Content caching at femto base stations (F-BSs) enhances user experience. In practice, the storage size of F-BSs is often minuscule compared to the size of the content library, which calls for effective content placement strategy aligned with user association (UA), networking issues, and possible content retransmissions. The common assumption is to associate user equipments with the closes F-BS that holds the requested content—content-centric user association (CC-UA). We argue that CC-UA could deteriorate hit rate and energy efficiency (EE), and then propose three cache-agnostic UA schemes to tackle this issue: baseline (CA-B), Macro-to-femto (CA-M2F), and femto-to-femto (CA-F2F). Under CA-B if the requested content is not found at the cache, it is retrieved via backhaul. The CA-M2F scheme uses the communication between Macro-BSs and F-BSs to improve the performance. Finally, the CA-F2F scheme uses the direct F2F communication paradigm allowing F-BSs to share contents between themselves on-demand. By the aid of stochastic geometry we model and analyze all these UA schemes and derive associated hit rate and EE performances based on main system parameters. We then utilize the analysis to study the performance of the developed UA-C schemes under several (heuristic) probabilistic content placement strategies. For a chosen choice of the content placement strategy, the numerical results confirm that CA-F2F and CA-M2F outperform CC-UA and CA-B by large margins. For example, we observe that via CA-F2F one can achieve 1200 percent growth of EE compared to CC-UA.

We address the mobility management of an autonomous UAV-mounted base station (UAV-BS) that provides communication services to a cluster of users on the ground while the geographical characteristics (e.g., location and boundary) of the cluster, the geographical locations of the users, and the characteristics of the radio environment are unknown. UAV-BS solely exploits the received signal strengths (RSS) from the users and accordingly chooses its (continuous) 3-D speed to constructively navigate, Le., improving the transmitted data rate. To compensate for the lack of a model, we adopt policy gradient deep reinforcement learning. As our approach does not rely on any particular information about the users as well as the radio environment, it is flexible and respects the privacy concerns. Our experiments indicate that despite the minimum available information the UAV-BS is able to distinguish between high-rise (often non-line-of-sight dominant) and sub-urban (mainly line-of-sight dominant) environments such that in the former (resp. latter) it tends to reduce (resp. increase) its height and stays close (resp. far) to the cluster. We further observe that the choice of the reward function affects the speed and the ability of the agent to adhere to the problem constraints without affecting the delivered data rate.

Power allocation in spectrum sharing systems is challenging due to excessive interference that the secondary system could impose on the primary system. Therefore, an interference threshold constraint is considered to regulate the secondary system's activity. However, the primary receivers should measure the interference and inform the secondary users accordingly. These cause design complexities, e.g., due to transceiver's hardware impairments, and impose a substantial signaling overhead. We set our main goal to mitigate these requirements in order to make the spectrum sharing systems practically feasible. To cope with the lack of a model we develop a coexisting deep reinforcement learning approach for continuous power allocation in both systems. Importantly, via our solution, the two systems allocate power merely based on geographical location of their users. Moreover, the inter-system signalling requirement is reduced to exchanging only the number of primary users that their QoS requirements are violated. We observe that compared to a centralized agent that allocates power based on full (accurate) channel information, our solution is more robust and strictly guarantees QoS requirements of the primary users. This implies that both systems can operate simultaneously with almost-zero inter-system signaling overhead.

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.

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.

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.

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.

We analyze the performance of a multiple-input multiple-output multiplexing system in a Poisson bipolar network under line-of-sight/non-line-of-sight (LOS/NLOS) path-loss model and zero-forcing beamforming at receivers. The capacity and outage performance of such a configuration, commonly under the standard path-loss model, have been broadly analyzed; yet little is known about its local transmission delay with considering the traits of LOS/NLOS model. As the effective fading power gain on each data stream is Nakagami-type, and due to the interference correlation across data streams of a link as well as the retransmission attempts, the evaluation of the mean delay is more involved than the capacity/coverage evaluation. Our rigorous analysis provides a lower bound and an approximate upper bound on the mean delay as the functions of density, multiplexing gain, transmission activity, and LOS/NLOS model, which sheds some light on the effect of the LOS component in circumventing the possible divergence of the mean delay. Simulations show the lower bound is very accurate and demonstrate several aspects of multiplexing, path-loss traits, and interference correlation on the mean delay. Exploiting the analysis, we further explore the optimization of effective spatial throughput of the network.

In multicast networks it is necessary to secure the successful reception of the packet by all the intended receivers, which often calls for the retransmission of the packet up to a number of times. When each receiver is subject to signal deterioration due to fading and unrestrained inter-cluster interference, retransmissions however renders unacceptable large delay that eventually undermines the utility of multicasting. In this paper, we attempt to understand the impact of a practically attractive multi-antenna communication scheme viz. antenna selection combining (ASC) on enhancing the performance of a random multicast network under delay requirement. Since during retransmission attempts the transmitters and the receivers in each cluster likely stay stationary, igniting substantial interference correlation across antennas, the potential diversity of ASC may be dramatically destructed. We, here scrutinize the effect of this diversity loss on the multicast performance by analytically evaluating the multicast coverage efficiency (MCE), which measures the percentage of receivers who experience multicast coverage during the retransmission procedure. We provide a number of approximations on MCE as the main system parameters, and further study their accuracies. Our simulations show that ASC has benefits in improving MCE, however not as pronounced as one may otherwise experience when interference is de-correlated across antennas and retransmission attempts.

