Approximate message passing (AMP) iterative detection is recognized as a reliable and practical approach for multiple-input multiple-output (MIMO) systems. However, existing AMP detection algorithms face a critical challenge: high computational complexity due to redundant iterations, making them impractical for the coming 6G networks with increased data throughput demands. This paper addresses this challenge by investigating the mutual information (MI) update flow in AMP iterative MIMO detection and introducing a precise MI computation mechanism based on the error function, referred to as the EFA mechanism. Leveraging the EFA mechanism, we propose a convergence-based termination (CT) scheme to accurately track the convergent iteration number and eliminate redundant iterations in AMP iterative detection. Numerical results demonstrate that the MI flow calculated using the EFA mechanism is consistent with the convergence behavior of AMP iterative MIMO detection across different iterations and signal-to-noise ratios (SNRs). Specifically, the EFA mechanism can precisely identify the convergent iteration number and corresponding SNR. Additionally, the CT scheme achieves up to a 80% reduction in complexity compared to original AMP detection, while maintaining the expected BER performance.

To meet the growing demand for communication capacity and address the scarcity of wireless spectrum resources, we propose a novel orthogonal time frequency space (OTFS) channel estimation scheme enhanced by visual environment semantics. This approach establishes a theoretical foundation for semantic-assisted channel estimation by modeling the potential relationship between the wireless communication channel and its surrounding environment. Leveraging a computer vision-based adaptive environment semantic sensing framework, the system extracts and processes environment features to infer channel characteristics. To tackle the challenge of capturing small-scale fading solely through visual environment semantics, we design two new pilot structures and the corresponding channel estimation methods. These are tailored to maximize the utility of information derived from the environment while minimizing pilot overhead. The simulation results demonstrate that the proposed scheme outperforms the conventional channel estimation method in terms of spectral efficiency and robustness in high-mobility and low-SNR scenarios with fewer pilot symbols.

Frequency shift keying (FSK) modulation can avoid the direct path interference problem in backscatter communication (BackCom). However, due to the limited number of reflection impedances of the tag, unwanted high-order harmonics are introduced, thereby degrading bit error rate (BER) performance. In this work, we investigate the harmonic elimination strategy for FSK-based BackCom. In particular, we first propose a novel multi-stage incident signal and the corresponding reflection strategy, which allows the tag to modulate the incident signal through absolute value operations, effectively suppressing harmonic generation. Then, we develop a USRP-based platform to experimentally verify the feasibility of our harmonic elimination strategy. Finally, the results show that our design can achieve a 12 dB attenuation in the third harmonic and up to 34 dB attenuation in high-order harmonics compared to conventional FSK-based BackCom without harmonic elimination, which consequently leads to improved BER performance.

Backscatter communication and harvest-then-transmit (HTT) communication are regarded as promising technologies for enabling green Internet of Things (IoT). The current works on the joint use of backscatter communication and HTT are limited in single cell scenarios with the fixed backscatter-then-HTT transmission structure. In this work, we propose a transmission scheme with flexible mode selection for the hybrid backscatter-HTT multi-cell system to achieve much improved communication performance, and then study the joint design for such a system. Specifically, by utilizing multi-antenna technology and enabling the flexible mode selecting between backscatter and HTT, a novel transmission scheme is developed. With the aim to maximize the sum rate of the considered system, we formulate a joint optimization problem for the base station transmission beamforming (TB), the transmission mode (TM), and the transmit power (TP) of the hybrid backscatter-HTT devices. To address the formulated non-convex problem, we propose a block coordinate descent-based algorithm, namely J3TO, to jointly optimize TB, TM, and TP, by decoupling the original problem into three sub-problems. Therein, the weighted minimum mean square error approach, matching theory, and the fractional programming technique are leveraged to deal with the sub-problems efficiently. Simulation results show that the proposed algorithm flexibly integrates the merits of backscatter and HTT technologies, achieving superior performance across various scenarios, compared with the benchmark schemes, e.g., backscatter-only SDMA, HTT-only SDMA, and backscatter-HTT TDMA.

