Indoor Positioning Systems (IPS) based on Received Signal Strength (RSS) often face challenges in achieving high accuracy due to spatial and temporal uncertainties in complex indoor environments. To address these limitations, this paper proposes a novel Static Reconfiguration Algorithm (SRA) leveraging Reconfigurable Intelligent Surface (RIS) technology to optimize RSS distributions. Unlike traditional methods, the SRA eliminates the need for dynamic RIS reconfiguration, instead employing a static approach that maximizes differentiation between RSS values at predefined Reference Points (RPs). This enhances localization precision by reducing spatial correlation and improving distinguishability, even in noisy environments. Simulation results demonstrate that the SRA significantly outperforms conventional RSS-based approaches, achieving positioning errors as low as 75 cm in high-noise scenarios compared to 150 cm with traditional methods. Furthermore, the algorithm proves effective across broader RSS measurement ranges (-100 to 0 dB) and achieves superior performance even with a single Access Point (AP). The multidimensional SRA approach further enhances accuracy by leveraging diverse RSS distributions through additional APs and time-division multiplexing. These results underscore the robustness, scalability, and efficiency of the SRA, positioning it as a transformative solution for next-generation IPS in smart environments.

New data protection regulations, e.g., General Data Protection Regulation (GDPR), enforced advertisement providers to amend their conventional approaches, enhancing users’ data privacy. As a result, major internet browsers, such as Apple Safari and Firefox, were quick to announce their plans to remove third-party cookies from their browsers entirely. In an effort to preserve conventional advertising practices, Google proposed a Federated Learning of Cohorts (FLoC) system to deliver higher privacy guarantees to users while also providing interest-based advertising. In FLoC, users sharing similar browsing histories are put into cohorts, and thus advertisements can be targeted to them as a group, rather than individually. Since each user independently calculates their cohort group, a minimum cohort size cannot be enforced, making them vulnerable to identification and tracking. To address this issue, in this article, a blockchain-based FLoC (BB-FLoC) system is proposed that guarantees k -anonymity for its users while at the same time allowing for effective personalised advertising. We further evaluate the operational feasibility of such a design and demonstrate that k -anonymity guarantees can be fulfilled in a fully decentralised manner in the proposed system. The proposed system is relatively lightweight, showcasing that it can be adapted for low-end devices, such as mobile phones.

In navigating the challenges of real-time semantic communication (SC) codec updates in the 6G-era non-terrestrial network (NTN)-assisted vehicular networks (NTN-VNs), a crucial component of intelligent transportation systems (ITS), this article introduces a novel approach inspired by human society. Facing complexities like 3-dimensional updating, network dynamism, and updating costs, NTN-VNs are treated as social networks. The proposed NTN-VN federated learning (NTN-VN-FL) framework asynchronously addresses challenges such as uplink and downlink SC codec updates, device decentralization, and asynchronous updating. By viewing device behaviors during updating as social behaviors with economic costs, an NTN-VN social management system ensures the proper functioning of the social network in the context of NTN-VN-FL. An economical social behavior selection mechanism, based on the reverse auction game for NTN-VN-FL, minimizes training delay and device energy costs, considering social relationships. The article also presents a two-stage Stackelberg game with the Vickrey auction rule to maximize social welfare in the auction. Simulation results highlight the superiority of NTN-VN-FL over existing potential application algorithms, effectively addressing the unique challenges of SC codec updating in NTN-VN. The efficacy of the social management system and social behavior selection mechanism is demonstrated in achieving optimal outcomes.

The combination of simultaneously transmitting and reflecting-reconfigurable intelligent surface (STAR-RIS) and nonorthogonal multiple access (NOMA) brings the necessary full-space degrees of freedom and spatial multiplexing gains for the Internet of Things (IoT) networks. The inherent network heterogeneity and sharing of wireless channels may however increase the exposure of the information interactions to the third party. To address this issue, we propose a covert communication scheme in STAR-RIS assisted NOMA networks over Nakagami-m fading channels, where both downlink and uplink IoT scenarios are considered. Under the NOMA protocol with imperfect successive interference cancelation (SIC), an IoT access point interacts with two IoT users aided by a STAR-RIS without being detected by two wardens. In this scenario, the two IoT users are located on both sides of the STAR-RIS which adopts coherent phase shifting and operates according to the mode switching protocol. To evaluate the wardens’ detection performance, the Kullback-Leibler (KL) divergence is used. Furthermore, the cascaded channel gains of IoT users and wardens are, respectively, characterized as Gamma and complex Gaussian random variables. The closed-form expressions of the expectations of KL divergence and the interruption probabilities for downlink and uplink are derived. To further improve the performance, we formulate the effective covert rate maximization as the joint optimization problems of the transmit power and power allocation coefficient for downlink and uplink, subject to the constraints for covertness, reliability and power budget, which are, respectively, resolved analytically. Extensive simulation results indicate that the proposed scheme improves covertness compared with the benchmarks.

Machine learning-based semantic communication is a promising enabler for future-generation wireless network systems such as 6G networks. In practice, effective semantic communication requires online training for unknown content. In highly mobile vehicular networks, however, reliable, and efficient model training becomes significantly challenging. The existing distributed learning approaches are also unable to effectively operate in highly dynamic vehicular semantic communication networks. To address these challenges, we propose a novel mobility-aware split-federated with transfer learning (MSFTL) framework based on vehicle task offloading scenarios in this paper. To enable adaptation to the complex vehicle semantic communication, the proposed framework divides the training of the model into four parts and uses the proposed new splitfederated learning. Furthermore, to improve training efficiency, model accuracy, and the ability to adapt in highly mobile environments, we also present a new transfer learning approach integrated into the proposed framework. Particularly, we propose a high-mobility training resource optimisation mechanism based on a Stackelberg game for MSFTL to further reduce training costs and adapt vehicle mobility scenarios. We also investigate the performance of the proposed schemes through extensive simulations. The results validate the proposed approach and indicate its superiority compared to the conventional learning frameworks for semantic communication in vehicular networks.

The low earth orbit (LEO) satellite-borne edge cloud (SEC) and machine learning (ML) based semantic communication (SemCom) are both enabling technologies for 6G systems facilitating computation offloading. Nevertheless, integrating SemCom into the SEC networks for user computation offloading introduces semantic coder updating requirements as well as additional semantic extraction costs. Offloading user computation in SEC networks via SemCom also results in new functional challenges considering, e.g., latency, energy, and privacy. In this paper, we present a novel SemCom-assisted SEC (SemCom-SEC) framework for computation offloading of resource-limited users. We then propose an adaptive pruning-split federated learning (PSFed) method for updating the semantic coder in SemCom-SEC. We further show that the proposed method guarantees training convergence speed and accuracy. This method also improves the privacy of the semantic coder while reducing training delay and energy consumption. In the case of trained semantic coders in service, for the users processing computational tasks, the main objective is to minimise the users’ delay and energy consumption, subject to sustaining users’ privacy and fairness amongst them. This problem is then formulated as an incomplete information mixed integer nonlinear programming (MINLP) problem. A new computational task processing scheduling (CTPS) mechanism is also proposed based on the Rubinstein bargaining game. Simulation results demonstrate the proposed PSFed and game theoretical CTPS mechanism outperforms the baseline solutions reducing delay and energy consumption while enhancing users’ privacy.

The intelligent reflecting surface (IRS) technology is emerged as an enabling technology for beyond fifth-generation systems and Internet of Things networks in which the signal propagation is reconfigured to enhance wireless system performance. IRS consists of many passive elements and each reflecting the incident signal with a certain phase shift to collectively achieve the required beamforming. The IRS is to be a low profile and lightweight setting with a conformal geometry; hence, its position can be easily engineered to achieve certain performance enhancements. In the current literature, however, the flexibility in the IRS position is often overlooked since it is considered as a given fixture. We argue that optimizing the IRS position provides a new degree of freedom in the network design and enables extra performance gain. In this article, we analytically characterize the optimal IRS’s position to maximize the achievable system rate. We then obtain the optimal IRS positions for different IRS settings with fixed height and variable height and consider both cost-efficient equal phase shift IRS, and nonequal phase shift IRS that enables sophisticated beamforming. We further incorporate antenna directivity in our analysis and investigate its effect on the optimal IRS position in each case. Simulation results show that the provided optimal position yields higher performance than settings with random IRS locations. Our results provide significant practical insights on the network coverage design using the IRS.