We consider multiple-input multiple-output multiplexing (multi-stream) systems in a spatial Aloha network. The active transmitters are distributed with accordance of Poisson point process with given density and each of which has its own receiver. We mainly focus on zero-forcing beamforming (ZFBF) at the receiver and assume the transmitters do not have access to channel state information. The capacity and outage performance of such network has broadly analyzed in the literature, while a little is known about its delay performance, which is investigated in this paper. Delay measures the number of attempted retransmissions before successful reception of all transmitted data streams of a typical communication link. Due to Nakagami-type fading per data stream, the SIR correlation among data streams of each communication link and among each retransmission attempt - which is due to the common location of transmitters - the evaluation of mean delay is substantially complex. Our rigorous analysis provides a lower- and an upper-bound on the mean delay as the function of the transmitter's density, multiplexing gain, transmission activity, and number of receiver's antennas. We conduct simulations to evaluate the accuracy of the analysis. Important insights regarding the impact of transmission activity and multiplexing gain on the mean delay is highlighted.

In this paper we analyze and design a Heterogenous cellular networks (HetNets) where base stations (BSs) are equipped with multi-antennas, serving a number of singleantenna user equipments (UEs) in downlink. We focus of space division multiple access (SDMA) whereby (i) zero-forcing beamforming vectors at the BSs are chosen based on the quantized channel direction information (CDI) and (ii) scheduled data rates are specified adaptively based on the quantized channel quality information (CQI). Adopting tools of stochastic geometry, we firstly, provide a tight approximation of the coverage performance of quantized SDMA beamforming in a closed-form that encompasses impacts of feedback capacity, density of BSs, and SIR thresholds under max-SIR cell association rule. Assuming CQI of each UE is its experienced SIR, we then exploit our analysis to devise a proper optimization problem to adaptively share feedback capacity between tiers, and also between CDI and CQI feedback. We do so by introducing net spatial throughput (NST) as the main performance metric, which is defined as the spatial throughput minus uplink penalty of feedback capacity per area per frame. Our numerical results show that serving more UEs calls for higher capacity of feedback channel without delivering strong NST. We further observe that one way to coup with such a weak performance is to densify the network in tier 2 wherever path-loss exponent is adequately large, e.g., installing many femto-cells in indoor.

In a stochastic geometry evaluation of cellular networks it is common to consider single-exponent power-law path-loss model. This is however far from reality, as the close-by base stations (BSs) are more likely to be in line-of-sight (LOS) mode, while farer BSs often exhibit non-LOS (NLOS) propagation effects with much larger path-loss exponent. We in this paper set goal to incorporate such realistic propagation model into the analysis of multiple-antenna (MIMO) multiplexing systems, which has not treated in the literature. Specifically, we consider zero- forcing beamforming (ZFBF) at the receiver while the transmitter has not access to channel state information, maximum signal-to- interference ratio (ZIR) cell association, and scenarios that the QoS implies the reception of the all transmitted data streams of a communication link to distinguish coverage. We derive a closed-form of the coverage probability. As it imposes dramatically huge computational complexity, we further propose an easy-to-compute upper-bound on it, which its accuracy is investigated against simulations. We notice that there is a density of BSs that results in the best coverage probability, which is accurately obtained by our analysis. While ultra-dense configurations have very poor coverage, it yields proportional growth of spectral efficiency with density. We finally highlight several important compromises between coverage and spectral efficiency versus multiplexing gain and density of BSs, one may take into consideration when it comes to the design of the network.

We consider multiple-antenna (MIMO) multiplexing (multi-stream) systems in a spatial Aloha network under quality of service (QoS) constraints. The active transmitters form a bipolar Poisson point process with given density, each with its own communicating receiver. The QoS requirement is specified in terms of the asymptotic decay rate of the buffer occupancy, characterizing the statistical queuing constraint. Assuming open-loop zero-forcing beamforming (ZFBF) at the receiver, we therefore evaluate the effective capacity (EC), which is the throughput metric subject to a given queuing delay requirement. Due to Nakagami-type fading per data stream as well as the SIR correlation among data streams of each communication link- stemmed from the common location of transmitters across data streams-the evaluation of EC is, however, substantially complex, and has not yet considered in the related literature. We in this paper provide a number of approximations that formulate EC as a function of multiplexing gain, the number of antennas, QoS requirement, density of transmitters, and path- loss exponent. Approximations are numerically friendly, and their accuracy are corroborated against simulations. It is seen that for given QoS requirement, there is a multiplexing gain that optimizes EC. We further observe that for less stringent delay requirement, large multiplexing gain is preferable, while by increasing delay exponent it is advocated to shift the operating point toward the single-stream communication.