Recently, reconfigurable intelligent surfaces (RISs) are gaining increasing attention in communication systems due to their ability to adapt themself according to the wireless environment. Therefore, the communication systems with massive RIS deployments are able to extend high-quality coverage ubiquitously. This is especially beneficial for Internet of Things (IoT) systems as the IoT devices can be located in hard-to-reach area. On the other hand, current methods to analyze and optimize the performance of communication systems with multiple RISs deployment are ad hoc, which depends on the specific system configurations. There lacks a unified theoretical framework that provides general analytical treatment for both passive and active RIS-assisting systems, possibly having multiple concatenated reflections via RISs, which is typical in IoT communication scenarios. Thus, we investigate general uplink RIS-assisted multi-user multiple-input multiple-output (MU-MIMO) communication systems under general Rician fading channels, where the number of cascaded RIS panels are arbitrary and the RIS elements can be active or passive. By utilizing the linearization trick and the operator-valued free probability theory, a unified analytic expression of the ergodic sum rate for the considered MU-MIMO systems is derived. Then, we further propose a low-complexity optimization approach to design the RISs’ phase shifts, thus enhancing the ergodic sum rate. Numerical results verify the accuracy of the analytical results for RIS-assisted systems. In addition, the convergence and effectiveness of the proposed optimization algorithm are demonstrated.

Among the key enabling 6G techniques, multiple-input multiple-output (MIMO) and non-orthogonal multiple-access (NOMA) play an important role in enhancing the spectral efficiency of the wireless communication systems. To further extend the coverage and the capacity, the simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) has recently emerged out as a cost-effective technology. To exploit the benefit of STAR-RIS in the MIMO-NOMA systems, in this paper, we investigate the analysis and optimization of the downlink dual-user MIMO-NOMA systems assisted by multiple STAR-RISs under the generalized singular value decomposition (GSVD) precoding scheme, in which the channel is assumed to be Rician faded with the Weichselberger’s correlation structure. To analyze the asymptotic information rate of the users, we apply the operator-valued free probability theory to obtain the Cauchy transform of the generalized singular values (GSVs) of the MIMO-NOMA channel matrices, which can be used to obtain the information rate by Riemann integral. Then, considering the special case when the channels between the BS and the STAR-RISs are deterministic, we obtain the closed-form expression for the asymptotic information rates of the users. Furthermore, a projected gradient ascent method (PGAM) is proposed with the derived closed-form expression to design the STAR-RISs thereby maximizing the sum rate based on the statistical channel state information. The numerical results show the accuracy of the asymptotic expression compared to the Monte Carlo simulations and the superiority of the proposed PGAM algorithm.

Orthogonal Frequency Division Multiplexing (OFDM) underpins modern wireless communication due to its resilience against multi-path fading and computationally efficient implementations. However, on one hand, in scenarios with time-frequency doubly selective fading channels, OFDM systems face significant challenges, as channel variation induces inter-carrier interference (ICI) that disrupts subcarrier orthogonality. On the other hand, the limited length of the cyclic prefix (CP), often constrained to a fraction of the symbol duration, may be insufficient to fully mitigate inter-symbol interference (ISI) in scenarios with large time spreads. Extending CP length would reduce spectral efficiency and increase latency, making it incompatible with the demands of high-efficiency, low-latency systems. In this paper, we propose an autoencoder based OFDM architecture integrating adaptive pulse shaping with an equalization neural network (PS-EQNet) that jointly addresses ISI caused by insufficient CP and ICI due to channel dynamics through learnable time-frequency filters. Additionally, we introduce a detection network tailored for simplified channels, which reduces computational complexity compared to existing schemes while maintaining robust performance. Simulation results confirm that the proposed PS-EQNet OFDM system significantly relaxes CP requirements, enhances spectral efficiency (SE), and achieves reliable bit error rate (BER) performance in time-frequency selective channels, establishing a flexible trade-off among SE, BER, and computational complexity.

