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Indoor optical wireless communication (IOWC) is a key technology complementing radio communication in 6G. Typically, the downlink of IOWC is implemented using visible light and uplink is implemented using infrared. Though the downlink of IOWC has been studied well, the uplink of multiple-access IOWC requires further research. In this paper, power allocation strategies in the uplink of IOWC with multiple non-cooperative users is studied. Optimizing power allocation in IOWC that maximize sum-rate with power constraints becomes a non-convex problem. First, this paper proposes an alternating maximization algorithm to compute near optimal power allocation policies for small number of users. Next, a phenomenon of invariance is observed when the number of users in the system is large. Under invariance, the optimal power allocation policy of a user becomes independent of other users, thereby facilitating fast and decentralized computation of power allocation strategies. From simulations, it was observed that the invariance can occur even with five to ten users. For the first time, a rigorous analysis of the invariance phenomenon is provided. An algorithm to compute the optimal power allocation at invariance is proposed; this algorithm is proven to achieve the global maxima in sum-rate without the channel knowledge of other users. [ABSTRACT FROM AUTHOR]

The integration of local device-to-device (D2D) communications and cellular connections has been intensively studied to satisfy co-existing D2D and cellular communication demand. In future cellular networks, there will be numerous standby users possessing D2D communication capabilities in close proximity to each other. Considering that these standby users do not necessarily request D2D communications all the time, in this paper we propose a hybrid D2D-cellular scheme to make use of these standby users and to improve the rate performance for cellular users. More specifically, through D2D links, a virtual antenna array can be formed by sharing antennas across different terminals to realize the diversity gain of MIMO channels. This paper considers the use of millimeter wave links to enable high data rate D2D communications. We then design an orthogonal D2D multiple access protocol and formulate the optimization problem of joint cellular and D2D resource allocation for downlink transmissions using the proposed scheme. We obtain a closed-form solution for D2D resource allocation, which reveals useful insights for practical system design. Numerical results from extensive system-level simulations demonstrate that the rate performance of cellular users is significantly improved. [ABSTRACT FROM AUTHOR]

This paper proposes a new paradigm for spectrum sharing between cellular wireless communications (CWC) and radio astronomy systems (RAS). In contrast to the existing paradigm of geographical and spectral isolation between CWC and RAS, this paper develops a three phase spectrum access, which enables geographical and spectral coexistence between CWC and RAS. Shared spectrum access zone (SSAZ) is created around the RAS site and CWC cells within the SSAZ follow the three phase spectrum access scheme while those outside the SSAZ have full spectrum access. In addition, system characteristics-based improved spectrum sharing is developed. Furthermore, a built-in fine tuning mechanism is presented for addressing mismatches between design and practical environments as well as for facilitating service evolutions. Performance evaluation results demonstrate that the proposed paradigm offers 1) certain guaranteed spectrum access to RAS, which is impossible in the existing paradigm, 2) capability to handle higher peak and mean traffics to CWC under spectrum restructuring of both CWC and RAS bands, and 3) overall improved spectrum utilization. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the multiple input multiple output (MIMO)-non-orthogonal multiple access (NOMA) transmission with the aid of location information. We first consider two users separated in both the distance and angle domains. With different access distances, NOMA could be used to serve the near-user and the far-user simultaneously, whereas spatial division multiple access (SDMA) would be applied if the two users have largely-separated angles of departure (AOD) that guarantees spatial orthogonality. Comparing the ergodic sum rates of these two multiple access (MA) schemes, we first characterize the preferable MA regions in the angle-distance plane. Analytical expression of the region boundary between NOMA and SDMA is derived. Moreover, NOMA-preferable regions are expressed in terms of the maximum distance difference and the minimum angle difference between the two users, respectively. On basis of these results, we further propose a location-based low-complexity user pairing algorithm for the general multiuser scenario. Numerical results confirm the accuracy of the derived region boundaries, and the simulations show that the proposed user pairing algorithm can effectively improve the resource utilization rate, compared to the conventional MA and user pairing schemes. [ABSTRACT FROM AUTHOR]

