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Multicell coordinated beamforming (CB) can mitigate intercell interference (ICI). However, existing work on CB focuses on systems that maximize overall throughput. This paper considers CB for systems with multiple receive antennas and further extends the CB to multiuser and multistream transmission. We consider fairness and pay close attention to cell-edge users. CB that maximizes the harmonic sum of signal-to-interference-plus-noise ratio (SINR) can be derived into a low-complexity algorithm that favors cell-edge users. Two iterative algorithms are developed. From the simulation results, the proposed algorithms can provide a better fifth-percentile user throughput compared with the CB algorithms minimizing mean square error, maximizing uplink SINR, and maximizing weighted sum rate. Furthermore, the computational complexity of the proposed algorithms is significantly lower than that maximizing the minimum SINR of users. [ABSTRACT FROM AUTHOR]

With interference alignment (IA), the achievable degrees of freedom (DoFs) in wireless networks can be linearly scaled up with the number of users. However, to attain the full DoF, the availability of perfect network channel state information (CSI) is mandatory, which is not pragmatic in general. In this paper, we quantify the performance of IA under CSI mismatch where the variance of the CSI measurement error depends on the signal-to-noise ratio (SNR). We show that when this error variance is proportional to the inverse of the SNR, the full DoF is achievable, and an upper bound on asymptotic mean loss in sum rate compared with the perfect CSI case is derived. We also derive a bound on the achievable DoF when the CSI error variance is proportional to the inverse of the SNR to a power of a constant. Furthermore, we investigate the effect of CSI mismatch on the performance of the maximum signal-to-interference-plus-noise ratio (Max-SINR) algorithm. We show that with perfect CSI, the Max-SINR algorithm outperforms interference leakage minimization algorithms, but with the presence of imperfect CSI, its comparative improvement becomes negligible. We then propose an adaptive Max-SINR algorithm that can notably improve the performance of the original Max-SINR algorithm under CSI mismatch. [ABSTRACT FROM AUTHOR]

In the heterogeneous networks (HetNets), the downlink-uplink decoupled (DUDE) user association is a very promising technology that can employ different association strategies for uplink and downlink. The DUDE mode has great potential for improving system capacity and frequency efficiency. However, interference between the DUDE user equipment (DUDE UE), macro user equipment (MUE) and small user equipment (SUE) still needs to be considered and properly tackled. Therefore, this paper presents an optimization scheme of frequency allocation and power control to improve the communication quality of users. Firstly, the multiple region frequency allocation (MRFA) scheme is proposed for non-uniform user distribution to alleviate interference among users and allocate spectrum resources equally to dense users. This scheme is modelled as a sub-region partition problem with maximum sum rate, which can disperse densely distributed users to different sub-bands for transmission. Secondly, the convergent power control (CPC) algorithm is considered to improve the transmission performance of each user. It can converge the transmit power to the optimal transmit power for reducing interference among co-channel users when there is no disturbance in the network. The CPC algorithm can also make the signal-to-interference-plus-noise-ratio (SINR) of each active user always greater than the target threshold until the end of communication by dynamically adjusting the transmit power of users. Simulation results show that the joint scheme of MRFA and CPC achieves a higher system throughput and better user performance than existing frequency allocation schemes or power control schemes. [ABSTRACT FROM AUTHOR]

In this paper, we consider power allocation in multiband cognitive radio (CR) networks, where multiple secondary users (SUs) transmit via a common relay and compete for the transmit power of the relay. We employ a hybrid overlay/underlay spectrum sharing scheme, allowing the SU to adapt its way of accessing the licensed spectrum to the status of the primary user (PU). If the PU is detected to be idle at the selected channel, the SU works in an overlay mode; else, it works in spectrum underlay. In addition, an auction-based power-allocation scheme is proposed to solve power competition of multiple SUs. For the SU working in spectrum overlay, the relay allocates the power in proportion to its payment without additional constraints; for the SU in spectrum underlay, its own transmit power and that of the relay are upper bounded for the quality of service (QoS) of the PU. Then, the convergence of the proposed auction algorithm and the outage probability of secondary transmissions is theoretically analyzed. Finally, the performance of the proposed scheme is verified by the simulation results. [ABSTRACT FROM PUBLISHER]