To meet the capacity requirements of future communications systems, multiple-input multiple-output (MIMO) and non-orthogonal multiple-access (NOMA) are promising techniques to improve the link and system capacities. In addition, the simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) can be well integrated with the communication systems to effectively extend the wireless coverage in a cost-efficient manner. Therefore, in this paper, we investigate the performance of the downlink dual-user MIMO-NOMA systems assisted by STAR-RIS under the generalized singular value decomposition (GSVD) precoding scheme. Specifically, we first apply the operator-valued free probability theory to obtain the Cauchy transform of the generalized singular values (GSVs) of the MIMO-NOMA channel matrices under Rician fading with the Weichselberger’s correlation structure, in which a linearization trick for the matrix-valued rational functions is applied to simplify the derivations. Then, based on the Cauchy transform of GSVs, we obtain the closed-form expression for the asymptotic information rates of the users under the considered system. Furthermore, we propose a projected gradient ascent method (PGAM) to enhance the sum rate of the system by designing the phase shifts of the STAR-RIS based on the derived closed-form expressions. The numerical results show the accuracy of the asymptotic expression compared to the Monte Carlo simulations and the effectiveness of the proposed PGAM algorithm.

By exploiting the degree of freedom on the altitude, unmanned aerial vehicle (UAV) communication can provide ubiquitous communication for future wireless networks. In the case of concurrent transmission of multiple UAVs, the directional beamforming formed by multiple antennas is an effective way to reduce co-channel interference. However, factors, such as airflow disturbance or estimation error for UAV communications, can cause the occurrence of beam misalignment. In this article, we investigate the system performance of a multitier UAV communication network with the consideration of unstable beam alignment. In particular, we propose a tractable random model to capture the impacts of beam misalignment in the 3-D space. Based on this, by utilizing stochastic geometry, an analytical framework for obtaining the outage probability in the downlink of a multitier UAV communication network for the closest distance association scheme and the maximum average power association scheme is established. The accuracy of the analysis is verified by Monte Carlo simulations. The results indicate that in the presence of random beam misalignment, the optimal number of UAV antennas needs to be adjusted to be relatively larger when the density of UAVs increases or the altitude of UAVs becomes higher.

The temporary events are generally gathered around many users interested in the same content. An unmanned aerial vehicle (UAV) with caching and multicasting is attractive for such scenarios with high traffic demands, since the multicasting allows concurrently serving users, and the caching can alleviate the burden on backhaul links. Hence, in this work, we investigate a cellular network assisted by caching-and-multicasting-empowered UAVs, where UAVs multicast the files from their caching storage or base stations via wireless backhaul links. Particularly, a popularity-aware (PA) file selection and multicast scheme is proposed, where the files to be multicasted are determined by the instantaneous requested popularity, the maximum number of allowable fetched files and the performance on wireless backhaul links. By leveraging stochastic geometry, we obtain the approximated yet accurate result for the average number of successfully multicasted users. Our results confirm the effectiveness of the PA scheme, i.e., achieving a larger average number of successfully multicasted users compared to the random scheme for most cases. Moreover, the results suggest that a relatively smaller number of multicast channels or reducing the maximum number of allowable fetched files can benefit network performance in the case of the high signal-to-interference ratio threshold on the backhaul links.

Reconfigurable intelligent surface (RIS) has recently been widely investigated in wireless communication systems due to its low deployment cost and high-performance gain. In this work, we study the multiple-RIS-assisted uplink multiple-user multiple-input multiple-output (MU-MIMO) communication systems, where each user’s signal is sent to the base station via both the direct and the reflected links. To obtain informative insight into the considered system with the statistical channel information, we first derive the closed-form expression for the ergodic sum rate of the MU-MIMO systems by applying the operator-valued free probability theory. Then, the covariance matrices of the transmit signals and the phase shifts of the RIS elements are jointly optimized to maximize the derived asymptotic ergodic sum rate via alternating optimization (AO). Specifically, the AO procedure is composed of a water-filling algorithm and a gradient descent algorithm over the Riemannian manifold and the two algorithms iterate until convergence. The numerical results show the accuracy of the asymptotic expression compared to the Monte Carlo simulation and the superiority of the proposed AO algorithm compared to the benchmark. Furthermore, the rank deficiency of the MIMO channel can be significantly improved by the deployment of multiple RISs and the proposed AO algorithm.