Abstract Unmanned aerial vehicles (UAVs) have gained considerable interests in numerous civil applications. To push forward its potentials, cellular-connected UAVs have been introduced. Nevertheless, cellular networks face several bottlenecks such as spectrum scarcity and limited concurrent connectivity. To address these issues, non-orthogonal multiple access (NOMA) can be adopted. NOMA provides several opportunities for cellular-connected UAVs such as larger rate region, balanced performance between system throughput and fairness, and reduced delay. In this paper, we review important findings of the related studies, and outline new opportunities and challenges in NOMA for cellular-connected UAVs. Monte-Carlo simulations are then performed to analyze the new aerial user’s (AU)’s signal characteristics and evaluate the NOMA performance for co-existence of AU and terrestrial user (TU). Our preliminary results show that NOMA is a promising strategy for cellular-connected UAVs.

Efficiency of cellular-connected UAVs is challenged by spectrum inefficiency, limited number of concurrent connectivity, and strong interference. To overcome these issues, in this paper, we study the performance of downlink non-orthogonal multiple access for cellular-connected UAVs. We develop a novel framework based on stochastic geometry for the co-existence of aerial users (AUs) and terrestrial users (TUs), where the spatial distribution of the base stations (BSs) follows a Poisson Point Process. In our analysis, two user association policies and two types of receive antennas are considered while an inter-cell interference coordination (ICIC) technique is also in place. As the main performance measures, we then analytically derive the coverage probability and average rate of AUs and TUs. These derivations are then used to provide quantitative insights on the impact of different system parameters and settings including AU's altitude, TU's distance from the BS, power allocation, successive interference cancellation (SIC) constraints, user association policy, antenna beamwidth, and the number of coordinated BSs. Based on our analysis we then propose an interference-aware scheme based on maximum-SINR user association, directional antenna, and ICIC. A benchmark scheme based on minimum-distance user association, omni-directional antenna, and without ICIC is considered. Compared to the benchmark scheme, our proposed scheme improves the AU's coverage probability by threefold and TU's average rate by six-fold. Compared to the orthogonal multiple access, our proposed scheme trades off a slight reduction in the AU's coverage probability (~1%) with a significant increase in the achieved rate of the TUs (603Kbps/resource block).

In this paper, we propose a downlink multiple-input single-output (MISO) transmission scheme, which is assisted by an intelligent reflecting surface (IRS) consisting of a large number of passive reflecting elements. In the literature, it has been proved that nonorthogonal multiple access (NOMA) can achieve the same performance as computationally complex dirty paper coding, where the quasi-degradation condition is satisfied, conditioned on the users' channels fall in the quasi-degradation region. However, in a conventional communication scenario, it is difficult to guarantee the quasi-degradation, because the channels are determined by the propagation environments and cannot be reconfigured. To overcome this difficulty, we focus on an IRS-assisted MISO NOMA system, where the wireless channels can be effectively tuned. We optimize the beamforming vectors and the IRS phase shift matrix for minimizing transmission power. Furthermore, we propose an improved quasi-degradation condition by using IRS, which can ensure that NOMA achieves the capacity region with high possibility. For a comparison, we study zero-forcing beamforming (ZFBF) as well, where the beamforming vectors and the IRS phase shift matrix are also jointly optimized. Comparing NOMA with ZFBF, it is shown that, with the same IRS phase shift matrix and the improved quasi-degradation condition, NOMA always outperforms ZFBF. At the same time, we identify the condition under which ZFBF outperforms NOMA, which motivates the proposed hybrid NOMA transmission. Simulation results show that the proposed IRS-assisted MISO system outperforms the MISO case without IRS, and the hybrid NOMA transmission scheme always achieves better performance than orthogonal multiple access.

Connecting aerial users (AU)s to cellular networks expands the potential of many applications. Nevertheless, existing cellular networks are not designed to efficiently serve AUs and terrestrial users (TU)s. Limited spectrum and high interference make the task even more challenging. Thus, in this paper, we examine the feasibility of fixed-power non-orthogonal multiple access (NOMA) scheme in meeting the demands of AUs and TUs by leveraging stochastic geometry. To this end, we propose a tractable framework for evaluating the coverage of AU and TU in cellular networks, where BSs are distributed using Poisson Point Process (PPP). We then derive the coverage probability of AU and TU. Using these analytical expressions, we further analyze the impact of different network parameters such as AU's altitude, TU's distance, and power allocation, and obtain key insights for designing an efficient NOMA scheme. Our results show that i) increasing AU's altitude does not always degrade the signal-to-interference ratio (SIR), ii) fixed-power NOMA scheme cannot be employed solely to serve AU's control and command (C& C) link, iii) pairing a near TU with a typical AU may prevent significant performance degradation, and iv) mitigating the interference of TU could improve the performance of AU.

Scarcity of the radio spectrum and high inter-cell interference (ICI) are major impediments to efficient connectivity in cellular-connected unmanned aerial vehicles (UAV)s. To address these issues, we propose aerial-terrestrial network non-orthogonal multiple access (ATN-NOMA). In the proposed scheme, we pair the aerial user (AU) and terrestrial user (TU) in a NOMA setting to leverage their asymmetric channel gains and rate demands in downlink communication. The high ICI issue at the AU receiver is further managed by equipping the AU with an adjustable beamwidth directional antenna and forming a distributed beamforming among the coordinated terrestrial base stations (BSs). The proposed ATN-NOMA scheme obtains the optimal beamwidth and power allocation to maximize the TUs' sum-rate subject to the AU's Quality-of-Service (QoS) requirement. The corresponding optimization is a non-convex optimization problem for which we exploit the structure of the problem to obtain a local optimal solution. We further compare TUs' sum-rate and AU's outage probability of the proposed scheme with multiple schemes. Simulation results show that our proposed scheme significantly outperforms the existing schemes and further demonstrate a robust performance against UAV altitude variations.

Fluctuating two-ray (FTR) channel model was shown to effectively characterize millimeter wave (mmWave) communication channels. In this article, we adopt FTR to investigate amplify-and-Forward (AF) mmWave relaying system. Two communications scenarios are considered corresponding to the presence and absence of a direct link between the transmitter and receiver. Outage probability and symbol error rate (SER) are then analytically obtained as performance metrics. The results are further compared with the corresponding metrics obtained based on conventional channel models including Nakagami-m and two-wave with diffuse power (TWDP). Especially, for the high-SNR regime, our analyses indicate that performance evaluations based on the conventional models significantly deviate from that of based on the FTR model. Our results provide quantitative insights on the importance of model selection in design and performance evaluations of relay-based mmWave systems. Moreover, for the high-SNR regime, we carry out asymptotic analysis and obtain a low-complexity expression for the achieved AF relaying gain. Such an expression provides a quantitative measure on whether or not AF relaying outperforms no-relaying in a given setting. Extensive numerical and simulation results are provided to confirm the accuracy of the analysis and investigate system performance in different settings.

The performance of multiple-input multiple-output (MIMO) multiplexing heterogenous cellular networks are often analyzed using a single-exponent path-loss model. Thus, the effect of the expected line-of-sight (LOS) propagation in densified settings is unaccounted for, leading to inaccurate performance evaluation and/or inefficient system design. This is due to the complexity of LOS/non-LOS models in the context of MIMO communications. We address this issue by developing an analytical framework based on stochastic geometry to evaluate the coverage performance. We focus on the zero-forcing beamforming where the maximum signal-to-interference ratio is used for cell association. We analytically derive the coverage. We then investigate the cross-stream interference correlation, and develop two approximations of the coverage: Alzer Approximation (A-A) and Gamma Approximation (G-A). The former is often used in the single antenna and single-stream MIMO. We extend A-A to a MIMO multiplexing system and evaluate its utility. We show that the inverse interference is well-fitted by a Gamma random variable, where its parameters are directly related to the system parameters. The accuracy and robustness of G-A is higher than that of A-A. We observe that depending on the multiplexing gain, it is possible to attain the best coverage probability by proper densification.

In this paper, we consider a downlink wireless communication system with the co-existence of ground user (GU) and mobile aerial user (AU). Existing solutions rely on orthogonal multiple access (OMA) to support these users, however, OMA is unable to provide the best rate and outage performance because its spectral efficiency is limited by the users' channel conditions and rate requirements. Thus, we propose an aerial-ground non-orthogonal multiple access (AG-NOMA) scheme that pairs the GU and AU for data and control links, respectively. Unlike terrestrial non-orthgonal multiple access (NOMA), the key idea of AG-NOMA is to exploit the asymmetric features of the channels and rate demands of the GU and AU in the downlink communication. Based on these opportunities, we investigate the maximum achievable GU rate over a time-varying wireless channel while satisfying the AU Quality-of-Service (QoS) requirement with perfect and partial channel state information (CSI). For perfect CSI, we derive the optimal successive interference cancellation (SIC) policy, power allocation, GU rate, and feasibility conditions in closed-form expressions. For partial CSI, we also derive the suboptimal SIC policy and power allocation in closed-form expressions, and further discussed a tradeoff between the achievable rate and reliability. This tradeoff depends on the system parameters, and thus we have suggested some appropriate parameters based on theoretical support and standard requirements to strike a balance between rate and reliability. Our simulation results show that AG-NOMA scheme with perfect and partial CSI can achieve up to +99% GU rate-improvement as compared to OMA and provide a more sustainable rate-improvement and/or lower outage probability than terrestrial NOMA scheme.

