non-orthogonal multiple access (NOMA) allows users sharing a resource-block to efficiently reuse spectrum and improve cell sum rate$\mathcal {R}_{\mathrm{ tot}}$at the expense of increased interference. Orthogonal multiple access (OMA), on the other hand, guarantees higher coverage. We introduce partial-NOMA in a large two-user downlink network to provide both throughput and reliability. The associated partial overlap controls interference while still offering spectrum reuse. The nature of the partial overlap also allows us to employ receive-filtering to further suppress interference. For signal decoding in our partial-NOMA setup, we propose a new technique called flexible successive interference cancellation (FSIC) decoding. We plot the rate region abstraction and compare with OMA and NOMA. We formulate a problem to maximize$\mathcal {R}_{\mathrm{ tot}}$constrained to a minimum throughput requirement for each user and propose an algorithm to find a feasible resource allocation efficiently. Our results show that partial-NOMA allows greater flexibility in terms of performance. Partial-NOMA can also serve users that NOMA cannot. We also show that with appropriate parameter selection and resource allocation, partial-NOMA can outperform NOMA.

A network model is considered, where Poisson distributed base stations transmit to N power-domain nonorthogonal multiple access (NOMA) users (TIEs) each that employ successive interference cancellation (SIC) for decoding. We propose three models for the clustering of NOMA TIEs and consider two different ordering techniques for the NOMA TIEs: mean signal power-based and instantaneous signal-to-intercell-interference-and-noise-ratio-based. For each technique, we present a signal-to-interference-and-noise ratio analysis for the coverage of the typical TIE. We plot the rate region for the two-user case and show that neither ordering technique is consistently superior to the other. We propose two efficient algorithms for finding a feasible resource allocation that maximize the cell sum rate Rtot, for general N, constrained to: 1) a minimum throughput T for each TIE, 2) identical throughput for all TIEs. We show the existence of: 1) an optimum N that maximizes the constrained Rtotgiven a set of network parameters and 2) a critical SIC level necessary for NOMA to outperform orthogonal multiple access. The results highlight the importance in choosing the network parameters N, the constraints, and the ordering technique to balance the Rtotand fairness requirements. We also show that interference-aware TIE clustering can significantly improve performance.

-Non-orthogonal multiple access (NOMA) is a spectrum reutilization technique that superposes messages in the power domain allowing multiple users to be served in the same time-frequency resource block. Successive interference cancellation (SIC) techniques are used for decoding NOMA. A network model is considered where Poisson distributed base stations transmit toNNOMA users each. We present a signal-to-interference-and-noise-ratio analysis for the coverage of the typical user. Due to SIC, coverage implies the ability to decode the messages of all weaker users in the SIC chain. An efficient algorithm for finding a feasible resource allocation that maximizes the cell sum rate ℛtotsubject to a minimum rate constraintTon the individual users is provided for generalN. We show the existence of an optimumNthat maximizes ℛtotgiven a set of network parameters. We also show that NOMA outperforms orthogonal multiple access if the residual intracell interference is below a certain level. The results highlight the importance in choosing network parametersNandTto balance ℛtotand fairness.

Full-duplex (FD) communication is optimistically promoted to double the spectral efficiency if sufficient self-interference cancellation (SIC) is achieved. However, this is not true when deploying FD-communication in a large-scale setup due to the induced mutual interference. Therefore, a large-scale study is necessary to draw legitimate conclusions about gains associated with FD-communication. This paper studies the FD operation for underlay device-to-device (D2D) communication sharing the uplink resources in cellular networks. We propose a disjoint fine-tuned selection criterion for the D2D and FD modes of operation. Then, we develop a tractable analytical paradigm, based on stochastic geometry, to calculate the outage probability and rate for cellular and D2D users. The results reveal that even in the case of perfect SIC, due to the increased interference injected to the network by FD-D2D communication, having all proximity UEs transmit in FD-D2D is not beneficial for the network. However, if the system parameters are carefully tuned, non-trivial network spectral-efficiency gains (64% shown) can be harvested. We also investigate the effects of imperfect SIC and D2D-link distance distribution on the harvested FD gains.

Due to their ability to provide high data rates, multiple-input multiple-output (MIMO) systems have become increasingly popular. Decoding of these systems with acceptable error performance is computationally very demanding. In this paper, we employ the Sequential Decoder using the Fano Algorithm for large MIMO systems. A parameter called the bias is varied to attain different performance-complexity trade-offs. Low values of the bias result in excellent performance but at the expense of high complexity and vice versa for higher bias values. Numerical results are done that show moderate bias values result in a decent performance-complexity trade-off. We also attempt to bound the error by bounding the bias, using the minimum distance of a lattice. The variations in complexity with SNR have an interesting trend that shows room for considerable improvement. Our work is compared against linear decoders (LDs) aided with Element-based Lattice Reduction (ELR) and Complex Lenstra-Lenstra-Lovasz (CLLL) reduction.