Dual-functional radar-communication (DFRC) has been widely concerned in future communication systems. By aggregating communication and detection resources, DFRC enables improved communication data rate as well as continual real-time sensing capability. However, the spectral efficiency of the communication channel will be inevitably compromised since the transceiver design has to take into account both of the communication and radar oriented beampatterns. In this paper, the reconfigurable intelligent surface (RIS) panels are deployed to assist the design of multi-antenna DFRC transceivers, where the RIS panels introduce additional degree-of-freedom to accommodate the dual-functional beampattern. First, applying the operator-valued free probability theory, we derive the closed-form expression of the asymptotic achievable rate of the multi-RIS-assisted MIMO DFRC systems in presence of general Rician fading. Then, we propose an alternating optimization (AO) algorithm to jointly optimize the transmit signals of the DFRC transmitter and the phase shifts of the reflecting elements of the RIS panels, which achieves an optimal tradeoff between the achievable rate and the desired radar beampattern. Simulation results verify the accuracy of the asymptotic expression of the achievable rate. In addition, the deployment of RISs and the proposed AO algorithm are proven to improve both the detection and communication performance.

Due to the flexible deployment of unmanned aerial vehicles (UAVs) and the wide-area coverage of satellites, the space–air–ground (SAG) communication network can provide flexible and pervasive connectivity, especially in remote areas. In this work, we investigate the uplink transmission in a SAG network, where the nonorthogonal multiple access mechanism is adopted at the UAVs to enhance the number of access from ground user equipments (UEs) and a low-earth orbit satellite offers the wireless backhaul for UAVs. In particular, the energy efficiency (EE) of the considered network is maximized by optimizing the user association (UA), power allocation (PA), and UAV 3-D trajectory jointly with the consideration of the movement of the satellite. To tackle the formulated problem, by leveraging the block coordinate descent (BCD) method, we develop a joint UA, PA, and UAV trajectory (namely, JUPT) optimization algorithm, i.e., the original problem is decomposed into three subproblems, and the subproblems are solved iteratively until convergence. Specifically, we propose to include the virtual UEs in the system and develop a low-complexity matching algorithm to effectively solve the UA problem. A successive convex approximation (SCA)-based Dinkelbach algorithm is then adopted to address the PA problem. Later, with the introduction of the auxiliary variables, the UAV 3-D trajectory subproblem is iteratively solved by the SCA method. Our numerical results demonstrate the superiority of the proposed JUPT algorithm, which obtains significantly higher EE compared to the benchmark schemes. Moreover, the rapid convergence of the JUPT algorithm is verified.

Continuously increasing demands from enhanced mobile broadband, machine-to-machine and internet of things pose a growing threat to 5G communication. Satellites integrated with 5G and beyond are pivotal to achieve global coverage, reliable and continuing service access, with the booming low-orbit satellite (LEO) constellations. While previous works largely focus on rural or remote areas, the orbiting satellites cover the ground evenly. This paper is then interested in unserved or underserved users in urban hotspots arising from large-scale access. Under the large delay of the ground-to-satellite link and the dynamic characteristic of satellites, we propose a satellite-terrestrial cooperative, geographical dispersed and regional centralized batch access control scheme. A data-driven QoS indicator, responsivity, is proposed to complement the semi-online batch scheme from a network perspective. It combines subsiding access control from LEO satellite to ground with LEO satellite resources to provide auxiliary access for higher responsivity users relatively. We model the on-demand batch access mechanism as a multidimensional knapsack problem (MKP) solved by a hybrid genetic algorithm. Collectively, the cooperative batch mechanisms compress signaling transmission and reduce optional power consumption. Simulation results show that the new indicator achieves a better balance between spectral efficiency and global OoS compared to existing methods.