Non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) have been recognized as promising technologies for the beyond fifth generation networks to achieve significant capacity improvement and delay reduction. In this paper, the technologies of hybrid NOMA and MEC are integrated. In the hybrid NOMA MEC system, multiple users are classified into different groups and each group is allocated a dedicated time slot. In each group, a user first offloads its task by sharing a time slot with another user, and then solely offloads during a time interval. To reduce the delay and save the energy consumption, we consider jointly optimizing the power and time allocation in each group as well as the user grouping. As the main contribution, the optimal power and time allocation is characterized in closed form. In addition, by incorporating the matching algorithm with the optimal power and time allocation, we propose a low complexity method to efficiently optimize user grouping. Simulation results demonstrate that the proposed resource allocation method in the hybrid NOMA MEC systems not only yields better performance than the conventional OMA scheme but also achieves quite close performance as global optimal solution.

In this paper, we consider a nonorthogonal multiple access (NOMA) assisted mobile edge computing (MEC) system where the power and time are jointly optimized to reduce the energy consumption and delay. In order to achieve a tradeoff between energy consumption and delay, we introduce weighting factors, and the optimization problem is formulated to minimize the weighted sum of energy consumption and delay. In the literature, only two offloading strategies, i. e., orthogonal multiple access (OMA) and pure NOMA, are mainly considered. In this paper, we investigate a third strategy, hybrid NOMA, which contains the strategies of OMA and pure NOMA. As the main contribution, we analytically characterize the optimal resource allocation, i. e., the joint power and time allocation, for two-scheduled-user case. Simulation results show that the proposed resource allocation method in hybrid NOMA systems yields lower energy consumption and delay than the conventional OMA scheme.

Analysis of the performance of Unmanned Aerial Vehicle (UAV)-enabled communications systems often relies upon idealized antenna characteristic, where the side-lobe gain of UAVs' antenna is ignored. In practice, however, side-lobe cause inevitable interference to the ground users. We investigate the impact of UAVs' antenna side-lobe on the performance of UAV-enabled communication. Our analysis shows that even for a very small antenna's side-lobe gain, the ground receiver can experience substantial interference. We further show that a rather large exclusion zone is required to ensure a sufficient level of protection for the ground receiver. Nevertheless, in a multiple-antenna setting for the ground users, even when such a large exclusion zone was in place, UAVs' antenna side-lobe creates a high level of correlation among the interference signals received across receive antennas. Such a correlation limits the system ability to exploit channel diversity in a multiple-antenna setting for improving capacity. We then quantify the impact of UAVs' antenna side-lobes on the overall system performance by deriving the corresponding loss of the achieved capacity in various communications environments. We provide a new quantitative insight on the cost of adopting non-ideal UAV antenna on the overall capacity. Our analysis also shows that the capacity loss can be confined by careful selection of system parameters.

Non-orthogonal multiple access (NOMA) with power-domain user multiplexing has been considered as one of the potential candidates of the fifth-Generation (5G) systems. In this paper, a two-stage user selection algorithm is proposed based on proportional fairness for downlink NOMA with zero-forcing beamforming (PF-NOMA-ZFBF) in order to improve the throughput-fairness trade-off for NOMA system. We focus on short term fairness, where short term refers to the minimum time window in which a specified fairness is guaranteed and evaluated using Jain's index. A transmit power allocation then applied to enhance the throughput of NOMA system. Simulation results show that the proposed PF-NOMA-ZFBF significantly improves user fairness index with at least 38.96% over conventional NOMA-ZFBF while maintaining the total system sum-rate (near maximum).

Providing seamless coverage in current cellular network technologies is surmountable only through gross overengineering. Alternatively, as an economically effective solution, the use of unmanned aerial vehicles (UAVs), augmented with the functionalities of terrestrial base stations (BSs), is recently advocated. In this paper we investigate the effect that the incorporation of UAV-mounted BSs (U-BS) poses on the coverage probability of cellular networks. To this end, we focus on the evaluation of the coverage probability of a large-scale aerialterrestrial heterogenous cellular network (AT-HetNet), in which BSs of each technology/tier can be either ground (G-BS) or UBS. Our analysis incorporates the impact of Line-of-Sight (LOS) and non-LOS (NLOS) path-loss attenuations of both ground-toground (G2G) and Air-to-Ground (A2G) links. Adopting tools of stochastic geometry we then obtain the coverage probability as a function of main system parameters and percentage of BSs in each tier that are aerial. Using simulations we also confirm the accuracy of our analysis. We further observe that for several common communication environments, e.g., high-rise and dense urban environments, the inclusion of U-BSs can be detrimental to the coverage probability. Nevertheless, it is still possible to minimize the coverage cost by turning off a percentage of G-BSs. Interestingly, for urban and sub-urban areas one can adjust the altitude of U-BSs in order to adjust the coverage probability.

In this paper, we propose a novel power allocation scheme that maximizes the sum spectral efficiency of the licensee in a dynamic Licensed Shared Access (LSA) system. In particular, our focus is on the time intervals in which the incumbent system is active in the spectrum. We derive an expression for the interference distribution of the licensee, e.g., a mobile network operator, utilizing a spectrum belonging to an airport incumbent under the LSA spectrum sharing. Formulating an optimization problem to maximize the sum spectrum efficiency subject to the interference threshold constraint at the licensee, we then show its convexity, and obtain its optimal solutions. We further investigate the impact of sum rate maximization on the fairness of network resource allocations. Simulation results show a significant gain in the achievable spectrum efficiency, especially during the intervals in which the incumbent system is active in the LSA band. This paper provides quantitative insights on the maximum achievable sum rate in an LSA system in which both the licensee and the incumbent systems are active at the same time.

Caching the content closer to the user equipments (UEs) in heterogenous cellular networks (HetNets) improves user-perceived Quality-of-Service (QoS) while lowering the operators backhaul usage/costs. Nevertheless, under the current networking strategy that promotes aggressive densification, it is unclear whether cache-enabled HetNets preserve the claimed cost-effectiveness and the potential benefits. This is due to 1) the collective cost of caching which may inevitably exceed the expensive cost of backhaul in a dense HetNet, and 2) the excessive interference which affects the signal reception irrespective of content placement. We analyze these significant, yet overlooked, issues, showing that while densification reduces backhaul load and increases spectral efficiency in cache-enabled dense networks, it simultaneously reduces cache-hit probability and increases the network cost. We then introduce a caching efficiency metric, area spectral efficiency per unit spent cost, and find it enough to cache only about 3% of the content library size in the cache of small-cell base stations. We further show that range expansion, known to be of substantial value in wireless networks, is almost impotent to curb the caching inefficiency. Surprisingly, unlike the conventional wisdom recommending traffic offloading from macro cells to small cells, in cache-enabled HetNets, it is more beneficial to exclude offloading altogether or to do the opposite.

We consider an unmanned aerial vehicle enabled (UAV-enabled) fog-radio access network (F-RAN) in which UAVs are considered as flying remote radio heads (RRH) equipped with caching and cooperative communications capabilities. We are mainly focus on probabilistic/randomized content placement strategy, and accordingly formulate the content placement as an optimization problem. We then study the efficiency of the proposed content placement by evaluating the average system capacity and its energy-efficiency. Our results indicate that cooperative communication plays an essential role in UAV-enabled edge communications as it effectively curbs the impact of dominant Line-of-Sight (LOS) received interference. It is also seen that cooperative cache-enabled UAV F-RAN performs better in high-rise environments than dense urban and sub-urban environments. This is due to a significant reduction of the received LOS interference because of blockage by the high-rise buildings, and the performance gain of cooperative communication on the attending signal. Comparing the performances of the developed content placement strategy and conventional caching techniques shows that our proposed probabilistic/randomized caching outperforms the others in most of the practical cases.

