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We investigate coordinated regularized zero-forcing (RZF) precoding for limited feedback multicell multiuser (MU) multiple-input–single-output (MISO) systems. We begin by deriving an approximation to the expected signal-to-interference-plus-noise (SINR) ratio for the proposed scheme with perfect channel direction information (CDI) at the base station (BS). We also derive an expected SINR approximation for limited feedback systems with random vector quantization (RVQ)-based codebook CDI at the BS. Using the expected interference result for the RVQ-based limited feedback CDI, we propose an adaptive feedback bit allocation strategy to minimize the expected interference by partitioning the total number of bits between the serving and out-of-cell interfering channels. Numerical results show that the proposed adaptive feedback bit allocation method offers a spectral efficiency gain over the existing coordinated zero-forcing (ZF) scheme. [ABSTRACT FROM PUBLISHER]

The communication channel power gain to the nearest neighbor of a node in a wireless communication network is not necessarily the largest among all neighbors due to fading. The probability that the $k$th nearest neighbor of a node has the best communication channel with the highest power gain in a 2-D network with homogeneous Poisson distribution of nodes is derived for a general fading environment. The result is specialized to the case where the communication links are modeled as generalized-gamma fading channels. The analytical results are verified and illustrated by computer simulations and numerical results. Some applications of the new theory are also presented. A novel criterion that represents the fading severity, i.e., the generalized amount of fading (GAF) , is defined, and its value as an important measure for fading channels is justified. [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]

Small-cell network is a promising solution to the high video traffic. However, it has some fundamental problems, i.e., high backhaul cost, quality of experience (QoE), and interference. To address these issues, we propose a cooperative transmission strategy for video transmission in small-cell networks with caching. In the scheme, each video file is encoded into segments using a maximum distance separable rateless code. Then, a portion of each segment is cached at a certain small-cell base station (SBS), so that the SBSs can cooperatively transmit these segments to users without incurring high backhaul cost. QoE When there is only one active user in the network, a greedy algorithm is utilized to deliver the video-file segment from the SBS with good channel state to the user watching videos in real time. This reduces video freezes and improves the QoE. When there exist several active users, interference will appear among them. To deal with interference, interference alignment (IA) is adopted. Based on the scheme for a single user, the greedy algorithm and IA are combined to transmit video-file segments to these users, and the performance of the system can be significantly improved. Simulation results are presented to show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Filter bank multicarrier systems with quadrature amplitude modulation (FBMC/QAM) have drawn attentions to get the advantage of complex symbol transmission, as well as very low out of band radiation and relaxed synchronization requirements for asynchronous scenarios. In order to make this system viable for practical deployment, the biggest challenge is designing appropriate filters to minimize the interference between adjacent subcarriers, while maintaining the Nyquist property of the filter. We show that the deviation from the Nyquist property can be compensated through the fractional shift of the filtered symbols, which provides flexibility to optimize the stopband of the filter. The proposed design method shows advantages over the state of the art designs, and provides guidance for the filter design in practical FBMC/QAM systems. [ABSTRACT FROM AUTHOR]

Interference alignment (IA) is widely regarded as a promising interference management technique for wireless networks and its potential is most profound in interference-intensive environments. This motivates us to study IA for multicast communications in multihop MIMO networks, which are rich in interference by nature. We develop a set of linear constraints that can characterize a feasible design space of IA for multicast communications. The set of linear constraints constitutes a simple mathematical model of IA that allows us to conduct cross-layer multicast throughput optimization in multihop MIMO networks, but without getting involved into the onerous signal design at the physical layer. Based on the mathematical model of IA, we formulate a multicast throughput maximization problem and develop an approximation solution that can achieve $(1-\varepsilon)$ -optimality. Simulation results show that the use of IA can significantly increase the multicast throughput in multihop MIMO networks and the throughput gain increases with the volume of multicast traffic and the number of antennas. [ABSTRACT FROM AUTHOR]