To support the ubiquitous connectivity requirement of sixth generation communication, unmanned aerial vehicles (UAVs) play a key role as a major part of the future communication networks. One major issue in UAV communications is the interference resulting from spectrum sharing and line-of-sight links. Recently, the application of the coordinated multipoint (CoMP) technology has been proposed to reduce the interference in the UAV-terrestrial heterogeneous network (HetNet). In this paper, we consider a three-dimensional (3D) multilayer UAV-terrestrial HetNet, where the aerial base stations (ABSs) are deployed at multiple different altitudes. Using stochastic geometry, we develop a tractable mathematical framework to characterize the aggregate interference and evaluate the coverage probability of this HetNet. Our numerical results show that the implementation of the CoMP scheme can effectively reduce the interference in the network, especially when the density of base stations is relatively large. Furthermore, the system parameters of the ABSs deployed at higher altitudes dominantly influence the coverage performance of the considered 3D HetNet.

Caching popular contents at edge networks (such as small-cell base stations) has been proposed to deal with the ever-growing mobile traffic. At the meantime, recommendation system is able to shape user demands for further prompting caching gain. In this paper, we study a multi-antenna multi-cell edge network employing transmit beamforming with caching-aware recommendation and user association. We first establish a framework for the joint problem of beamforming, user association, content caching and recommendation to minimize the content transmission delay of mobile users, by specifying a set of necessary conditions for all four component functions of the network. The resulting optimization problem corresponds to a non-convex, multi-timescale, and mixed-integer programming problem, which is hard to handle. To deal with the difficulty in solving the joint optimization problem by the direct formulation, we equivalently decompose it into three sub-problems. Then, we develop a computationally-efficient iterative algorithm to obtain the sub-optimal solution, where the three subproblems are tackled iteratively. Simulation results are conducted to demonstrate that the proposed algorithm can obtain lower transmission delay than baseline schemes.

The Satellite communication network is not limited by geographical factors and is an indispensable part of global interconnection. This paper analyzes a hybrid of cloud computing and edge computing LEO satellite network architecture, where the three-tier network is composed of ground users, LEO satellites, and remote cloud servers. Users can not only forward computing tasks to remote cloud servers through LEO satellites for processing, but also directly offload computing tasks to LEO satellites for processing. Based on this, we study the problem of user computing offloading in LEO satellite network and construct a joint optimization problem of offloading decision and computing resource allocation, which aims to reduce the user processing delay and energy consumption when the total computing resources of edge nodes are limited. This problem is a mixed-integer nonlinear problem, which is difficult to be solved in finite time. With the increase in the number of users, the complexity of the solution is very high. Therefore, we reconstruct the problem based on the linear reconstruction technique and relax the binary variables to transform the original non-convex problem into a convex problem. The simulation results show that the algorithm can effectively reduce user delay and energy consumption compared to the case when the tasks are processed locally.

In quorum sensing (QS), bacteria exchange molecular signals to work together. An analytically-tractable model is presented for characterizing QS signal propagation within a population of bacteria and the number of responsive cooperative bacteria (i.e., cooperators) in a two-dimensional (2D) environment. Unlike prior works with a deterministic topology and a simplified molecular propagation channel, this work considers continuous emission, diffusion, degradation, and reception among randomly-distributed bacteria. Using stochastic geometry, the 2D channel response and the corresponding probability of cooperation at a bacterium are derived. Based on this probability, new expressions are derived for the moment generating function and different orders of moments of the number of cooperators. The analytical results agree with the simulation results obtained by a particle-based method. In addition, the Poisson and Gaussian distributions are compared to approximate the distribution of the number of cooperators and the Poisson distribution provides the best overall approximation. The derived channel response can be generally applied to any molecular communication model where single or multiple transmitters continuously release molecules into a 2D environment. The derived statistics of the number of cooperators can be used to predict and control the QS process, e.g., predicting and decreasing the likelihood of biofilm formation.

