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The densification of the orthogonal frequency division multiplexing (OFDM) based fifth-generation communication systems, as well as the requirement of integrating sensing and communication functionalities, has promoted the development of integrated-sensing-and-communication (ISAC) dense cellular networks (DCNs). In the OFDM-based ISAC-DCN, multiple base stations simultaneously serve mobile users and sense targets based on the echo of downlink communication signals. In this paper, we establish the interference model in ISAC-DCN for sensing and communication. Focusing on the interference management of the ISAC-DCN, we investigate the multi-dimension resource allocation problem. In particular, we aim to maximize the network utility by jointly optimizing sub-band allocation, user association, and transmission power under the sensing signal-to-interference-plus-noise ratio constraint to be solved iteratively. The mixed-integer optimization problem is decoupled into three sub-problems. Specifically, a greedy genetic sub-band allocation scheme is proposed for sub-band allocation to reduce total interference. We employ the successive convex approximation technique to transform the transmission power control sub-problem and solve it via geometric programming. Simulation results illustrate the trade-off between sensing and communication performances, and show that the proposed algorithm significantly improves the network utility and achieves higher detection probability. [ABSTRACT FROM AUTHOR]

Self-organizing networks (SONs) are considered as one of the key features for automation of network management in new generation of mobile communications. The upcoming fifth-generation mobile networks and beyond are likely to offer new advancements for SON solutions. In SON concept, self-healing is a prominent task which comes along with cell outage detection and cell outage compensation. Next-generation cellular networks are supposed to have ultra-dense deployments which make cell outage detection critical and harder for network maintenance. Therefore, by imitating the ultra-dense multi-tiered scenarios, this study scrutinizes femtocell outage detection with the help of long short-term memory and one-dimensional convolutional neural networks by using time sequences of key performance indicator parameters generated in user equipment. In both the proposed schemes, probable outage-related anomalies in femto access points (FAP) are detected and classified within predetermined time sequence intervals. Moreover, aggregation decision methods are also incorporated into the proposed framework for boosting cell outage detection procedure on FAP level. Our findings show that proposed deep learning approaches outperform existing feed-forward neural networks, and on the average, in more than 80% of the cases the outage states of the femtocells are correctly predicted among healthy and three anomalous states. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence, the large-scale access of intelligence equipment with complex heterogeneity will bring unpredictable spectrum limitation and complex interferences to traditional cellular networks. This situation can be alleviated by device-to-device (D2D) technique which improves spectrum efficiency by reusing cellular resources. In this paper, a resource allocation framework comprising channel allocation and power control based on Stackelberg game is proposed for distributed interference coordination between D2D and cellular communications with quality-of-service guarantee. First, base station matches the channel to D2D pairs on the basis of potential throughput gain. Second, interferences from D2D pairs to cellular users are converted into a penalty for D2D pairs through the interlayer price, and the optimization problem of system throughput is decoupled into multiple subproblems those can be solved in distributed and iterative manner in each D2D pair. Simulation results show that two proposed distributed algorithms of channel allocation and power control on interference coordination perform well in convergence and overall system throughput. [ABSTRACT FROM AUTHOR]

Multimedia content streaming from Internet-based sources emerges as one of the most demanded services by wireless users. In order to alleviate excessive traffic due to multimedia content transmission, many architectures (e.g., small cells, femtocells, etc.) have been proposed to offload such traffic to the nearest (or strongest) access point also called "helper". However, the deployment of more helpers is not necessarily beneficial due to their potential of increasing interference. In this work, we evaluate a wireless system which can serve both cacheable and non-cacheable traffic. More specifically, we consider a general system in which a wireless user with limited cache storage requests cacheable content from a data center that can be directly accessed through a base station. The user can be assisted by a pair of wireless helpers that exchange non-cacheable content as well. Files not available from the helpers are transmitted by the base station. We analyze the system throughput and the delay experienced by the cached user and show how these performance metrics are affected by the packet arrival rate at the source helper, the availability of caching helpers, the caches' parameters, and the user's request rate by means of numerical results. [ABSTRACT FROM AUTHOR]