In this paper, we optimize the energy efficiency (bits/s/Hz/J) of device-to-multi-device (D2MD) wireless communications. While the device-to-device scenario has been extensively studied to improve the spectral efficiency in cellular networks, the use of multicast communications opens the possibility of reusing the spectrum resources also inside the groups. The optimization problem is formulated as a mixed integer non-linear joint optimization for the power control and allocation of resource blocks (RBs) to each group. Our model explicitly considers resource sharing by letting co-channel transmission over a RB (up to a maximum of $r$ transmitters) and/or transmission through $s$ different channels in each group. We use an iterative decomposition approach, using first matching theory to find a stable even if sub-optimal channel allocation, to then optimize the transmission power vectors in each group via fractional programming. In addition, within this framework, both the network energy efficiency and the max-min individual energy efficiency are investigated. We characterize numerically the energy-efficient capacity region, and our results show that the normalized energy efficiency is nearly optimal (above 90% of the network capacity) for a wide range of minimum-rate constraints. This performance is better than that of other matching-based techniques previously proposed. [ABSTRACT FROM AUTHOR]

Joint optimal resource allocation and probabilistic caching design is conceived for device-to-device (D2D) communications in a heterogeneous wireless network (HetNet) relying on full-duplex (FD) relays. In particular, popular contents can be cached at user devices and at relays that are located close to users. A user may request the contents of interest from another user via D2D communications and also from a nearby relay equipped with FD radios. If the requested contents are not found in the buffers of other users/relays within the coverage range, users may opt for connecting to the macro base station (MBS) via a relay by using an FD communication. Furthermore, we propose a beneficial mobility-aware coded caching philosophy for D2D communications in the HetNet considered. Especially, we model the mobility pattern of users as discrete random jumps and exploit coded caching for improving the throughput attained. Subsequently, we develop mathematical models for analyzing the throughput in the presence of edge caching, where both the system-level co-channel interference and the FD self-interference are considered. We circumvent the high complexity of stochastic optimization by developing low-complexity optimization. Finally, numerical results are presented to illustrate the theoretical findings developed in this paper and quantify the throughput gains attained. [ABSTRACT FROM AUTHOR]

By blending the concepts of non-orthogonal multiple access (NOMA) and orthogonal frequency division multiplexing, in this paper, a novel hybrid scheme is conceived for supporting diverse services in future wireless systems. Motivating to maximize energy efficiency (EE), the joint resource management of user clustering (UC) and power allocation is investigated for the downlink hybrid NOMA systems. Under two different power consumption cases, the optimal resource allocation (Opt-RA) algorithm is developed with the help of converting the original mixed integer non-linear programming (MINLP) problem to the tractable decoupled problems. For practical implementation, the heuristic resource allocation (Heur-RA) algorithm is also proposed, and it includes a low-complexity UC algorithm based on the candidate search-and-allocation approach. Our simulation results show that, both the Opt-RA and Heur-RA algorithms achieve significantly higher EE performance than other existing algorithms. Further, the results also prove that, the hybrid NOMA conceived is able to exploit the advantages of NOMA scheme, and is superior to conventional orthogonal multiple access (OMA) in terms of EE, as well as achieving higher flexibility for system configuration than NOMA. [ABSTRACT FROM AUTHOR]

In this paper, a fundamental study of energy efficiency (EE) optimization for coordinated multi-point (CoMP) simultaneous wireless information and power transfer (SWIPT) heterogeneous networks (HetNets) is provided. We aim to optimize the EE while satisfying certain quality-of-service requirements in regard to transmission rate and energy harvesting at both the macro cell and small cells. The corresponding joint beamforming and power allocation in the presence of intra- and inter-cell interference constitutes an EE maximization problem that is non-convex, and hence, very challenging to solve. In order to solve this problem, we propose to separate the beamforming design and power allocation processes. First, we adopt linear zero-forcing (ZF) beamforming to suppress the multi-user interference from both the energy harvesting users (EH-UEs) as well as the information decoding UEs (ID-UEs), thus transforming the HetNet under consideration to a virtual point-to-point system. An efficient power allocation algorithm is then developed to maximize the corresponding EE. On the other hand, the ZF strategy does not utilize the notion that interference benefits the EH-UEs. As a result, we propose a partial ZF approach by differentiating the EH-UEs and ID-UEs in order to further improve the EE. Our findings show that the EE can be significantly improved through the integration of CoMP-SWIPT in HetNets. [ABSTRACT FROM AUTHOR]