Providing seamless connection to a large number of devices is one of the biggest challenges for the Internet of Things (IoT) networks. Using a drone as an aerial base station (ABS) to provide coverage to devices or users on ground is envisaged as a promising solution for IoT networks. In this paper, we consider a communication network with an underlay ABS to provide coverage for a temporary event, such as a sporting event or a concert in a stadium. Using stochastic geometry, we propose a general analytical framework to compute the uplink and downlink coverage probabilities for both the aerial and the terrestrial cellular system. Our framework is valid for any aerial channel model for which the probabilistic functions of line-of-sight (LOS) and non-LOS links are specified. The accuracy of the analytical results is verified by Monte Carlo simulations considering two commonly adopted aerial channel models. Our results show the nontrivial impact of the different aerial channel environments (i.e., suburban, urban, dense urban, and high-rise urban) on the uplink and downlink coverage probabilities and provide design guidelines for best ABS deployment height.

Deployment of low-cost power beacons (PBs) is a promising solution for dedicated wireless power transfer (WPT) in future wireless networks. In this paper, we present a tractable model for PB-assisted millimeter wave (mmWave) wireless ad hoc networks, where each transmitter (TX) harvests energy from all PBs and then uses the harvested energy to transmit information to its desired receiver. Our model accounts for realistic aspects of WPT and mmWave transmissions, such as power circuit activation threshold, allowed maximum harvested power, maximum transmit power, beamforming, and blockage. Using stochastic geometry, we obtain the Laplace transform of the aggregate received power at the TX to calculate the power coverage probability. We approximate and discretize the transmit power of each TX into a finite number of discrete power levels in log scale to compute the channel and total coverage probability. We compare our analytical predictions to simulations and observe good accuracy. The proposed model allows insights into effect of system parameters, such as transmit power of PBs, PB density, main lobe beamwidth, and power circuit activation threshold on the overall coverage probability. The results confirm that it is feasible and safe to power TXs in an mmWave ad hoc network using PBs.

Backscatter communication (BackCom), which allows a backscatter node (BN) to communicate with the reader by modulating and reflecting the incident continuous wave from the reader, is considered a promising solution to power the future Internet-of-Things. In this paper, we consider a single BackCom system, where multiple BNs are served by a reader. We propose using the power-domain non-orthogonal multiple access (NOMA), i.e., multiplexing the BNs in different regions or with different backscattered power levels, to enhance the spectrum efficiency of the BackCom system. To better exploit power-domain NOMA, we propose setting the reflection coefficients for multiplexed BNs to be different. Based on this considered model, we develop the reflection coefficient selection criteria. To illustrate the enhanced system with the proposed criteria, we analyze the performance of the BackCom system in terms of the average number of bits that can be successfully decoded by the reader for the two-node pairing case and the average number of successful BNs for the general multiplexing case. Our results show that NOMA achieves the much better performance gain in the BackCom system as compared to its performance gain in the conventional system, which highlights the importance of applying NOMA to the BackCom system.

Enabling machine-type communication (MTC) over large scale cellular networks is a promising solution to handling the emerging MTC traffic. To enable a massive number of machines to connect to the base station, random access mechanisms and data aggregation have been largely studied separately in the literature. In this paper, we use stochastic geometry to investigate MTC over cellular with access class barring enhanced random access and data aggregation. We present an approximate yet accurate and tractable analytical framework for characterizing the MTC performance in terms of the machine type device (MTD) success probability, average number of successful MTDs and probability of successful preamble utilization. We validate the proposed model by comparison with simulations. Our results show that while the provision of more resources for the relaying phase benefits MTC, the provision of more preambles in the random access is not always beneficial to MTC. Thus, system parameters need to be chosen carefully to benefit the MTC traffic.