To meet the ever-increasing demands of mobile traffic, femtocells are considered as one of the promising solutions. In this paper, we study a sensing-based resource allocation scenario in cognitive femtocell networks and present an efficient distributed imperfect-spectrum-sensing-based resource allocation (DIRA) algorithm while considering the channel uncertainty to maximize the total data rate of cognitive femtocell networks by jointly optimizing both subchannel assignment and power allocation taking into account the influence of the sensing accuracy. However, the general optimization problem turns out to be a mixed integer programming problem. In order to make it tractable, the original optimization problem is divided into two sub-optimization problems,namely,optimal subchannel allocation and optimal power allocation. Specifically, the proposed distributed fairness-based subchannel allocation (DFSA) algorithm guarantees fairness by introducing channel condition difference and satisfaction degree as the indicators of subchannel allocation. Additionally, optimal power allocation with the consideration of imperfect spectrum sensing and interference uncertainty is performed using the proposed chance-constrained power optimization (CPO) algorithm. Bernstein's approximation is conducted to make the chance constraint tractable. Simulation results illustrate that the distributed imperfect-spectrum-sensing-based resource allocation (DIRA) algorithm can provide considerable fairness among femtocells and at the same time maximize the total data rate of the cognitive femtocell network. [ABSTRACT FROM AUTHOR]

In this paper, we propose a medium access control (MAC) protocol to allow a radio over fiber-based wireless local area network (RoF-based WLAN) to coexist with legacy carrier sense multiple access with collision avoidance (CSMA/CA)-based WLANs. In RoF-based WLANs, there are long propagation delays between access points (APs) and stations (STAs). When an RoF-based WLAN uses the conventional CSMA/CA protocol and coexists with legacy WLANs, the propagation delay causes unexpected frame collisions and unfairness between the RoF-based WLAN and legacy WLANs. The proposed protocol reduces unexpected frame collisions and improves fairness between the RoF-based WLAN and legacy WLANs in environments where they coexist. It is only necessary to apply the proposed protocol to the AP in the RoF-based WLAN (RoF AP); there is no need to modify STAs, which is an advantage of the protocol. In the proposed scheme, the RoF AP transmits frames during the transmission and reception of frames in the legacy WLAN, such that the frame transmitted by the AP arrives at a destination STA one short interframe space (SIFS) period after the channel became idle, and thus the RoF AP's frames do not collide with other frames. As a result, the proposed method decreases the likelihood of frame collisions and increases the throughput of the RoF-based WLAN. In addition, the proposed method provides adaptive adjustment of the transmission probability, which enables the RoF-based WLAN and the legacy WLANs to fairly share wireless channels. The proposed protocol has been investigated for IEEE 802.11a/b/g WLANs. Numerical analysis and simulation evaluations show that the proposed scheme increases the TCP throughput of the RoF-based WLAN up to the same level as that in legacy WLANs. [ABSTRACT FROM AUTHOR]

Femtocell technology addresses the severe problems of poor network capacity and indoor coverage. Meanwhile, the emergence of high-capacity air interfaces and dense deployment of small cells result in increasingly high backhaul cost in cellular wireless networks. Purchasing on leased lines can guarantee the service provision during busy hours, however, purchased capacity goes to waste in off-peak time. Hybrid mode is the most promising one among all femtocell access modes which allows macro users to associate with adjacent femtocells with idle bandwidth resources. Femto holder (FH) is egoistic and unwilling to share bandwidth with transferred users from macrocells without any compensation, thus the successful implementation of hybrid access becomes a challenging problem. In this paper, we present an economic refunding framework to motivate hybrid access in femtocells. Macro users can opportunistically associate with adjacent femtocells with excess backhaul capacity. FH can receive certain refunding from wireless service provider (WSP) in exchange for traffic offloading. FH employs congestion pricing policy so as to control the cell load in the femtocell. Within this framework, we design a general utility maximization problem for user association that enables macro users to associate with femtocells based on traffic status, cell load, and access price. Dual decomposition is used to obtain an approximate solution. The impact of congestion pricing on the aggregate throughput and load balancing is also analyzed. Extensive simulations show the proposed scheme achieves a remarkable throughput gain compared with that with no compensation and compensation with usage-based pricing policy. Load balancing is substantially improved as well. [ABSTRACT FROM AUTHOR]