A base-station (BS) equipped with multiple antennas can use its spatial dimensions in three different ways: 1) to serve multiple users, thereby achieving a multiplexing gain; 2) to provide spatial diversity in order to improve user rates; and 3) to null interference in neighboring cells. This paper answers the following question: What is the optimal balance between these three competing benefits? We answer this question in the context of the downlink of a cellular network, where multi-antenna BSs serve multiple single-antenna users using zero-forcing beamforming with equal power assignment, while nulling interference at a subset of out-of-cell users. Any remaining spatial dimensions provide transmit diversity for the scheduled users. Utilizing tools from stochastic geometry, we show that, surprisingly, to maximize the per-BS ergodic sum rate, with an optimal allocation of spatial resources, interference nulling does not provide a tangible benefit. The strategy of avoiding inter-cell interference nulling, reserving some fraction of spatial resources for multiplexing, and using the rest to provide diversity, is already close-to-optimal in terms of the sum-rate. However, interference nulling does bring significant benefit to cell-edge users, particularly when adopting a range-adaptive nulling strategy where the size of the cooperating BS cluster is increased for cell-edge users. [ABSTRACT FROM AUTHOR]

In this paper, we consider a non-orthogonal multiple access cognitive radio network, where a full-duplex (FD) multi-antenna relay assists transmission from an access point (AP) to a cognitive far user, while at the same time, the AP transmits to a cognitive near user. Our objective is to maximize the rate of the near user under a constraint that the rate of the far user is above a certain threshold. To this end, a non-convex joint optimization problem of relay beamforming and the transmit powers at the AP and FD relay is solved as a semi-definite relaxation problem, in conjunction with an efficiently solvable line-search approach. We also consider a low complexity fixed beamformer design, where the optimum power allocation between the AP and FD relay is solved. Several fixed beamforming designs based on the zero-forcing criterion are proposed for which exact and asymptotic outage probability expressions corresponding to the near and far users are derived. Our results demonstrate that the proposed joint optimization can significantly reduce the self-interference impact at the FD relay and inter-user interference in the near user case. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA)-based cognitive wireless networks can improve the spectral efficiency to utilize the vacant spectrum resource and exploit the power domain diversity. In this paper, we formulate a max-min resource allocation problem for video traffic in NOMA-based cognitive wireless networks as a mixed integer non-linear programming (MINLP) problem. The max-min video transmission problem is subject to the constraints of maximum accessed user number at each subchannel, total available energy of each secondary user, video encoding characteristics, and interference power threshold. To solve the formulated MINLP problem, we divide it into two subproblems, i.e., a power allocation and secondary user scheduling subproblem, and a video packet scheduling subproblem. First, we apply a successive convex approximation to transform the joint power allocation and secondary user scheduling subproblem into a bi-convex programming problem. Second, the binary search and dual decomposition methods are combined to obtain the approximated optimal power allocation and secondary user scheduling solutions. Finally, we propose a heuristic packet scheduling algorithm. Simulation numerical results show that the proposed algorithm improves the video quality and guarantees the fairness among different secondary users. [ABSTRACT FROM AUTHOR]