Wireless power transfer (WPT) has emerged as an attractive solution to power future wireless communication networks. In this paper, we consider WPT using power beacons (PBs) for a millimeter wave (mmWave) wireless ad hoc network. Using stochastic geometry, we derive the moment generating function (MGF) and the nth cumulant of the aggregate received power from PBs at a reference receiver in closed-form. The MGF allows the complementary cumulative distribution function (CCDF) of the aggregate received power from PBs to be numerically evaluated. We also compare different closed-form distributions which can be used to approximate the CCDF of the aggregate received power. Our results show that the lognormal distribution provides the best CCDF approximation compared to other distributions considered in the literature. The results also show that under practical setups, it is feasible to power users in a mmWave ad hoc network using PBs.

Access class barring (ACB) is regarded as an efficient and practically implementable method to reduce the traffic overload in cellular networks. In this paper, we present a unified analytical framework to analyze the performance of the fixed ACB scheme for a simple random access procedure (i.e., one-shot transmission model) in machine type communication (MTC) over cellular networks. We derive the exact expressions for the probability of a machine's packet being served by the base station (BS), the average number of machine type devices (MTDs) successfully served by the BS per second and the noncollision slot access probability. We verify the accuracy of the derived expressions by comparison with simulations. Based on the analytical expressions, we then maximize the probability of a MTD's packet being served and obtain the sub-optimal probability factor value for the fixed ACB in closed-form. Our results confirm that, the use of ACB scheme is important for scenarios with high MTD packet arrival rate, which is relevant for massive MTC. The proposed framework allows fine tuning and accurate prediction of the MTC performance with ACB.

In this paper, we consider underlay in-band device-to-device (D2D) communication in a finite cellular network region. To minimize the D2D interference generated at the base station (BS), we adopt the exclusion zone mechanism, i.e., only D2D users outside the BS exclusion zone share the same resource with the cellular uplink user. Using the stochastic geometry, we develop a general framework to analytically compute the outage probability at the center-located BS and the outage probability at an arbitrarily located D2D receiver in a disk-shaped network region. To quantify the overall D2D communication performance in the finite region, the average number of successful D2D transmissions is also derived. It shows that the D2D receiver close to the cell edge or the exclusion zone experiences lower outage probability compared to the D2D receiver not close to the edge region, which illustrates the location-dependent performance. Moreover, given the outage probability constraint at the BS, which is controlled by varying the radius of the exclusion zone, we find that there is an optimum D2D receiver sensitivity that results in the maximum average number of successful D2D transmissions. The results highlight the importance of carefully choosing system parameters to extract the benefit from the exclusion zone.

To enable massive machine type communication (mMTC), data aggregation is a promising approach to reduce the congestion caused by a massive number of machine type devices (MTDs). In this paper, we consider a two-phase cellular-based mMTC network, where MTDs transmit to aggregators (i.e., aggregation phase) and the aggregated data is then relayed to base stations (i.e., relaying phase). Due to the limited resources, the aggregators not only aggregate data, but also schedule resources among MTDs. We consider two scheduling schemes: random resource scheduling (RRS) and channel-aware resource scheduling (CRS). By leveraging the stochastic geometry, we present a tractable analytical framework to investigate the signal-to-interference ratio (SIR) for each phase, thereby computing the MTD success probability, the average number of successful MTDs and probability of successful channel utilization, which are the key metrics characterizing the overall mMTC performance. Our numerical results show that, although the CRS outperforms the RRS in terms of SIR at the aggregation phase, the simpler RRS has almost the same performance as the CRS for most of the cases with regards to the overall mMTC performance. Furthermore, the provision of more resources at the aggregation phase is not always beneficial to the mMTC performance.