Interference alignment (IA) is a promising technique for interference management and can be applied to spectrum sharing in cognitive radio (CR) networks. However, the sum rate may fall short of the theoretical maximum, particularly at low signal-to-noise ratio (SNR), and the quality of service (QoS) of the primary user (PU) may not be guaranteed. In addition, power allocation (PA) in IA-based CR networks is largely ignored, which can further improve its performance. Thus, in this paper, PA in IA-based CR networks is studied. To guarantee the QoS requirement of the PU, its minimal transmitted power is derived. Then, we propose three PA algorithms to maximize the throughput of secondary users (SUs), the energy efficiency (EE) of the network, and the requirements of SUs, respectively, while guaranteeing the QoS of the PU. To reduce the complexity, the closed-form solutions of these algorithms are further studied in detail. The outage probability of the PU according to its rate threshold is also derived to analyze the performance of these algorithms. Moreover, we propose a transmission-mode adaptation scheme to further improve the PU's performance when its QoS requirement cannot be guaranteed at low SNR, and it can be easily combined with the proposed PA algorithms. Simulation results are presented to show the effectiveness of the proposed adaptive PA algorithms for IA-based CR networks. [ABSTRACT FROM AUTHOR]

In this paper, observing the information asymmetry phenomenon among multiple secondary users (SUs) spectrum sharing, we analyze the hierarchical decision-making and the strategic interaction of information-poor and information-rich SUs. A Stackelberg capacity-maximization game is formulated with leaders and followers, and closed-form solutions are mathematically derived for the optimal Stackelberg equilibrium solution. Moreover, the existence and uniqueness of equilibrium solutions are investigated via the quasi-variational inequality method. Finally, the distributed algorithm with partial asymmetric information awareness is designed to reach the solution. Numerical results demonstrate that the proposed algorithm achieves improved individual and system performance with mild condition on the ratio of information-poor leaders and information-rich followers. [ABSTRACT FROM PUBLISHER]

Cognitive radio (CR) is currently one of the most promising solutions for designing spectrum-efficient wireless communication systems. In this paper, we present a greedy cognitive access policy that handles spectrum sensing with the tools of image processing. By means of the Wigner–Ville transform (WVT), we are able to analyze the time and frequency features of the received interference, and represent them on a time–frequency grid as an image in which brightness reveals the spectrum occupancy. According to sensed interference, each secondary user autonomously tries to access the grid following a multiple-division principle, i.e., by properly shaping the signal in the code, time, and frequency domains. In detail, this is realized by processing the WVT to derive the shaping mask (and the matching algorithm) that allows the filling up of the “time spectrum holes.” Numerical simulations and a test-bed implementation show how the proposed scheme outperforms selected state-of-the-art approaches while still presenting an affordable computational cost. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communication has attracted substantial research attention recently, due to its potential to improve coverage, spectrum efficiency, and energy efficiency within the existing cellular infrastructure. One major challenge for spectrum resource sharing in D2D underlay lies in the mutual interference between cellular user equipments (CUEs) and D2D user equipments (DUEs). Considering this mutual interference constraint, this work investigates the problem of optimal matching of D2D links and CUEs to form spectrum-sharing partners to maximize ergodic sum rates under transmit power and outage constraints. Unlike previous works, full channel-state information (CSI) is not required. To solve the resulting high-complexity problem, candidate DUE sets are first narrowed down according to required outage probability constraints, which are used to construct a simplified bipartite graph. The weight of the bipartite graph is characterized as the maximization of ergodic sum rate of the associated D2D and cellular links under outage constraints for which a low-complexity algorithm is proposed to solve the nonconvex problem. After constructing the bipartite graph, the Hungarian algorithm is used to determine the optimal pairing between D2D links and CUEs. Numerical results demonstrate that the proposed algorithm can improve the outage-constrained spectrum efficiency of D2D networks with practical complexity. [ABSTRACT FROM PUBLISHER]

In consideration of an orthogonal-frequency-division-multiplexing access cognitive two-way relay network with imperfect spectrum sensing, we propose a joint resource allocation algorithm to maximize the total transmission rate of secondary users (SUs) under maximum transmit power constraints and interference temperature constraints. To solve this joint optimization problem, we use the Lagrange dual decomposition method, discrete searching approach, and the Hungarian algorithm to obtain the optimal power allocation, the subcarrier pairing matrix, and the relay selection matrix. Moreover, the analyses of feasibility, sensitivity, convergence, and calculation complexity of the proposed algorithm are given. The effectiveness and validity of this algorithm with imperfect spectrum sensing are proved by the simulations of system performance and comparisons with the algorithm with perfect spectrum sensing. The results also indicate that our algorithm can provide protection for primary user (PU), while SUs and relays opportunistically access the spectrum occupied by PU. [ABSTRACT FROM AUTHOR]