In this paper, we concentrate on the robust multi-objective optimization (MOO) for the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in device-to-device (D2D) communications underlaying heterogeneous networks (HetNets). Different from traditional resource optimization, we focus on finding robust Pareto optimal solutions for spectrum allocation and power coordination in D2D communications underlaying HetNets with the consideration of interference channel uncertainties. The problem is formulated as an uncertain MOO problem to maximize EE and SE of cellular users (CUs) simultaneously while guaranteeing the minimum rate requirements of both CUs and D2D pairs. With the aid of $\varepsilon$ -constraint method and strict robustness, we propose a general framework to transform the uncertain MOO problem into a deterministic single-objective optimization problem. As exponential computational complexity is required to solve this highly non-convex problem, the power coordination and the spectrum allocation problems are solved separately, and an effective two-stage iterative algorithm is developed. Finally, simulation results validate that our proposed robust scheme converges fast and significantly outperforms the non-robust scheme in terms of the effective EE-SE tradeoff and the quality of service satisfying probability of D2D pairs. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) has been proposed as an alternative to orthogonal multiple access (OMA) in an effort to enhance the spectral efficiency of 5G cellular systems. However, the NOMA throughput gain relative to that of OMA has been shown to be modest. In this paper, we propose a novel NOMA scheme that exploits the partial overlap (i.e., similarity) among users bit sequences at the base station (BS). Specifically, users bit sequences are divided into blocks of short lengths, i.e., short bit sequences. Then, one user is selected and served during a given transmission time interval (TTI). Users whose bit sequences partially overlap with the bit sequence of the served user are also (partially) served during the same TTI. At the receiving end, the receiver corresponding to the served user recovers its entire bit sequence, whereas the partially served users recover their corresponding overlapping bit blocks and ignore the rest of the sequence. The performance of the proposed scheme is analyzed in terms of the overall throughput. We show that a throughput gain of up to three times that of existing OMA schemes can be achieved. Moreover, we show that the average rate per user decreases slightly as the number of users increases, whereas it linearly decreases with the number of users in existing NOMA schemes. We stress here that the proposed scheme completely differs from existing NOMA schemes as the latter schemes are based on power allocation at the BS where successive interference cancellation is normally used. The implication of this is that the proposed scheme provides substantial throughput gains without causing interference among users and without adopting a specific power allocation at the BS. [ABSTRACT FROM AUTHOR]

To improve the spectral efficiency in long-term evolution systems, the resource blocks (RBs) are shared among different cells/base stations (BSs) resulting in interference among the cells/BSs on each RB, although all the sub-carriers (SCs) in an RB may not be used in a cell. Defining the load of a given BS per RB as the fraction of the active SCs in that RB, in this paper, we present a generalized signal-to-interference-and-noise-ratio (SINR) model for downlink users on a given RB. This model considers both the transmit powers of the BSs and the loads of the cells over that RB. Under this load-coupled SINR model, to study the feasibility of a given rate demand vector for users, we formulate an optimization problem of minimizing the total load of the BSs on the RBs. Then, for two different scenarios of feasible and infeasible demand vectors, respectively, we study the load management problem (i.e., minimizing the total load of the BSs on the RBs) and admission control problem (i.e., finding the sub-set of users with maximum cardinality whose demands can be concurrently satisfied), respectively. Our theoretical investigations, which provide guidelines for designing radio resource management methods for load-coupled OFDMA networks, are complemented through Monte Carlo simulations. [ABSTRACT FROM PUBLISHER]

Ultra-dense networks are envisioned as essential to embrace the skyrocketed traffic for the next-generation wireless networks. In this paper, we consider the uplink transmissions in ultra-dense networks, where the increased interference along with the increased density significantly challenges the efficient utilization of network resources as well as the provisioning of users’ quality of services (QoS). Targeting these issues, we consider the QoS in terms of target signal-to-interference-plus-noise ratio (SINR) and power consumption simultaneously for each user within a multi-objective optimization model. We then investigate the interactions among users by leveraging the non-cooperative game-theoretical framework. By characterizing the properties of Nash equilibrium, we develop the target-SINR oriented resource allocation (TORA) algorithm, which features distributed implementation. Moreover, we obtain the condition to guarantee the convergence of our proposed TORA algorithm and demonstrate that it adapts to different interfering scenarios. Furthermore, considering the heterogeneous service requirements in real practice, we also design the target-SINR constrained resource allocation (TCRA) algorithm, such that TORA and TCRA are able to cope with voice and data services, respectively. Also provided are the simulation results, which demonstrate that, compared with the counterparts, our proposals more effectively guarantee the target-SINR for users with efficient power utilization. [ABSTRACT FROM PUBLISHER]