Coverage evaluation of heterogeneous multi-tier cellular networks (HetNets) is often based on simplifying assumptions on cell association (CA): the resource required by, and practical limitations of pilot measurements are overlooked. Also, the base station (BS) providing the strongest signal-to-interference ratio among all BSs is always the serving BS (an ideal CA (iCA)). Consequently, the resultant analysis falls short of characterizing HetNets' coverage in practical settings. We therefore propose an analytical framework for modeling a practical CA (pCA) by considering pilot measurement, pilot sensitivity at the users, and the number of pilot measurements, KP. Using tools from stochastic geometry, we obtain the coverage with pCA in both Rayleigh and Nakagami environments. We propose an algorithm to obtain the optimal KP and its partitioning among the BSs in different tiers that maximizes the coverage. Our analysis provides key insights in designing dense HetNets. For dense networks, scale invariance achievable under iCA is shown unsustained with pCA. Also, dense HetNets are pilot-neutral, and hence their performance is not affected by pilot sensitivity. Our extensive simulations confirm the accuracy of our analysis and the proposed algorithm, and demonstrate the effect of pCA in comparison with iCA.

Most of the current research on the coverage performance of multi-stream MIMO heterogeneous networks (HetNets) has focused on a single data-stream. This does not always provide accurate results as our analysis show the cross-stream correlation due to interference can greatly affect the coverage performance. This paper analyzes the coverage probability in such systems, and studies the impact of cross-stream correlation. Specifically, we focus on the max-SIR cell association policy and leverage stochastic geometry to study scenarios, whereby a receiver is considered in the coverage, if all of its data-streams are successfully decodeable. Assuming open-loop maximum ratio combining (MRC) at receivers, we consider the cases where partial channel state information is available at the receiver. We then obtain an upper-bound on the coverage and formulate cross-stream SIR correlation. We further show that approximating such systems based on fully-correlated (non-correlated) data-streams results in a slight underestimation (substantial overestimation) of the coverage performance. Our results provide insights on the multiplexing regimes where densification improves the coverage performance and spectral efficiency. We also compare MRC with more complex zero-forcing receiver and provide quantitative insights on the design tradeoffs. Our analysis is validated via extensive simulations.

In this paper we investigate the capacity of random wireless networks in which transmitters are equipped with multiantennas. A quantized version of channel direction information (CDI) is also available, provided by the associated single antenna receivers. We adopt tools of stochastic geometry and random vector quantization to incorporate the impacts of interference and quantization errors, respectively. We first study the capacity of Aloha, and channel quality information (CQI)-based scheduling, whereby the transmissions decision in each transceiver pair depends on the strength of the CQI against a prescribed threshold. We then propose a new scheduling scheme, namely modified CQI (MCQI), by which the quantization error is effectively incorporated in the scheduling. Further we obtain the capacity of MCQI-based scheduling. Simulation results confirm our analysis and show that the proposed MCQI-based scheduling improves the capacity compared to the CQI-based scheduling and Aloha. It is also seen that the performance boost is more significant where the feedback capacity is low and the network is dense. In comparison with the case of high feedback capacity, the network capacity is not reduced by low feedback capacity in the MCQI-based scheduling. This is of practical importance since the network designer can save the feedback resources by employing MCQI-based scheduling without compromising the capacity and increasing the receivers' complexity.

The capacity performance of ICIC has been extensively studied in coordinated multi-point transmissions (CoMP). In practice however, due to limited feedback, the acquired channel direction information (CDI), which is crucial for ICIC, is often partially available. Hence one may question whether the ICIC is able to meet the Quality-of- Service (QoS) requirements. This paper considers the optimal partitioning of the feedback bits in CoMP while accounting for the inter-cell interference cancellation (ICIC). In this paper, we adopt a statistical model of QoS in CoMP by using the notion of effective capacity (EC). Utilizing EC we then formulate the system function as an optimization problem with the objective of maximizing the total EC subject to the limited feedback available to the cluster of base stations (BSs). Analytical approximations are then obtained on the EC performance which are then utilized as the base for algorithms that assign feedback bits among the user equipments (UEs) and BSs. Using simulations we then investigate the accuracy of the obtained approximations and highlight practical system designs for dealing with stringent delay requirements. Of crucial practical importance, the findings of this paper also indicates that in CoMP there is an optimal cluster size for a given feedback capacity that maximizes the corresponding EC.

We study the coverage performance of multi-antenna (MIMO) communications with maximum ratio combining (MRC) at the receiver in heterogeneous networks (HetNets). Our main interest in on multi-stream communications when BSs do not have access to channel state information. Adopting stochastic geometry we evaluate the network-wise coverage performance of MIMO-MRC assuming maximum signal- to-interference ratio (SIR) cell association rule. Coverage analysis in MIMO-MRC HetNets is challenging due to inter-stream interference and statistical dependencies among streams' SIR values in each communication link. Using the results of stochastic geometry we then investigate this problem and obtain tractable analytical approximations for the coverage performance. We then show that our results are adequately accurate and easily computable. Our analysis sheds light on the impacts of important system parameters on the coverage performance, and provides quantitative insight on the densification in conjunction with high multiplexing gains in MIMO HetNets. We further observe that increasing multiplexing gain in high- power tier can cost a huge coverage reduction unless it is practiced with densification in femto-cell tier.

In this paper adopting stochastic geometry we investigate the system performance in heterogeneous networks including multiple tiers of BSs with multiple-input single output spatial division multiple access (MISO-SDMA) technique. In the related literature on heterogeneous systems, ideal cell association (CA) rules are often considered for simplicity, where each user equipment (UE) examines a very large number of pilots across the tiers before choosing its associated base station (BS). Here we consider practical cases where UEs are restricted to examine KH≥ 1 pilots across all tiers before choosing their associated BS. We then obtain closed-form expressions for the system performance measured by the coverage probability and UE's data rate. Our analytical results provide quantitative insights on the impact of different factors on the system performance including the BS's spatial density, their transmission powers, number of transmit antennas, SIR thresholds, number of UEs served by each BS, and KH. Interestingly, we observe that increasing KHalways improves the coverage probability however, it only improves data rate up to a certain point. The data rate is then reduced by further increasing of KH. Given KHpilots in practical cases, the issue is how to allocate the pilots among different tiers. We address this issue by developing an algorithm and show that by careful allocation of available pilots, the network performance is significantly improved even in cases with small KH. Our results also indicate a fundamental tradeoff, as sharing strategies providing the best coverage performance yield very poor capacity and vice versa. Such trade-off provides a new degree of freedom in heterogeneous networks design.

This paper considers an underlay access strategy for coexisting wireless networks where the secondary system utilizes the primary spectrum to serve its users. We focus on the practical cases where there is uncertainty in the estimation of channel state information (CSI). Here the throughput performance of each system is limited by the interference imposed by the other, resulting in conflicting objectives. We first analyze the fundamental tradeoff between the tolerance interference level at the primary system and the total achievable throughput of the secondary users. We then introduce a beamforming design problem as a multiobjective optimization to minimize the interference imposed on each of the primary users while maximizing the intended signal received at every secondary user, taking into account the CSI uncertainty. We then map the proposed optimization problem to a robust counterpart under the maximum CSI estimation error. The robust counterpart is then transformed into a standard convex semi-definite programming. Simulation results confirm the effectiveness of the proposed scheme against various levels of CSI estimation error. We further show that in the proposed approach, the trade-off in the two systems modelled by Pareto frontier can be engineered by adjusting system parameters. For instance, the simulations show that at the primary system interference thresholds of -10 dBm (-5 dBm) by increasing number of antennas from 4 to 12, the secondary system throughput is increased by 3.3 bits/s/channel-use (5.3 bits/s/channel-use).

We formulate the resource allocation in the downlink of heterogeneous orthogonal frequency division multiple access (OFDMA) networks. Our primary objective is to maximize the system sum throughput subject to service and system constraints, including maximum transmit power, quality of service and per-user subchannel allocation. Due to the intercell interference, the corresponding optimization problem is, in fact, nonconvex, that cannot be solved using standard convex optimization techniques. Here we propose an algorithm based on local search method and use of penalty function to approximate the formulated constrained optimization problem by an unconstrained one. To approximate a global optimal, we set escaping procedure from the critical point based on constraint function conditions. The result shows that the proposed method might achieve optimum conditions by a hybrid of split and shared spectrum allocation. Numerical analysis indicates that the proposed algorithm outperform the other conventional methods in the scenario of the high level of inter-cell interference. Moreover, the proposed method approximates the global optimum by considering both channel gain and inter-cell interference with a fast rate of convergence.