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.

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.

Cardinality estimation is of fundamental importance in various wireless communication applications. The performance of any adaptive medium access control in the uplink channel is in fact affected by its accuracy. This paper provides a fresh look at this fundamental problem, and proposes a novel scheme for fast and accurate cardinality estimation. This scheme utilizes the experienced outage probability in detecting IDs of the devices in the uplink. It is observed that for practically relevant values of Signal-to-Interference-plus-Noise Ratio (SINR) threshold, e.g., β ≤ 10 dB, and spreading sequence length, e.g., Nc≥ 7, the base station is able to estimate the true cardinality with vanishing error in only one shot, even if the network is so populated, e.g., the number of active devices N ≥ 100. Otherwise, one may apply the proposed method in couple of consecutive shots such that in each of which portion of the cardinality is estimated.

In future, a massive number of devices are expected to communicate for pervasive monitoring and measurement, industrial automation, and home/building energy management. Nevertheless, such Machine-to-Machine (M2M) communications are prone to failure due to depletion of machines energy if the communication system is not designed properly. A key step in building energy-efficient protocols for large-scale M2M communications is to assess, model or characterize a network energy consumption profile. To meet this need, we develop a theoretical and numerical framework to evaluate the cumulative distribution function (CDF) of the total energy consumption by fully exploiting the properties of stochastic geometry. Unlike the other existing approaches, we model the transmission energy as a function of transmission power, packet size, and link affordable capacity that is a logarithmic function of experienced Signal to Interference plus Noise Ratio (SINR). Since it is very difficult, if not impossible, to derive a closed-form expression for the CDF, we derive numerically computable first- and second-order moments of energy consumption. Applying these moments we then propose Log-normal and Log-logistic distributions to approximate the CDF. Our simulation results show that Log-logistic almost precisely approximates the exact CDF.

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.

Providing direct communications among a rapidly growing number of wireless devices within the coverage area of a cellular system is an attractive way of exploiting the proximity among them to enhance coverage and spectral and energy efficiency. However, such device-to-device (D2D) communications create a new type of interference in cellular systems, calling for rigorous system analysis and design to both protect mobile users (MUs) and guarantee the connectivity of devices. Motivated by the potential advantages of cognitive radio (CR) technology in detecting and exploiting underutilized spectrum, we investigate CR-assisted D2D communications in a cellular network as a viable solution for D2D communications, in which devices access the network with mixed overlay-underlay spectrum sharing. Our comprehensive analysis reveals several engineering insights useful to system design. We first derive bounds of pivotal performance metrics. For a given collision probability constraint, as the prime spectrum-sharing criterion, we also derive the maximum allowable density of devices. This captures the density of MUs and that of active macro base stations. Limited in spatial density, devices may not have connectivity among them. Nevertheless, it is shown that for the derived maximum allowable density, one should judiciously push a portion of devices into receiving mode in order to preserve the connectivity and to keep the isolation probability low. Furthermore, upper bounds on the cellular coverage probability are obtained incorporating load-based power allocation for both path-loss and fading-based cell association mechanisms, which are fairly accurate and consistent with our in-depth simulation results. Finally, implementation issues are discussed.

A message passing (MP) algorithm for resource allocation (RA) in an Orthogonal Frequency Division Multiple Access (OFDMA) based spectrum sharing system is developed in this paper. We derive optimal power and subcarrier allocations. We further shed light on advantages of the MP algorithm particularly against the dual solution and highlight its suitability in reducing the computational burdens for practical configurations. It is observed that MP algorithm converges only after two iterations compared to 400 required iterations in the dual case. This considerably reduces the corresponding computational time, which in turn results in much lower consumed processing energy. The saved processing energy and time can then be exploited for enhancing the scheduled data rate especially when the number of users is high.

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.

This paper investigates the ergodic sum capacity of a spectrum-shared Multiple Access Channel (MAC). We assume that the secondary service (SS) only knows the channel distribution information (CDI) between its transmitters and the primary receivers. Availability of CDI results in collision incidences at the primary receivers because of conflicting levels of intolerable interference. We introduce the concept of collision probability constraint to manage the unexpected QoS degradation of primary service in the secondary resource allocation (RA). This RA problem is inherently difficult to solve and its objective function is not necessarily convex. Two well-known approaches, called Iterative Approach (IA) and Analytical Approach (AA), each with several cases/categories, are then used to find solutions. IA solves the problem iteratively by reconstructing convex optimization problems from the original (non-convex) one in a number of iterative loops until the collision probability constraints are satisfied. IA is shown to converge quickly to a suitable solution. Furthermore, by using a control parameter, the system designer can make a tradeoff between the speed of convergence and the ergodic sum capacity. AA, on the other hand, solves the RA problem by suggesting tractable versions of collision probability constraints. Unlike IA, AA does not require extra signaling between transmitters and the base station to tune parameters, thus facilitating the implementation of SS. Our in-depth simulations have shown the proposed approach to yield lower spectral efficiency than IA.

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.

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 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.

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.

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.