In this paper, a novel non-orthogonal multiple access (NOMA) enhanced device-to-device (D2D) communication scheme is considered. Our objective is to maximize the system sum rate by optimizing subchannel and power allocation. We propose a novel solution that jointly assigns subchannels to D2D groups and allocates power to receivers in each D2D group. For the subchannel assignment, a novel algorithm based on the many-to-one two-sided matching theory is proposed for obtaining a suboptimal solution. Since the power allocation problem is non-convex, sequential convex programming is adopted to transform the original power allocation problem to a convex one. The power allocation vector is obtained by iteratively tightening the lower bound of the original power allocation problem until convergence. Numerical results illustrate that: 1) the proposed joint subchannel and power allocation algorithm are an effective approach for obtaining near-optimal performance with acceptable complexity and 2) the NOMA enhanced D2D communication scheme is capable of achieving promising gains in terms of network sum rate and the number of accessed users, compared to a traditional OMA-based D2D communication scheme. [ABSTRACT FROM AUTHOR]

Interference alignment (IA) can remarkably improve the spectral efficiency of dense small cell networks (SCNs) underlaying a macrocell, but its feasibility condition and implementation complexity are restricted by the number of small cell equipments (SUEs). Moreover, the SUEs performing IA may have unsatisfactory quality of service (QoS) requirements as IA only eliminates interference while neglecting the gain of desired signals. In this paper, we propose a centralized efficient subchannel allocation scheme based on IA with similarity clustering in dense SCNs underlaying a macrocell, which aims at maximizing the number of QoS guaranteed SUEs performing IA. The corresponding problem is formulated as a combinatorial optimization problem which is NP-hard. So a low-complexity solution is proposed which includes three phases: similarity clustering for SUEs through graph partitioning, further adjustments of cluster sizes to make IA feasible in each cluster, and subchannel allocation for the formed clusters, each of which is performed with a notably reduced computational complexity. Moreover, the proposed solution greatly reduces the signaling overhead incurred by channel state information estimation. Numerical results show that the proposed solution not only outperforms other related schemes, but also achieves a performance close to the optimal solution. [ABSTRACT FROM AUTHOR]

Small-cell networks and massive multiple-input multiple-output (MIMO) systems are regarded as important candidate techniques for 5G communication systems. This paper considers a heterogeneous network composed of a macrocell tier overlaid with an extremely dense tier of small-cells. In the network, the macrocell base station (BS), which applies massive MIMO, does not only serve macro user equipment units but also provides wireless backhaul for small-cell access points (APs). The wireless backhaul shares the same spectrum resource with radio access networks without creating extra spectrum resources. However, due to the densification of small-cells, the inter- and intra-tier interferences become severe. To mitigate the interferences, we use the regularized zero-forcing precoding combined with a projection technique is used at the BS in downlink (DL) to avoid interference to the APs in uplink (UL). Meanwhile, the joint linear minimum mean square error detection is applied in UL to mitigate the inter-tier interference. We derive deterministic expressions for ergodic UL and DL sum rates (SRs) by leveraging the large-dimensional random matrix theory. The expressions only depend on statistical channel information and can be used to optimize the bandwidth division between radio access links and wireless backhaul, as well as the time allocation between DL and UL operation intervals. Numerical results show that the deterministic SR equivalents are accurate and that the proposed resource allocation method can significantly improve system performance. [ABSTRACT FROM AUTHOR]