By allowing two nearby mobile devices to communicate via a direct link between them, device-to-device (D2D) communications can efficiently increase the capacity of D2D-underlaid cellular networks, in which D2D and cellular communications share the same frequency band. However, the coexistence of D2D and cellular communications in the same frequency band will cause interference between the D2D and cellular users, thus degrading their performance. One may control the transmit power based on the real-time channel-state information (CSI) to mitigate this interference, but it is difficult to acquire the real-time CSI between D2D/cellular transmitters and D2D receivers. To overcome this difficulty, we propose novel statistical-feature-based power control (SFPC), which determines the transmit power based on statistical (instead of real-time) CSI. The proposed SFPC combines the power control—that is aware of D2D success likelihood—with opportunistic access control to 1) reduce the interference caused by D2D communications and 2) maximize the area spectral efficiency of D2D communications. Specifically, it aims to minimize the D2D transmit power and optimize the selection of access threshold. Our simulation results show that SFPC can increase both the cellular communication success probability and the energy efficiency of D2D communications, as well as reduce the average D2D transmit power. [ABSTRACT FROM PUBLISHER]

As the base of quality-of-service (QoS) guarantee and system optimizing, performance analysis is very important for interference-limited networks. The performance of a user is closely related to its service rate. However, in interference-limited networks, the transmissions of users interfere with each other, and the power control and unsaturated traffic make the interference relationship among users more complicated. Hence, the service rates of users are correlated with each other and are difficult to derive. According to the relation between the queue length and the service rate, we propose an $N$- dimensional Markov chain, which models queue states of users, to study the performance of an interference-limited system. By calculating the conditional service rate, which is only related to the channel quality given the power policy, the transition matrix is derived. By using the transition matrix, we solve the Markov chain and obtain the stationary probability of the queue length of each user, which enables the calculations of other performance metrics, i.e., delay and packet overflow probability, and so on. Furthermore, to reduce the computational complexity, we decompose the proposed $N$- dimensional Markov chain. Then, based on the decomposition, we propose an iterative algorithm. The comparisons between simulation results and analytical results under different scenarios verify that our method can provide good estimations of each user's performance. The results derived by our method can determine the condition under which the power control algorithm for the saturated system is suitable in unsaturated networks and in which the new power policy is needed. [ABSTRACT FROM PUBLISHER]

Achievable degrees of freedom (DoF) of the large-scale interfering two-way relay network is investigated. The network consists of $K$ pairs of communication nodes (CNs) and $N$ relay nodes (RNs). It is assumed that $K\ll N$ and that each pair of CNs communicates with each other through one of the $N$ RNs without a direct link between them. Interference among RNs is also considered. Assuming local channel state information (CSI) at each RN, a distributed and opportunistic RN selection technique is proposed for the following three promising relaying protocols: amplify-and-forward (AF), decode-and-forward (DF), and compute-and-forward (CF) relaying protocols. As a main result, the asymptotically achievable DoF is characterized as $N$ increases for the three relaying protocols. In particular, a sufficient condition on $N$ required to achieve the certain DoF of the network is analyzed. Through extensive simulations, it is shown that the proposed RN selection techniques outperform conventional schemes in terms of achievable rate, even in practical communication scenarios. Note that the proposed technique operates with a distributed manner and requires only local CSI, leading to easy implementation for practical wireless systems. [ABSTRACT FROM AUTHOR]