In resource constrained wireless systems, achieving higher spectral efficiency (SE) and energy efficiency (EE), and greater rate fairness are conflicting objectives. Here, a general framework is presented to analyze the tradeoff among these three performance metrics in cooperative OFDMA systems with decode-and-forward relaying, where subcarrier pairing and allocation, relay selection, choice of transmission strategy, and power allocation are jointly considered. In our analytical framework, rate fairness is represented utilizing the α-fairness model, and the resource allocation problem is formulated as a multi-objective optimization problem. We then propose a cross-layer resource allocation algorithm across application and physical layers, and further devise a heuristic algorithm to tackle the computational complexity issue. The SE-EE tradeoff is characterized as a Pareto optimal set, and the efficiency and fairness tradeoff is investigated through the price of fairness. Simulations indicate that higher fairness results in a worse SE-EE tradeoff. It is also shown imposing fairness helps to reduce the outage probability. For a fixed number of relays, by increasing circuit power, the performance of SE-EE tradeoff is degraded. Interestingly, by increasing the number of relays, although the total circuit power is increased, the SE-EE tradeoff is not necessarily degraded. This is thanks to the extra degree of freedom provided in relay selection.

In this paper, we propose a robust transmission strategy for multi-cell networks equipped with multiple-antenna base stations (BSs) under universal frequency reuse and in the presence of channel estimation error.We propose a distributed optimization scheme, where each BS individually minimizes a combination of its total transmit power and its resulting overall interference inflicted on the users of the adjacent cells, subject to maintaining a desired quality of service at its local users.We transform the proposed scheme to a robust optimization problem for the worst case of errors and derive a semidefinite programming (SDP) using rank-relaxation.We prove that the derived SDP always yields exact rank-one optimal solutions.This is in contrast to the standard rank-relaxed SDP technique that requires an additionally high computational complexity to approximate the solutions with sufficient accuracies, required for an effective beamforming.A comparison of simulation results show that the proposed transmission strategy can expand the signal-tointerference-plus-noise-ratio operational range with significantly reduced power consumption levels at BSs and perform closely to its centralized counterpart.

We propose a novel inter-cell power allocation for multi-carrier cognitive cellular networks. The proposed scheme incorporates the network-wide primary service communication activity into sub-channel power allocation. To model the primary service activity we define sub-channel activity index (SAI). SAI is then evaluated through a simple yet efficient collaborative spectrum monitoring scheme with very low signaling overhead. Corresponding to a secondary user transmission over a sub-channel, a utility function is defined which is a decreasing function of SAI, and an increasing function of the sub-channel achievable rate. Optimal power allocation is then formulated to maximize the total secondary base station (SBS) utility, subject to SBS transmit power, and primary system collision probability constraints. The sub-optimal solutions to the non-convex optimization are then obtained utilizing dual decomposition method. Comparing with a cognitive cellular network with no signalling among the SBSs, where SBS adopts equal sub-channel power allocation, simulation results indicate a significant gain on the achievable rate. We further compare the rate performance with an ideal system in which perfect interference channel state, and spectrum sensing information are available at the SBS and a combination of underlay and overlay access techniques are adopted. Comparing to the ideal system, the proposed method requires significantly lower signaling overhead while its rate performance closely follows the ideal access.

In this paper we investigate single-hop multicast transmission in which randomly located multiple transmitters multicast packets to a cluster of receivers. Packet retransmission is known as a promising mechanism for improving the transmission reliability. Our focus is on evaluating (i) the minimum required delay (retransmission attempts), τ*, for establishing an outage-free multicast, where a transmitted packet is successfully decoded by entire nodes in the cluster, and (ii) Multicast Progress Radius (MPR) for a given delay constraint. MPR indicates how far, on average, a packet can successfully progress in a cluster without outage while the retransmission delay is restricted. Assuming general fading distribution, we derive closed-form expressions for the cumulative distribution function of τ*, and MPR. By simulations we confirmed our analysis and studied the impact of several system parameters on the MPR. Based on results of this paper we conclude that outage-free multicast requires a very large number of retransmission attempts, thus not practically achievable only based on retransmission.

Orthogonal frequency division multiple access and coordinated multipoint transmission/reception are two key techniques employed in LTE-Advanced to provide high-speed connectivity to mobile users regardless of their locations within the cells. The combination of the two techniques in a cellular network with large cells however, results in timing asynchronization. This leads to symbol timing offset (STO) and, thus, degrades users' performance. In this paper, we propose a novel user position aware (UPA) algorithm to tackle the timing offset problem by partitioning the coverage area into different zones based on users' received power requirements. Serving base stations in each zone are assigned such that their distances to a user within the zone are bounded. Hence, the time difference of signals arrived at the user is controlled and, therefore, the effect of STO is mitigated. We analyze the performance of the proposed method by deriving bounds on the STO, and signal-to-interference-plus-noise ratio (SINR) in different zones. Simulation results confirm that the proposed UPA algorithm significantly reduces the STO and improves users' SINR.

This paper considers radio resource allocation (RRA) in the downlink of an orthogonal frequency division multiple access (OFDM)-based spectrum-sharing network. The objective of RRA is to maximize the average achievable throughput subject to the primary service interference threshold and the secondary service transmit power constraint. RRA is usually implemented based on a time window T over which system parameters are averaged and checked against resource constraints. We use short-term ( T=1 time slot) and long-term ( T ≫ 1 slots) averaging as approximations to instantaneous and average constraints, respectively. RRA is also investigated for this system with long-term interference threshold and short-term interference threshold constraints. RRA optimization is a nonconvex optimization problem in which the duality principle is adopted to obtain approximate solutions. The duality gap indicates the degree of approximation in the thus-obtained solution. We prove that the duality gap corresponding to each resource allocation asymptotically decays at least with an exponential rate of T. We further show that OFDMA is, asymptotically, the optimal subcarrier assignment. We also propose a practically implementable online power and subcarrier allocation with on-the-fly channel state information measurement. An extensive simulation study has been conducted to verify the theoretically predicted duality gap behavior and to investigate the impact of different system parameters on the secondary service performance. The developed algorithms are also validated to be robust in practical settings and converge fast to theoretical bounds, and thus practically implementable.

We propose a novel scheme to design downlink beamforming vectors in a cognitive cellular network which shares radio spectrum with a primary communication system. We formulate an optimization problem which minimizes the cognitive base station transmit power and the induced interference on the primary users and keeps them below predefined system thresholds. This is subject to providing a certain level of signal-to-interference-plus-noise ratio to the secondary users. We propose an iterative algorithm to solve the optimization problem. The convergence of the proposed iterative algorithm is analytically proved. Simulation results verify that the proposed algorithm quickly converges to the optimal solution. Results also indicate that the proposed algorithm guarantees the transmit power and interference constraints. We then compare the proposed scheme with a benchmark system based on the previous methods. Comparisons show significant reduction in the total interference at reasonable cost of the cognitive base station transmit power.

We propose a novel scheme for downlink beamforming design in an underlay cognitive cellular system. The beamforming design is formulated as an optimization problem with the objective of keeping the cognitive base station transmit power as well as the induced interference on the primary users, below predefined system thresholds. This is subject to providing a certain level of signal-to-interference-plus-noise ratio (SINR) to the secondary users. We then derive the corresponding semidefinite programming form for the formulated optimization problem and propose an iterative algorithm to obtain the beamforming vectors as the optimal solutions. We further analytically show the convergence of the proposed iterative algorithm. Extensive simulations verify that the proposed algorithm quickly converges to the optimal solution. We then compare the proposed scheme with a benchmarking system defined based on the previous methods proposed in the related literature. Comparisons show that the proposed algorithm outperforms the benchmarking system and induces lower interference at the primary service receivers. It is also observed that the proposed algorithm offers a higher sum rate in comparison to the benchmarking system. Simulation results further reveal that the proposed approach effectively works at a relatively high SINR level required by secondary users and strict interference threshold set by the primary system while the benchmarking system fails to do so.