Femtocells are the auspicious solution for the coverage and capacity challenges that mobile operators are currently facing indoors. Whereas some operators are focused on offloading data traffic from macrocells to femtocells, others prefer to ensure indoor coverage and prioritize voice traffic in order to mitigate the negative impact of blocked or dropped calls. In this context, this paper proposes a novel self-optimizing mechanism to prevent congestion problems at indoor environments, focused on operators that prioritize voice traffic connections. A challenge specific to femtocells is that they normally can only serve a small number of simultaneous connections. Based on this restriction, the proposed mechanism resizes femtocell coverage areas by tuning their transmission powers for load balancing purposes. How information on user location can enhance the optimization process is also investigated in this paper. According to this, two methods to estimate the received signal level per user are evaluated. Finally, the performance is studied by means of both simulations and a real field trial. [ABSTRACT FROM AUTHOR]

This paper proposes a stream selection algorithm to deal with the interference and increase the sum capacity in the context of heterogeneous networks where cells of different types coexist. Due to the different transmit powers between the macro and small cells, interference levels are also different. Since the small cells are densely deployed, fully connected interference network between small cells is considered in this paper. The proposed algorithm performs the selection of a stream sequence among a predetermined set of sequences. Those selected sequences are the ones that mostly contribute to the sum rate when performing the exhaustive search. As a consequence, since the search space is reduced, the complexity is significantly decreased. These stream sequences form a regular structure where the first stream is associated to a pico user. Another distinguishing property of the proposed approach is that the stream sequences include at least one stream for each user. When selecting the streams, the channel matrices of the unselected streams are projected orthogonally to the virtual transmit and virtual receive channels of the selected stream in order to align the interference in the null space of these virtual channels. The performance evaluations are carried out by considering different scenarios with different numbers and locations of pico cells. It is shown that the proposed method can significantly reduce the computational complexity while achieving a very close performance to the exhaustive search. [ABSTRACT FROM AUTHOR]

In cognitive heterogeneous networks, when multiple adjacent femtocells are deployed, uncontrolled transmission power can lead to severe mutual interference. In order to reduce interference while satisfying capacity requirements, we propose a power management scheme for an adjacent femtocell network. Firstly, we build an interference model for adjacent femtocells, in which distance-dependent interference to terminals within the whole femtocell coverage area is considered. Then, we calculate the total capacity of adjacent femtocells based on the mutual interference and formulate a non-convex optimization problem to maximize the capacity under the transmission power constraints. To solve the non-convex problem, we divide it into two convex subproblems and solve them with the Lagrange dual theory and linear programming method. Finally, we derive the closed-form expression of the optimal power configuration to maximize capacity while minimizing energy consumption simultaneously. The simulation results indicate that the proposed power scheme demonstrates obvious improvement in terms of capacity and power economization, compared with the maximal power configuration method. [ABSTRACT FROM AUTHOR]

In this paper, a cognitive closed access multi-element antenna-specific femtocell protocol is presented. Femtocell is considered as the preeminent solution for indoor coverage in long-term evaluation (LTE) and LTE-advanced networks. The protocol is verified using a patch antenna for LTE network. In a vast deployment of this mini base station, unwanted handover event is considered as the major obstacle. Access control mechanism with coverage-optimized antenna pattern is one of the most promising solution to resolve this obstacle. A previously proposed microstrip four-element femtocell configuration is used to analyze the performance in user categorizing technique for closed access femtocell network. The categorization is performed using multi-layer feed forward network in neural network. The performance of the technique shows an inherent relationship between completeness of training data and error percentage. Sufficiently low error rates can be achieved by presenting about 15 training samples. [ABSTRACT FROM AUTHOR]

Driven by the demands for better user experience and high data-rate service, there is an ever increasing trend for capacity enhancement for wireless networks. The densely deployed small cells is a promising solution which can provide a huge capacity gain and improve the user experience with high data-rate services. Due to the random deployed manner of the customers, small cells should have automatic parameters an tuning and optimization abilities to realize the self-deployment in heterogeneous networks. Therefore, a novel dynamic hybrid frequency allocation scheme is proposed by applying both inner and outer circle regions for different frequency allocation schemes for small cells, which can improve the capacity and minimize interference among different hierarchical networks. Closed-form solutions are achieved for proposed downlink capacity model and key parameters affecting the capacity are also analyzed thoroughly. Furthermore, an optimal geographic region division scheme is designed and the optimal square zone length is theoretically obtained for an efficient information delivery among small cells. Numerical results verify that the capacity can be improved with the appropriate small cell deployment using proposed novel schemes. [ABSTRACT FROM AUTHOR]