In-band full-duplex (IBFD) backhauling is a potential technique for wireless backhauling of small cells that allows the use of same spectrum for the backhaul and access links of the small cell base stations (SBSs) concurrently, however, at the expense of backhaul interference and self-interference (SI). This paper investigates the problem of optimal access/backhaul spectrum allocation considering IBFD backhauling, out-of-band full-duplex (OBFD) backhauling (in which the access and backhaul transmissions take place on different spectrum), and the SBSs with the provisioning for hybrid IBFD/OBFD backhauling. We first formulate a problem to maximize the minimum achievable rate (i.e., minimum of the rates in the backhaul link and the access link) at the SBSs in a hybrid IBFD/OBFD setting. The solution of the centralized spectrum allocation problem, which serves as a benchmark for any sub-optimal solution, is provided by transforming the original problem into an epigraph form. As a special case of the formulated problem, we derive closed-form optimal solutions for the access/backhaul spectrum allocation of OBFD backhauling as well as IBFD backhauling. We then propose and comparatively analyze the performance of two distributed backhaul spectrum allocation schemes, namely, maximum received signal power (max-RSP) and minimum received signal power (min-RSP) schemes. For these schemes, we theoretically derive the number of allocated backhaul channels, minimum rate coverage probability, and average achievable rate of each SBS given its distance from the centralized wireless backhaul hub (WBH) for both IBFD and OBFD backhauling. Numerical results reveal that the optimal spectrum allocation rules can significantly vary for IBFD and OBFD backhauling. Optimal OBFD backhauling favors more backhaul spectrum for SBSs located far-away from the WBH. With IBFD backhauling, spectrum allocation for SBSs strongly depends on SI. With the reduction in SI, the optimal backhaul spectrum increases/decreases for nearby/farther SBSs. Simulation results comparing the optimal solution with the distributed spectrum allocation solutions based on max-RSP and min-RSP schemes are also presented. [ABSTRACT FROM PUBLISHER]

Femtocells constitute an economical solution conceived for improving the indoor coverage, which are capable of achieving a high network capacity. In order to guarantee a high Spectral Efficiency (SE), femtocells have to reuse the spectrum of macrocells. As a result, the performance of both the femtocells and macrocells may suffer owing to the near-far effects. In this paper, we study a twin-layer cellular networks, where the Macrocell Base Stations (MBSs) employing Fractional Frequency Reuse (FFR) host the Femtocell Base Stations (FBSs). This paper investigates the design, performance analysis and optimization problems of this FFR aided twin-layer network. We firstly assume that the femtocells opt for full spectrum access (FSA). The per-layer outage probability (OP) is derived and the network is optimized for maximizing the macrocell's throughput. We found that the advantage of FFR eroded in dense femtocell-scenarios and the optimized network tends to become a Unity Frequency Reuse (UFR) aided system. We then propose a spectrum swapping access (SSA) strategy for protecting the macrocell's performance and for overcoming the typical near-far problem. Our analysis demonstrates that both the OP of femtocell users in the Cell Centre Region (CCR) and that of the macrocell users in the Cell Edge Region (CER) will be reduced by the proposed SSA. The optimized network using our SSA is more robust to the detrimental impact of femtocells. [ABSTRACT FROM AUTHOR]

Heterogeneous network is a novel network architecture proposed in long-term-evolution, which highly increases the capacity and coverage compared with the conventional networks. However, in order to provide the best services, appropriate resource management must be applied. In this paper, we consider the joint optimization problem of user association, subchannel allocation, and power allocation for downlink transmission in multi-cell multi-association orthogonal frequency division multiple access heterogeneous networks. To solve the optimization problem, we first divide it into two subproblems: 1) user association and subchannel allocation for fixed power allocation and 2) power allocation for fixed user association and subchannel allocation. Subsequently, we obtain a locally optimal solution for the joint optimization problem by solving these two subproblems alternately. For the first subproblem, we derive the globally optimal solution based on graph theory. For the second subproblem, we obtain a Karush–Kuhn–Tucker optimal solution by a low complexity algorithm based on the difference of two convex functions approximation method. In addition, the multi-antenna receiver case and the proportional fairness case are also discussed. Simulation results demonstrate that the proposed algorithms can significantly enhance the overall network throughput. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate resource allocation algorithm design for multicarrier non-orthogonal multiple access (MC-NOMA) systems employing a full-duplex (FD) base station for serving multiple half-duplex (HD) downlink and uplink users simultaneously. The proposed algorithm is obtained from the solution of a non-convex optimization problem for the maximization of the weighted sum system throughput. We apply monotonic optimization to develop an optimal joint power and subcarrier allocation policy. The optimal resource allocation policy serves as a system performance benchmark due to its high computational complexity. Furthermore, a suboptimal iterative scheme based on successive convex approximation is proposed to strike a balance between computational complexity and optimality. Our simulation results reveal that the proposed suboptimal algorithm achieves a close-to-optimal performance. In addition, FD MC-NOMA systems employing the proposed resource allocation algorithms provide a substantial system throughput improvement compared with conventional HD multicarrier orthogonal multiple access (MC-OMA) systems and other baseline schemes. In addition, our results unveil that FD MC-NOMA systems enable a fairer resource allocation compared with traditional HD MC-OMA systems. [ABSTRACT FROM AUTHOR]