In this paper, a novel approach is proposed to obtain the optimal operating point of spectrum sensing in overlay spectrum sharing systems. The objective is to maximize the secondary service achievable capacity subject to the primary service collision probability as well as the other system and service constraints. In the related literature the miss detection probability, as the main reason of collision, is often considered to model the impact of spectrum sensing on the achievable ergodic capacity of the secondary service. In this paper, however, we directly consider the collision probability constraint in finding the optimal ergodic capacity instead of considering the miss detection probability. We then propose a framework in which other opportunities which lie in the wireless channel fluctuation and power allocation are also extracted in favor of achieved capacity. In addition to the conventional One-Shot (O-S) scheme, we also propose four novel approaches to solve the optimization problem: Modified-One-Shot (M-O-S) scheme, Multi-Shot (M-S) scheme, Conservative-Modified-One-Shot (C-O-S) scheme, and Restricted-Modified-One-Shot (R-O-S) scheme. Our studies show that the proposed formulation results in a higher secondary service capacity even when compared to the cases with very low miss detection probability. In the proposed schemes in this paper, the main decision parameter is the average (over fading) received interference at the secondary service receiver due to the primary service transmission, I, which can be simply measurable in the secondary transmitter. Extensive numerical studies are conducted to investigate various system aspects. Our studies further suggest that for very low, moderate, and very high values of \(I\) , the proper schemes are C-O-S, M-S, and M-O-S, respectively.

In this study, the authors propose a cross‐layer resource allocation scheme for orthogonal frequency multiple access (OFDM) systems based on the subcarrier channel distribution information (CDI). Here, in contrast to most of the previous works, the authors consider practical discrete rate adaptation in which rate is adapted using a predefined set of modulation levels corresponding to fading regions. The OFDM system supports ‘streaming traffic’ that requires a minimum guaranteed average delay, as well as ‘elastic traffic’ with flexible rate requirements. The main objective is to maximise the total average transmission rate of elastic users, whereas the average delay is also guaranteed for streaming traffic, all subject to the maximum average transmission power constraint. The authors then propose an algorithm which finds suboptimal fading regions, as well as suboptimal subcarrier allocation based on dual decomposition method. In the proposed method, the solution of optimisation problem remains valid, until the channel distributions and/or the packet arrival and packet length distribution of the users are changed. This significantly reduces the computational complexity since there is no need to solve the optimisation problem for each channel side information (CSI) feedback. The proposed scheme also reduces the signalling overhead since corresponding to each user the CSI is required only for the assigned subcarriers. Particularly, the proposed method is suitable for cases in which wireless channel distributions is not changed, or can be simply estimated, for example, cases where a parametric distribution is fixed and only statistics such as average and variance is changed. Using simulations, the authors study the impact of number of fading regions and packet arrival rate on the achievable rate of elastic traffic.

In this paper, we utilize stochastic geometry to analyze the primary service (PS) outage performance for spectrum sharing in Rayleigh fading environment. Using this approach, the impacts of the secondary service (SS) parameters and wireless environment on the PS outage probability are analyzed. We further obtain a closed form for the PS outage probability. The maximum SS transmitter node density for a given outage probability constraint of the PS is then obtained. We also investigate the impact of secondary spectrum sensing on the PS outage probability. A novel approach is further proposed that provides tight approximation for the PS outage probability. The results of the proposed approach are then validated through analysis and simulations. We then consider power control in the secondary network and show that the truncated channel inversion power control significantly decreases the PS outage probability. Cases with centralized and decentralized cooperative spectrum sensing are also studied, and their corresponding PS outage probabilities are analyzed. Mean spatial throughput of the SS is also analyzed. We further investigate the impact of the PS outage constraint on the spatial throughput of the SS. Extensive simulations confirm our analytical derivations.

In this paper, we propose an interference management method for underlay spectrum sharing and evaluate its performance. In this method the secondary service has been facilitated by granting passive access to the power control signalling transmitted by the primary network base station. To exploit both slow shadowing and fast fading, the proposed method performs secondary service power management in two phases, each in different time-scales: rate optimal power allocation phase and interference reduction power adjustment phase. In the longer time-scale, rate optimal power allocation phase adaptively allocates the secondary transmit power exploiting the medium-scale channel variations (shadowing effect) of the secondary channel to maximize its capacity. In the shorter time-scale, interference reduction power adjustment phase exploits the power control commands transmitted in the primary network to adaptively adjust secondary service transmission power for reducing the effects of the secondary service transmission on the Quality-of-Service (QoS) of the primary service network. The main advantage of this method which is referred to as Adaptive Multiple Time-Scale Power Allocation (AMTPA) is that it does not require direct signaling between the two systems. We further present AMTPA analytical performance evaluation results. Practical considerations are also presented regarding the primary network requirements and its power control feasibility after adopting AMTPA in the secondary network. Extensive simulation results indicate significant improvement in the system performance by using AMTPA. Using simulations we also show how one can set AMTPA parameters so that a certain level of QoS in the primary network is satisfied.

In this paper, we consider an underlay spectrum sharing system and propose utilizing discrete rate Trellis Coded Modulation Orthogonal Frequency Division Multiple Access (TCM-OFDMA) technique in the secondary system. Downlink radio resource allocation schemes are then proposed for such system. Simulation results indicate that using the proposed scheme, we can significantly increase the sum rate compared to conventional uncoded OFDMA schemes with only a moderate increase in system complexity. It is also shown that in cases where the secondary network is unable to achieve higher rates by increasing the total power and/or interference threshold, utilizing TCM-OFDMA acts as a smart alternative.

This paper proposes a new utility-based fairness criteria for radio resource allocation in underlay CDMA cognitive radio networks based on harmonic mean concept. Then joint rate and power allocation problem is considered for secondary users subject to the QoS and interference threshold constraints. It is shown that the proposed approach yields a better balance between throughput and fairness compared with conventional fairness criteria, namely max-min and proportional fairness.

In a dynamic spectrum sharing system, secondary users (SUs) attempt to maximise their throughput while preserving a given level of quality of service (QoS) for primary users (PUs). In doing so, the secondary network monitors the spectrum and decides on spectrum availability, which at times and for various reasons, may be erroneous. If spectrum is sensed as available, the secondary network selects an appropriate spectrum access strategy, and adjusts other communication parameters such as transmit power levels. In this study, the authors analyse primary service outage degradation caused by secondary access with non-ideal spectrum sensing. For different spectrum access strategies, namely, the overlay and the modified underlay spectrum access (MUSA), the authors derive a closed-form expression for the maximum outage probability degradation (MOD) in the presence of spectrum sensing errors and fading and show how adjustments by secondary service can result in attaining the desired QoS for PUs. Besides, for a given acceptable MOD in the primary network, the authors obtain a lower bound on the achievable expected rate of the secondary service in Nakagami-m and Rayleigh fading channels. Simulations confirm the analysis and show that MUSA considerably increases the secondary service rate, particularly when the activity of primary service is above 50%.

In this article, radio resource allocation in underlay spectrum sharing based on the orthogonal frequency-division multiple access is studied. A cellular-based secondary service is considered in which the licensed spectrum is opportunistically accessed provided that the imposed interference at the primary service receivers because of secondary service transmissions stays below an interference threshold constraint. The main objective here is to maximise the sum capacity of the secondary service and to find the optimal allocated power, subcarrier and rate across all subcarriers and different secondary users. Three different scenarios are considered based on the availability of the channel state information (CSI) between the secondary service base station and primary receivers. The optimal resource allocation for the case of accurate CSI between the secondary base station and the primary receivers is obtained. To manage more practical situations, in the second considered scenario the authors assume that only the channel distribution information information between the secondary base station and the primary receivers is available at the secondary service base station. In the third scenario the authors further propose a novel algorithm, which controls the collision incidences caused by secondary transmissions owing to lack of CSI in secondary base station. Simulation analyses are also conducted in order to investigate the system performance based on the proposed resource allocation algorithms.

In this study, the authors propose a novel channel and queue aware algorithm for allocating power and subcarrier to users in orthogonal frequency division multiple access (OFDMA) networks. The proposed algorithm utilises a utility function to simultaneously balance and improve the efficiency and fairness of radio resource allocation. In contrast to the conventional approaches in the literature, in which it is assumed that the OFDMA system is able to support a continuous set of bit rates, here, in the system model the authors consider the fact that in practical OFDMA systems only a limited set of bit rates are supported. Furthermore, the authors do not consider the full buffer assumption and note that in practice a user scheduled for transmission might not always have data to transmit. By formulating the radio resource allocation the authors then show optimal bit loading results in a greedy algorithm that employs both bit removal and bit filling procedures. The solutions are developed in the framework of a matroid theory. The authors then analyse the average system throughput and investigate the performance of the proposed algorithm through simulations. Comparisons to similar approaches are also conducted which indicates significant performance improvement.