The complexity and uncertainty inherent in large cellular networks make the acquisition of location and channel information of all but perhaps a few neighboring network nodes (base stations (BSs)) difficult for a given user. Therefore, a cell association policy must operate with sparse information. Thus, the serving BS is proposed to be the one that provides the highest instantaneous signal-to-interference ratio (SIR) from among all BSs providing average received signal power exceeding a predetermined minimum. This policy is evaluated for the downlink of single-tier (homogeneous) and two-tier (heterogeneous) networks, and for the latter, the key advantage of the proposed policy is its capability to enable traffic offloading. Two methods to determine the minimum average signal power are given. Coverage probabilities and average rates of mobile stations in coverage are derived, accounting for path loss, multipath fading, and random locations of BSs in each tier. Analysis is verified by Monte Carlo simulations. We observe that the instantaneous SIR and average received signal power of a few BSs are sufficient to achieve the coverage corresponding to the highest SIR association, which in general requires instantaneous SIR information of a larger subset of a network. We also observe that in a two-tier network, the effect of strong interference from high-power BSs, such as macro BSs, can be limited by proper choice of minimum average received signal power for low-power BSs. [ABSTRACT FROM PUBLISHER]

We investigate the heterogeneous cellular network (HetNet) where the macrocell base stations (MBSs) are equipped with very large antenna arrays. Since such a combined massive multi-input multi-output (MIMO) and HetNet system operates in the co-channel time-division duplex mode, to mitigate the pilot contamination effect to channel estimation, the number of users that can be served simultaneously is limited by the available pilot resources in the conventional designs. We propose a pilot reuse scheme for massive MIMO–HetNet to increase the user capacity. Specifically, location-aware channel estimation is employed at the MBSs to mitigate the severe pilot contamination introduced by pilot reuse, and we propose a novel pilot assignment algorithm to reduce the interference in HetNets. Simulation results demonstrate that our proposed scheme can support more users and increase both the uplink and the downlink sum-rate capacity, in comparison to the conventional scheme, particularly when the antenna number at the MBSs is sufficiently large. [ABSTRACT FROM AUTHOR]

The high-speed railway wireless communication network architecture is gradually transforming from a traditional GSM-Railway (GSM-R) cellular network to a 5G heterogeneous ultra-dense communication network. How to effectively deal with the interference while obtaining the capacity gain has become an inevitable problem. This article proposes a power allocation interference alignment algorithm based on game equilibrium with the goal of joint optimization about throughput and energy efficiency for imperfect channels in high-speed railway communication. Firstly, the imperfect Channel State Information including delay and fading is calculated. Then, in order to improve system throughput and energy efficiency, we establish a game model and prove the existence of Nash equilibrium in the model. At the same time, a power allocation iterative algorithm based on Recurrent Neural Network is proposed. Finally, combined with the interference alignment algorithm based on a maximal signal-to-noise ratio, the optimal power matrix is calculated by iteration to achieve interference management optimization. The simulation results prove that our algorithm has superior performance in improving the system throughput, energy efficiency and transmission reliability in high-speed railway wireless communication with imperfect channels. [ABSTRACT FROM AUTHOR]

A multi-user multiple-input single-output simultaneous wireless information and power transfer full-duplex system with imperfect channel state information is considered. Under the assumption that the unknown channel estimation error is within a certain range, the self-interference cannot be suppressed completely at the base station and at the multi-user nodes. The proposed design problem is formulated as maximizing the average harvested energy of multi-user nodes and maintaining the signal-to-interference-plus-noise ratio requirement, which is proved to be non-convex. Utilizing semidefinite relaxation and S-procedure methods, a convex optimization problem of optimal beamforming vector for the multi-antenna transmitter is obtained. Moreover, semidefinite relaxation is proved to be tight by showing the existence of rank-one optimal solutions. Simulation results are presented to verify the robustness and effectiveness of the proposed algorithm compared with the non-robust design. [ABSTRACT FROM AUTHOR]