Underlay in-band device-to-device (D2D) communication can improve the spectrum efficiency of cellular networks. However, the coexistence of D2D and cellular users causes inter-cell and intra-cell interference. The former can be effectively managed through inter-cell interference coordination and, therefore, is not considered in this paper. Instead, we focus on the intra-cell interference and propose a D2D mode selection scheme to manage it inside a finite cellular network region. The potential D2D users are controlled by the base station (BS) to operate in D2D mode based on the average interference generated to the BS. Using stochastic geometry, we study the outage probability experienced at the BS and a D2D receiver, and spectrum reuse ratio, which quantifies the average fraction of successfully transmitting D2D users. The analysis shows that the outage probability at the D2D receiver varies for different locations. In addition, without impairing the performance at the BS, if the path-loss exponent on the cellular link is slightly lower than that on the D2D link, the spectrum reuse ratio can have negligible decrease, while the D2D users' average number of successful transmissions increases with increasing D2D node density. This indicates that an increasing level of D2D communication can be beneficial in future networks.

In this paper, we build a unified analytical framework that allows for analysis and comparison of three device-to-device (D2D) mode selection schemes proposed in the literature to date, namely the distance cut-off scheme, the link gain scheme and the guard zone scheme. In the framework we adopt Poisson point process (PPP) assumptions to model the cellular and D2D interference, respectively. Using stochastic geometry, we derive easy to implement expressions for the success probability at a typical base station (BS) and a typical D2D receiver (RX) in an underlay in-band D2D-enabled single tier cellular network. Comparing the derived analytical results with simulations, we show that the PPP assumptions are accurate for the success probability at the BS. Moreover, they provide a good approximation for the success probability at the D2D RX when the D2D RX is located close to the cell edge. Furthermore, the distance cut-off scheme generally outperforms other mode selection schemes.

This paper analyzes the performance of the primary users (PUs) and secondary users (SUs) in an arbitrarily-shaped underlay cognitive network. In order to meet the interference threshold requirement for a primary receiver at an arbitrary location, we consider different SU activity protocols that limit the number of active SUs. We propose a framework, based on the moment-generating function of the interference due to a random SU, to analytically compute the outage probability in the primary network, as well as the average number of active SUs in the secondary network. We also propose a cooperation-based SU activity protocol in the underlay cognitive network that includes the existing threshold-based protocol as a special case. We study the average number of active SUs for the different SU activity protocols, subject to a given outage probability constraint at the PU, and we employ it as an analytical approach to compare the effect of different SU activity protocols on the performance of the primary and secondary networks.

This paper characterizes the aggregate interference at the primary user (PU) due to M secondary users (SUs) in an underlay cognitive network, where appropriate SU activity protocols are employed in order to limit the interference generated by the SUs. Different from prior works, we assume that the PU can be located anywhere inside an arbitrarily-shaped convex network region. Using the moment generating function (MGF) of the interference from a random SU, we derive general expressions for the n-th moment and the n-th cumulant of the aggregate interference for guard zone and multiple-threshold SU activity protocols. Using the cumulants, we study the convergence of the distribution of the aggregate interference to a Gaussian distribution. In addition, we compare the well-known closed-form distributions in the literature to approximate the complementary cumulative distribution function (CCDF) of the aggregate interference. Our results show that care must be undertaken in approximating the aggregate interference as a Gaussian distribution, even for a large number of SUs, since the convergence is not monotonie in general. In addition, the shifted lognormal distribution provides the overall best CCDF approximation, especially in the distribution tail region, for arbitrarily-shaped network regions.

This paper analyzes the outage performance in finite wireless networks. Unlike most prior works, which either assumed a specific network shape or considered a special location of the reference receiver, we propose two general frameworks for analytically computing the outage probability at any arbitrary location of an arbitrarily-shaped finite wireless network: (i) a moment generating function-based framework which is based on the numerical inversion of the Laplace transform of a cumulative distribution and (ii) a reference link power gain-based framework which exploits the distribution of the fading power gain between the reference transmitter and receiver. The outage probability is spatially averaged over both the fading distribution and the possible locations of the interferers. The boundary effects are accurately accounted for using the probability distribution function of the distance of a random node from the reference receiver. For the case of the node locations modeled by a Binomial point process and Nakagami-m fading channel, we demonstrate the use of the proposed frameworks to evaluate the outage probability at any location inside either a disk or polygon region. The analysis illustrates the location-dependent performance in finite wireless networks and highlights the importance of accurately modeling the boundary effects.