This paper focuses on a robust distributed power allocation scheme for downlink two-tier heterogeneous networks (HetNets). The objective is to maximize the network aggregate utility of femtocell users (FUEs) which factors the fairness between users under the constraint of not causing serious interference to existing macrocell users (MUEs). Being impractical for different nodes to cooperate in HetNets to obtain precise estimated values of the channel gains between them, it is a challenge to guarantee the performance of the power allocation algorithm by using existing methods. This work makes a step forward in the direction of conquering this challenge by taking into account channel uncertainty, and the robust counterpart of nominal problem, without channel uncertainty, is framed by using worst-case robust optimization theory. To make the robust counterpart computationally tractable, we exploit its convexity and derive that the channel uncertainties between a FUE and nearby femtocell base stations (FBSs) fall into water-filling form being related to the received power from interference sources. Based on the inherent relationship between channel uncertainty and received power, we design a distributed algorithm which merely needs to solve a deterministic problem. The algorithm is devised based on alternating direction method of multipliers (ADMM) with a fast convergence speed. The simulation results demonstrate the robustness of our proposed approach, and the corresponding cost of robustness is investigated. [ABSTRACT FROM AUTHOR]

This editorial sums up relevant topics on the assessment of wireless communication systems covered by the especial issue entitled 'Experimental Evaluation in Wireless Communications.' The topics include practical aspects on the implementation of distributed asynchronous non-linear kernel methods over wireless sensor networks; localization methods based on the exploitation of radio-frequency identification (RFID) wireless sensors and cellular networks or on sparsity approximations; channel sounding and assessment of broadband orthogonal frequency-division multiplexing (OFDM)-based wireless systems in high-speed vehicular communications; coexistence analysis of femtocell-based and outdoor-to-indoor systems; techniques for peak-to-average power ratio (PAPR) reduction; new solutions for baseband and radio frequency (RF) hardware impairments in full-duplex wireless systems; and, finally, suitability of interference alignment for broadband indoor wireless communications. [ABSTRACT FROM AUTHOR]

This article considers what the minimum energy indoor access point deployment is in order to achieve a certain downlink quality-of-service. The article investigates two conventional multiple-access technologies, namely: LTE-femtocells and 802.11n Wi-Fi. This is done in a dynamic multi-user and multi-cell interference network. Our baseline results are reinforced by novel theoretical expressions. Furthermore, the work underlines the importance of considering optimisation when accounting for the capacity saturation of realistic modulation and coding schemes. The results in this article show that optimising the location of access points both within a building and within the individual rooms is critical to minimise the energy consumption. [ABSTRACT FROM AUTHOR]

Cognitive radio and femtocells are recent technology breakthroughs that aim to achieve throughput improvement by means of spectrum management and interference mitigation, respectively. However, these technologies are limited by the former's susceptibility to interference and the latter's dependence on bandwidth availability. In this paper, we overcome these limitations by integrating cognitive radio and femtocell technology and exploring its feasibility and throughput improvement. To realize this, we propose an integrated architecture and formulate a multiobjective optimization problem with mixed integer variables for the joint power control, base station assignment, and channel assignment scheme. In order to find a pareto optimal solution, a weighted sum approach was used. Based on numerical results, the optimization framework is found to be both stable and converging. Simulation studies further show that the proposed architecture and optimization framework improve the aggregate throughput as the client population rises, hence confirming the successful and beneficial integration of these technologies. [ABSTRACT FROM AUTHOR]

This paper presents a derivation of the probability density function (PDF) of the signal-to-interference and noise ratio (SINR) for the downlink of a cell in multicellular networks. The mathematical model considers uncoordinated locations and transmission powers of base stations (BSs) which reflect accurately the deployment of randomly located femtocells in an indoor environment. The derivation is semianalytical, in that the PDF is obtained by analysis and can be easily calculated by employing standard numericalmethods. Thus, it obviates the need for time-consuming simulation efforts. The derivation of the PDF takes into account practical propagation models including shadow fading. The effect of background noise is also considered. Numerical experiments are performed assuming various environments and deployment scenarios to examine the performance of femtocell networks. The results are compared with Monte Carlo simulations for verification purposes and show good agreement. [ABSTRACT FROM AUTHOR]

A two-tier UMTS network is considered where a large number of randomly deployed Wideband Code Division Multiple Access (WCDMA) femtocells are laid under macrocells where the spectrum is shared. The cochannel interference between the cells may be a potential limiting factor for the system. We study the uplink of this hybrid network and identify the critical scenarios that give rise to substantial interference. The mechanism for generating the interference is analyzed and guidelines for interference mitigation are provided. The impacts of the cross-tier interference especially caused by increased numbers of users and higher data rates are evaluated in the multicell simulation environment in terms of the noise rise at the base stations, the cell throughput, and the user transmit power consumption. [ABSTRACT FROM AUTHOR]