Abstract In this paper, we propose a novel cooperative relaying scheme with multiple relays for frequency selective wireless environment. In our proposed scheme, the frequency selective wireless channel is divided into flat fading sub‐channels. Cooperative relaying is then employed over each sub‐channel to improve the system diversity order. We then investigate the asymptotic behavior of the outage probability and show that the proposed scheme achieves full diversity order in both amplify and forward (AF) and adaptive decode and forward (ADF) relaying scenarios. Furthermore, we propose a power allocation strategy to minimize the system outage probability. Simulation results confirm our analysis and show that the proposed power allocation method outperforms uniform power allocation. Copyright © 2010 John Wiley & Sons, Ltd.

In this study, the authors propose two high spectral efficient relaying protocols with low communication overhead including: the priority-based relay selection (PRS), and the priority-based relay selection with incremental transmission (PRSIT). Relay selection and scheduling are integrated in the proposed protocols to achieve full diversity order as well as high spectral efficiency. The authors then define the communication overhead per allocated time slot to a user as the number of required signalling bits for channel estimation and implementing corresponding communication procedures. In this study, the authors show that their proposed protocols have much lower communication overhead comparing with other high spectral efficient cooperative protocols such as opportunistic relaying (OR) and OR with incremental transmission while their achieved diversity-multiplexing trade off performances are the same as those protocols. The authors further show that the average communication overhead for the PRS and PRSIT is a logarithmic function of the number of users while it is a linear function in OR and OR with incremental transmission. Simulation results also show that however, the authors proposed protocols impose much lower communication overhead, they either outperform or act closely to the existing cooperative protocols in the outage probability.

In this study, the authors formulate the optimal radio resource allocation for OFDM-based relay networks with heterogeneous delay requirements. The authors consider streaming traffic that requires a maximum guaranteed average delay and elastic traffic with flexible rate requirements. The main objective is to maximise the total transmission rate of elastic users, while average delay constraint for streaming traffic is satisfied. In the proposed formulation we also consider transmit power constraint for the base station as well as each relay. The authors then propose an algorithm based on dual approach to find the optimum subcarrier, relay assignment and power allocation. Using simulations, the authors evaluate the impact of streaming traffic on the total rate of elastic users for different number of relays and various power constraints.

In automatic retransmission request (ARQ) based systems, L time retransmissions are allowed. The achieved performance of such systems is closely related to the channel dynamics during different retransmissions. In this paper, we present a generalized dynamic channel model which covers both long term, and short term static channel as the special cases. We then analyze the diversity multiplexing trade off (DMT) for ARQ based non cooperative communication and ARQ based opportunistic cooperative communication (OCC) over Nakagami-m channels. The analysis in this paper studies the impact of channel dynamics on the DMT performance for non cooperative and cooperative systems. In the analysis we consider two non cooperative communication systems including random user selection (RUS), and best user selection (BUS). We show that depending on channel dynamic conditions, while all the studied schemes enjoy the time diversity gain, BUS exploits multi-user diversity gain in its DMT performance. Also, DMT performance of OCC is significantly high due to cooperative diversity gain. In particular, we show that for RUS and OCC, as the channel dynamics conditions are changing from long term to short term. The DMT performance is significantly improved until the performance is maximized in the case of short term static channels, however, this DMT behavior is different for BUS. Two retransmission approaches including packet combining (PC) and packet accumulating (PA) are also studied and their impacts on DMT performance are analyzed for cooperative and non-cooperative schemes.

Here our focus is on the downlink radio resource allocation in underlay spectrum sharing based on OFDMA technology. Both continuous and discrete rate strategies are investigated. We consider the practical case in which for the wireless channel between the secondary base station and secondary users only partial channel state information (CSI) is available at the secondary base station. We formulate the resource allocation problem in the secondary network as an optimization problem in which the objective is to maximize the secondary users weighted sum rate. Two main constraints at the secondary base station are the maximum total transmission power, and the primary service collision probabilities. The only available a priori information is the channel distribution information (CDI) for the channel between the secondary base station and the primary receivers. Since the optimal radio resource allocation is non convex we utilize dual optimization method to obtain suboptimal solutions. The computational complexity due to the constraints in the original radio resource allocation is then reduced by exploiting system specifications and substituting the original constraints with the equivalent constraints on the transmission power and rate. Simulations studies are conducted to investigate the impact of the different system parameters. We also compare the proposed algorithm with the conventional radio resource allocation and show that by the proposed algorithm we are able to enforce the collision probability constraint in the primary service which in return results in a slight decreasing in the sum rate of the secondary system. Furthermore, we show that the proposed schemes are able to keep the outage probability imposed by imperfect CSI below a given threshold.

In this paper, we utilize stochastic geometry to analyze the primary service outage performance for spectrum sharing in Rayleigh fading environment. Using this approach, the impacts of the secondary service parameters as well as the wireless environment on the primary service outage probability are analyzed. We further obtain a closed form for the primary service outage probability based on the transmit power of the secondary service as well as miss detection probability of the spectrum sensing. Furthermore, we obtain the maximum secondary service transmitter node density for a given outage probability constraint of the primary service. We also derived an upper bound to the achievable capacity of the primary service. Simulations results confirm the analytical derivations.

In this paper we propose a novel approach to obtain the optimal operating point of the spectrum sensing in overlay spectrum sharing. The operating point of the spectrum sensing is specified by the receiver operating characteristic (ROC) curve which is a fundamental spectrum sensing behavior that relates its false alarm and missed detection probabilities. Our objective is to maximize the ergodic capacity of the secondary service in the presence of inaccurate spectrum sensing. We formulate an optimization problem to obtain the optimal transmission power strategy and ROC operating point of the spectrum sensing. Constraints of the considered optimization problem include the secondary service maximum transmission power as well as the maximum primary service collision probability. Two iterative sub-optimal schemes are then proposed to find the solutions of the optimization problem. Numerical results show that both proposed schemes quickly converge after a few iterations. Moreover, it is observed that the proposed schemes significantly outperform other conventional approaches.

In this study, the authors propose a cross-layer resource allocation scheme for push to talk (PTT) service over orthogonal frequency division multiple access (OFDMA)-based networks. In our modelling, the authors consider two traffic types: streaming traffic, which requires a maximum guaranteed average delay and elastic traffic with flexible rate requirements. PTT traffic is also considered as a streaming traffic with more flexible delay requirements comparing to conventional streaming traffic. The authors consider queue state information as well as channel state information in a cross-layer framework to maximise the total transmission rate of the elastic users, while average delay constraint for streaming users, and maximum transmission power constraint are satisfied. An algorithm is then proposed based on dual decomposition method to obtain the subcarrier assignment and power allocation for each user. Using simulations, the authors then evaluate the impact of the streaming PTT traffic and other system parameters on the total rate of elastic users.

In this paper, we consider DS-CDMA/OFDM spectrum sharing systems and obtain the achievable capacity of the secondary service under different subchannel selection policies in the fading environment. Subchannel selection policies are divided into two categories: uniform subchannel selection, and nonuniform subchannel selection. Uniform subchannel selection is preferred for cases where a priori knowledge on subchannels state information is not available at the secondary transmitter. For cases with available a priori knowledge on subchannels state information, we study various nonuniform subchannel selection policies. In each case, we obtain the optimum secondary service power allocation and the corresponding maximum achievable capacity. Then we present results on the scaling law of the opportunistic spectrum sharing in DS-CDMA/OFDM systems with multiple users. Numerical results show that the optimal subchannel selection is based on the minimum value of the subchannel gain between the secondary transmitter and the primary receiver.

In this paper, we analyze the achievable capacity of the secondary service for overlay and underlay access strategies. We then propose a novel mixed access strategy in which in contrast to the underlay strategy, the secondary service transmits during the idle periods without considering the interference threshold constraint. In contrast to the overlay strategy, mixed strategy makes transmission during the busy periods with a probability p_a subject to satisfying the interference threshold constraint. Parameter p_a is a secondary service parameter, which can be adjusted based on the spectrum status. Moreover, we show that the secondary service can adjust p_a to select appropriate access strategy with the objective of maximizing the achieved capacity based on the interference at the secondary service receiver, I, imposed by the primary service transmitter. The proposed spectrum-sharing technique developed in this paper based on I significantly reduces the system complexity comparing to the system in which for spectrum sharing, the imposed interference at the primary receiver is required. We further suggest a simple power allocation scheme for the mixed strategy that its achieved capacity is very close to the maximum achievable capacity of the secondary service.

In this paper, we analyze the outage probability of coded cooperation in opportunistic relaying (OR-CC) and distributed space-time coding (DSTC-CC) cooperative communication systems at arbitrary signal to noise ratios (SNRs) and number of available relays assuming Rayleigh fading channels. Furthermore, we obtain lower and upaper bounds for the diversity multiplexing tradeoff (DMT) for OR-CC and DSTC-CC schemes in the cases where the source node is/is not included in the cooperation. Simulation results confirm our analysis.