Efficiency in spectrum utility has been a concern in wireless communications for a long time. Cognitive radios have been seen as a solution to occupy the gaps in the licensed spectrum through opportunistic spectrum access and simultaneous spectrum sharing techniques. For this purpose, spectrum sensing has been vital in providing accurate statistical information regarding licensed or primary user (PU) activity on its spectrum. In this paper, we design new sensing thresholds that take into account the outage caused to the PU as a consequence of cognitive or secondary users (SUs) accessing or sharing the said spectrum. With these new thresholds, we can see more protection to the PU from SU spectrum access transmissions based on missed detections, and eliminate most common assumptions made with spectrum sharing systems. Our thresholds also work with a dynamic decision-making algorithm that allows the SUs to use only the statistical sensing information to understand the network dynamics, and determine its transmission opportunities and corresponding power consumption, in a decentralized and uncooperative cross-layer network. [ABSTRACT FROM AUTHOR]

This paper proposes a centralized decision making framework at the macro base station (MBS) for device-to-device (D2D) communication underlaying a two-tier cellular network. We consider a D2D pair in the presence of an MBS and a femto access point, each serving a user, with quality of service constraints for all users. Our proposed solution encompasses mode selection (choosing between cellular or reuse or dedicated mode), resource allocation (in cellular and dedicated mode), and power control (in reuse mode) within a single framework. The framework prioritizes D2D dedicated mode if the D2D pair is close to each other and orthogonal resources are available. Otherwise, it allows D2D reuse mode if the D2D satisfies both the maximum distance and an additional interference criteria. For reuse mode, we present a geometric vertex search approach to solve the power allocation problem. We analytically prove the validity of this approach and show that it achieves near optimal performance. For cellular and dedicated modes, we show that frequency sharing maximizes sum rate and solve the resource allocation problem in a closed form. Our simulations demonstrate the advantages of the proposed framework in terms of the performance gains achieved in the D2D mode. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a spectrum refarming system where an OFDMA system shares the licensed band of a CDMA system. Both systems share the same cell site, but each has different base station (BS) antennas. Joint resource allocation problem is formulated to optimize the CDMA receive power, OFDMA transmit power, and subcarrier assignment. Conventional interference control to protect the primary CDMA system relies on the availability of cross-channel gains (CCGs) from each secondary OFDMA transmitter to the CDMA BS receiver. However, the CCGs are difficult to be obtained due to lack of intersystem cooperation. To address this problem, we first decouple the original problem into higher and lower-level problems via primal decomposition. Then, a robust lower-level resource allocation (R-LRA) scheme, which controls interference without using CCGs is proposed, with which CDMA users can be sufficiently protected. Thereafter, an enhanced R-LRA (ER-LRA) scheme is proposed to decrease the conservation of R-LRA scheme. Assisted by the CDMA inner power control and based on the ER-LRA, efficient algorithm is designed to solve the higher-level problem. Extensions of the ER-LRA for other scenarios are also studied. Simulation results are provided to validate the proposed schemes in facilitating and improving the spectrum sharing performance. [ABSTRACT FROM AUTHOR]