We present an analysis of a femtocellular communications network and the impact of cochannel interference on link performance. Furthermore, we propose a method whereby user terminals can maintain a controlonly connection to an adjacent femtocell for interference mitigation purposes. Specifically, we provide an emphasis on suboptimal but practical methods that rely on transmit beamforming. Our numerical results demonstrate that even simple multiantenna methods can be effectively used to suppress co-channel interference provided that control channel connection between interfering femto-base station and user terminal is allowed. [ABSTRACT FROM AUTHOR]

Femto-cells consist of user-deployed Home Evolved NodeBs (HeNBs) that promise substantial gains in system spectral efficiency, coverage, and data rates due to an enhanced reuse of radio resources. However, reusing radio resources in an uncoordinated, random fashion introduces potentially destructive interference to the system, both, in the femto and macro layers. An especially critical scenario is a closed-access femto-cell, cochannel deployed with a macro-cell, which imposes strong downlink interference to nearby macro user equipments (UEs) that are not permitted to hand over to the femto-cell. In order to maintain reliable service of macro-cells, it is imperative to mitigate the destructive femto-cell to macro-cell interference. The contribution in this paper focuses on mitigating downlink femto-cell to macro-cell interference through dynamic resource partitioning, in the way that HeNBs are denied access to downlink resources that are assigned to macro UEs in their vicinity. By doing so, interference to the most vulnerable macro UEs is effectively controlled at the expense of a modest degradation in femto-cell capacity. The necessary signaling is conveyed through downlink high interference indicator (DL-HII) messages over the wired backbone. Extensive system level simulations demonstrate that by using resource partitioning, for a sacrifice of 4% of overall femto downlink capacity, macro UEs exposed to high HeNB interference experience a tenfold boost in capacity. [ABSTRACT FROM AUTHOR]

There are two main access policies (open and closed) to Femtocell Access Points (FAPs), being closed access the customers favorite. However, closed access is the root cause of crosstier interference in cochannel deployments of two-tier networks (i.e., macrocells and femtocells). Further, the effect of this problem is remarkably serious in the downlink of outdoor users not subscribed to any femtocell. Open access has been considered as a potential solution to this problem. However, this increases signaling in the network due to the elevated number of HandOvers (HOs) that mobile users have to perform. Therefore, this paper proposes an interference avoidance technique based on the use of Intracell HandOvers (IHOs) in Orthogonal Frequency Division Multiple Access (OFDMA) femtocells. It is shown that a proper combination of IHO and power control techniques reduces the outage probability for nonsubscribers compared with that of closed and open access. In addition, the impact of several network parameters such as the femtocell penetration is also considered in the analysis. [ABSTRACT FROM AUTHOR]

In this paper, the trade-off among system sum energy consumption and robustness is studied. In this regard, a robust power allocation problem is formulated for a two-tier heterogeneous network with uplink transmission mode and consideration of imperfect channel state information. The objective is to minimize the total transmit power of femtocell users (FUs), while the interference to macrocell user receiver is limited to a predefined interference level, the transmit power of each FU transmitter is kept within their power budgets, and the actual signal-to-interference-plus-noise ratio of each femtocell receiver is above a minimum threshold. Considering the uncertainties of the interference links from FUs to macrocell base stations and forward transmission links of each FU, the robust power allocation problem is formulated as a semi-infinite programming problem (SIPP). By the worst-case approach, the SIPP is transformed into a convex optimization problem solved by the Lagrange dual decomposition method. Moreover, the feasible regions of constraints, computational complexity, and sensitivity degree of the proposed robust algorithm are also analyzed. Simulation results investigate the impact of channel uncertainties and the superiority of the proposed algorithm by comparing with non-robust algorithm. [ABSTRACT FROM AUTHOR]

The article discusses various reports published within the issue, including "On Uplink Interference Scenarios in Two-Tier Networks," by Z. Shi et al., "A Semi-Analytical PDF of Downlink SINR for Femto-Cell Networks," by Sung et al., and "Interference Suppression by Practical Transmit Beamforming Methods in Closed Femtocells," by Husso et al.