In this paper, we propose a low complexity heuristic algorithm for radio resource allocation in orthogonal frequency division multiple access (OFDMA) systems based on subcarrier channel distribution information (CDI). We consider practical rate adaptation in which rate is adapted using a predefined set of modulation levels, which is in contrast to previous works that consider continuous rate. We formulate the problem of resource allocation in an OFDMA system with streaming traffic which requires a minimum guaranteed average rate, and elastic traffic with flexible rate requirements. The main objective is to maximize the total transmission rate of the elastic users, while average rate guarantees for streaming traffic as well as maximum transmission power constraints are satisfied. To reduce the computational complexity, we decouple the resource allocation problem into two sub-problems corresponding to two traffic types. For streaming traffic, we optimally allocate subcarrier and power and then the remaining radio resources including the unassigned subcarriers and unallocated transmission power of the base station are optimally allocated to the elastic traffic. We then develop a heuristic algorithm based on Lagrangian method to obtain an approximation of the optimal solution. Using simulations, we study the impact of number of fading regions. Simulations also provides insight on the trade-off between the number of streaming and elastic users.

In this letter, a joint transmit scheduling and dynamic sub-carrier and power allocation method is proposed to exploit multi-user diversity in downlink packet transmission in an OFDM wireless network with mixed real-time and non-real-time traffic patterns. To balance efficiency and fairness and to satisfy the QoS requirements of real-time users, we utilize a utility-based framework and propose a polynomial-time heuristic algorithm to solve the formulated optimization problem. The distinguishing feature of the proposed method is that it gives in one shot, the transmission scheduling, the sub-carriers assigned to each user, and the power allocated to each sub-carrier, based on a fair and efficient framework while satisfying the delay requirements of real-time users.

When utilizing spectrum sharing in wireless channels, a secondary service may access the spectrum allocated to the primary service while this frequency band is under-utilized. The availability of the frequency band to the secondary user is a function of the activity of the users in the primary network. In this paper, we analyze the achievable capacity of the secondary service which employs opportunistic spectrum access (OSA) over a fading environment based on the primary network activity. We categorized OSA methods into Access Limited OSA (AL-OSA), and interference limited OSA (IL-OSA) schemes. In AL-OSA the spectrum is shared with the secondary service in circumstances in which the primary service is totally inactive however, in IL-OSA access to the spectrum is allowed subject to an interference threshold. For both cases we develop analytical frameworks to analyze the impact of the primary network activity on the achievable capacity of the secondary service. Simulation results confirm our analysis and also show that in cases where higher activity is in the primary network, IL-OSA is the more appropriate OSA method. For a less active primary network, AL-OSA is shown to performs better with respect to the achievable capacity.

This paper considers resource allocation in OFDM wireless networks with mixed real-time and non-realtime traffic patterns. We employ a utility-based framework to balance efficiency and fairness, while satisfying QoS requirements of real-time users. A utility function is assigned to each user over each sub- carrier; this indicates the transmission priority for the user/sub-carrier pair based on the achievable rate and experienced delay, subject to delay and power constraints. The proposed scheduler gives in one shot the sub-carrier and power allocation, plus transmission scheduling for each time-slot. Simulation results indicate that while satisfying real-time users' delay requirements, the proposed method achieves a significant performance improvement in terms of overall throughput and fairness.

In this paper, we analyze DS-CDMA/OFDM spectrum sharing system based on opportunistic spectrum access (OSA). In this system, the primary network air interface is based on DS-CDMA, in which the system performance is limited by a maximum total received interference. The total interference, among other things, is a function of the primary users' communication activity. In OSA, part of this interference is considered to be created by the secondary service, this portion is called interference threshold. Decreasing the activity of the primary users results in a higher interference threshold, and at the same time, creates less interference at the secondary service receiver; thus the achievable capacity of the secondary service is increased. In this paper, we analytically obtain the maximum achievable capacity of the secondary service over fading channel. Our analysis reveals the dependency of the achievable capacity and the users' activity in the primary network. A direct consequence of our analysis is that exploiting the temporal variations of the available radio resource caused by the users' activity in the primary network can significantly increase the maximum achievable capacity. Simulation results confirm our analysis.

Motivated by the results in (K. Navaie et al., 2006) on the self-similarity of the downlink interference in heterogenous service DS-CDMA networks, in this paper, we propose a model-based linear adaptive-predictive method to estimate the level of interference for optimizing the system throughput and minimizing the delay for non-real-time data transmission. We use a fractional Gaussian noise (fGn) model in an appropriate time-scale to represent the self-similarity in the downlink interference. The estimated interference is utilized to allocate the available power to non-real-time services. In doing so, we use a utility-based optimization scheme and dynamic programming for time-domain optimal scheduling of non-real-time traffic. Simulation results validate the fGn model and show a substantial improvement in the delay fairness and a significant increase in the average cell throughput using our proposed scheme; and confirm that the interference model is valid for a broad range of arrival rates of non-real time traffic.

In this paper using a utility-based approach, down-link packet transmission in a CDMA/TDMA cellular network is formulated as an optimization problem. A utility function corresponds to each packet served by a base-station that is an increasing function of the packet experienced delay and the channel gain, and a decreasing function of the base-station load. Unlike previous works, in this paper, the optimization objective is to maximize the total network utility instead of the base-station utility. We show that this optimization results in joint base-station assignment and packet scheduling. Therefore, in addition to multi-user diversity, the proposed method also exploits multi-access-point diversity and soft capacity. A polynomial time heuristic algorithm is then proposed to solve the optimization problem. Simulation results indicate a significant performance improvement in terms of packet-drop-ratio and achieved throughput.

In this paper we present network-centric and user- centric routing mechanisms designed for the wireless world initiative new radio (WINNER) multi-hop cellular air interface. We study the pros-and-cons of each mechanism and describe the interactions between routing and main radio resource management (RRM) functionalities.

In this paper we study the multi-user diversity gain in the downlink of single-hop and multi-hop infrastructure-based networks. We propose a base-station coordinated cooperative relaying method, cooperative induced multi-user diversity relaying (CIMDR), to overcome the fundamental limitations on the average achieved net throughput per-user. In the proposed method, multi-user diversity is induced and then exploited in a 2-hop relaying scheme to improve per user achieved data throughput. We show that by using the proposed method, the throughput per-user and the packet-drop-ratio are significantly improved

In this paper, we show that the total downlink interference in heterogeneous wireless DS-CDMA networks follows an asymptotically self-similar (as-s) process. The as-s model is valid for the interference under certain conditions on channel variations and traffic characteristics that cover a range of practical situations. We derive these conditions and generalize earlier results, obtained for data-centric cellular networks, to heterogeneous cellular networks. Simulation results for actual cases confirm analytical results, and show that non-uniform spatial distribution of users and their soft-hand-off status do not affect the nature of this self-similar process. Furthermore, we discuss the impact of the analysis developed in this paper in designing appropriate mechanisms for controlling radio resources in such networks.

In this paper, we develop a cross-layer model for downlink interference in heterogeneous DS-CDMA wireless cellular networks. In this model, interference is described as a function of application layer parameters (traffic characteristics) and physical layer variations (channel characteristics). We show that for a heterogeneous service DS-CDMA network, downlink interference is a second-order self-similar process and thus has long-range dependence. We then use the predictive structure of total downlink interference to maximize non-realtime data throughput. We use fractional Gaussian noise (fGn) to model the self-similarity of downlink interference. In the proposed method, the base-station uses an optimal linear predictor, based on the fGn model, to estimate the level of interference. The estimated interference is then used to allocate power to users. To maximize data throughput, we use time domain scheduling. The simulation studies confirm the self-similarity of downlink interference and validate the fGn model. The simulation results also show a substantial performance improvement using the proposed predictive-adaptive scheme and confirm that the interference model is still valid after applying the proposed method.

In this paper, using the dynamic pricing platform, a novel framework for downlink resource allocation in heterogeneous cellular CDMA networks is proposed. For each user, we define a utility that is a function of channel status and delay condition of that individual user as well as network load status. The network utility is then defined as the summation of the users' achieved utilities. We solve downlink resource allocation problem through maximization of total network utility. This approach results in a suboptimal base-station assignment scheme which-unlike previous work-is network optimal instead of cell optimal. We then show that optimal base-station assignment is a multidimensional multiple-choice Knapsack problem (MMKP). Since MMKP is NP-Hard a polynomial-time suboptimal heuristic algorithm is then employed to develop an efficient base-station assignment.