Deployment of low-power low-cost small access points such as femtocell access points (FAPs) constitute an attractive solution for improving the existing macrocell access points' (MAPs) capacity, reliability, and coverage. However, FAP deployment faces challenging problems such as interference management and the lack of flexible frameworks for deploying the FAPs by the service providers (SPs). In this paper, we propose a novel solution that jointly associates the user equipment (UE) to the APs, and allocates the FAPs to the SPs such that the the total satisfaction of the UEs in an uplink OFDMA network is maximized. We model the competitive behaviors among the UEs, FAPs, and SPs as a dynamic matching game and we propose distributed algorithms to find the optimal UE association and FAP allocations. We show analytically that the matching algorithms converge to the optimal and stable outcomes after a small number of iterations. Simulations and analytical results show the proposed mechanism is arbitrarily close to the global optimal solution by setting a design parameter (step number) but has significantly reduced overhead and complexity over the centralized algorithm. [ABSTRACT FROM PUBLISHER]

In cellular networks, proximity users may communicate directly without going through the base station, which is called Device-to-device (D2D) communications and it can improve spectral efficiency. However, D2D communications may generate interference to the existing cellular networks if not designed properly. In this paper, we study a resource allocation problem to maximize the overall network throughput while guaranteeing the quality-of-service (QoS) requirements for both D2D users and regular cellular users (CUs). A three-step scheme is proposed. It first performs admission control and then allocates powers for each admissible D2D pair and its potential CU partners. Next, a maximum weight bipartite matching based scheme is developed to select a suitable CU partner for each admissible D2D pair to maximize the overall network throughput. Numerical results show that the proposed scheme can significantly improve the performance of the hybrid system in terms of D2D access rate and the overall network throughput. The performance of D2D communications depends on D2D user locations, cell radius, the numbers of active CUs and D2D pairs, and the maximum power constraint for the D2D pairs. [ABSTRACT FROM AUTHOR]

This paper studies a multi-carrier based spectrum sharing system, in which two users iteratively update their respective transmit power allocation over parallel subcarriers (SCs) to maximize the individual transmit rate. Unlike the conventional iterative water-filling (IWF) algorithm that adopts the single-user detection (SD) at each user's receiver by treating the interference from all other users as additive noise, this paper proposes a new decentralized resource allocation scheme, namely iterative spectrum shaping (ISS), in which each receiver applies multiuser detection to opportunistically cancel the co-channel interference over selected SCs, thus termed opportunistic multiuser detection (OMD). Two coding schemes are investigated to exploit different forms of "frequency diversity" gains with OMD: carrier independent coding, which applies independent codebooks for different SCs to maximize the interference-decoding diversity; and carrier joint coding, which uses one single codebook across all the SCs to achieve the full coded diversity. For each coding scheme, the optimal transmit power allocation strategy is derived to maximize one user's transmit rate, with the power and rate allocation of the other user being fixed. Simulation results show that the converged system throughput by the proposed ISS algorithm with OMD is significantly improved over that by the conventional IWF with SD, in cognitive radio (CR) based wireless spectrum sharing networks. [ABSTRACT FROM PUBLISHER]

We consider the problem of resource allocation in downlink OFDMA systems for multi service and unknown environment. Due to users' mobility and intercell interference, the base station cannot predict neither the Signal to Noise Ratio (SNR) of each user in future time slots nor their probability distribution functions. In addition, the traffic is bursty in general with unknown arrival. The probability distribution functions of the SNR, channel state and traffic arrival/density are then unknown. Achieving a multi service Quality of Service (QoS) while optimizing the performance of the system (e.g. total throughput) is a hard and interesting task since it depends on the unknown future traffic and SNR values. In this paper we solve this problem by modeling the multiuser queuing system as a discrete time linear dynamic system. We develop a robust H^∞ controller to regulate the queues of different users. The queues and Packet Drop Rates (PDR) are controlled by proposing a minimum data rate according to the demanded service type of each user. The data rate vector proposed by the controller is then fed as a constraint to an instantaneous resource allocation framework. This instantaneous problem is formulated as a convex optimization problem for instantaneous subcarrier and power allocation decisions. Simulation results show small delays and better fairness among users. [ABSTRACT FROM AUTHOR]