We investigate the secrecy performance of a multiuser diversity scheme for an interference-limited wireless network with a base station (BS), $N$ legitimate users, and an eavesdropper in the presence of a single dominant interferer. Assuming interference dominates noise power at the eavesdropper and at each legitimate user's receiver, the BS transmits information to the legitimate user with the $k$ th best (highest) signal-to-interference ratio. We derive a closed-form expression for the secrecy outage probability for an arbitrary $N$ and an asymptotic expression for a fixed $k$ and large $N$. Furthermore, we derive a closed form asymptotic expression for the ergodic secrecy capacity of the $k$ th best user and shows that it scales like $O\left(\log (N)\right)$ for a fixed $k$ and large $N$. [ABSTRACT FROM AUTHOR]

Cognitive radio and heterogeneous wireless networks are important candidate techniques for the fifth generation (5G) communication systems. On the other hand, propagation properties of radio channels in a physical layer are exploited to design efficient secure transmission schemes for 5G wireless networks. In this work, a security-aware joint power and subchannel allocation problem based on the inter-network cooperation is investigated at cognitive heterogeneous networks via imperfect spectral sensing. The security-aware joint power and subchannel allocation is subject to constraints in available subchannels, proportional fairness secrecy transmission rates among secondary mobile terminals (MTs), total interference power threshold, and total power for each secondary MT. In order to determine the impact of imperfect spectral sensing to resource allocation, we first represent the interference power at primary base station in terms of the misdetection probability and false alarm probability. Then, the security-aware power and subchannel allocation problem with inter-network cooperation is formulated as a biconvex optimization problem, and an optimal security-aware power and subchannel allocation algorithm is proposed utilizing the dual decomposition method. Compared to the heuristic power and subchannel allocation algorithms, numerical simulation results show that the proposed algorithms improve the total secrecy throughput and guarantee the proportional fairness among different secondary MTs. [ABSTRACT FROM AUTHOR]

We consider the problem of link scheduling in multihop wireless networks subject to interference constraints. We consider a graph-based representation of wireless networks where scheduled links adhere to the $K$ -hop link interference model. For this scheduling problem, we develop an asynchronous and distributed greedy heuristic. Furthermore, we show that this distributed heuristic computes the exact same schedule as the well-known centralized greedy link scheduling algorithm. [ABSTRACT FROM AUTHOR]

In this correspondence, an uplink nonorthogonal multiple access (NOMA) system where the base station (BS) trends to decode the independent information of users occupying the same radio resource simultaneously is considered. Different from the traditional successive interference cancellation (SIC) decoding scheme where the later decoding can only be processed after the successful decoding of the previous users, an advanced SIC decoding strategy is proposed to achieve outage balancing for the later decoded users. Under the proposed SIC decoding mechanism, the BS regards the unsuccessfully decoded users’ information as the interference on the following users, i.e., even the outage occurs for any of the previous decoded users, the BS will still try to decode the following users’ information. The outage performance with the new decoding strategy is theoretically analyzed. The closed-form expressions of the outage probability for each user are derived for an uplink 2-user NOMA system. The accuracy of the theoretical results is verified by the simulations. [ABSTRACT FROM AUTHOR]

A cooperative wireless-powered communication network protocol is proposed, in which user far away from a hybrid access point (H-AP) is capable of harvesting wireless powers by overhearing the uplink signals of users that are relatively nearer to the H-AP, in addition to downlink signal broadcast by the H-AP. In this setting, time allocations for the downlink transmission of the H-AP and the uplink transmission for the users are jointly optimized for two different purposes. First, the weighted sum-rate maximization problem is solved for a given total transmission time. Then, the total transmission time is minimized under a minimum rate constraint, and an efficient algorithm is also presented to solve the optimal solution by a line search strategy. Numerical results demonstrate that the proposed schemes significantly increase the far user's rate, which in turn improves user fairness and transmission delay. [ABSTRACT FROM PUBLISHER]

As a benefit of sophisticated interference cancelation techniques, full-duplex (FD) transceiver design may become feasible, even possibly on the aggressive time-scale of fifth-generation (5G) wireless communication systems. Hence, we further develop the recent bidirectional relaying [i.e., the two-way half-duplex (HD) relaying] aided cooperative network to its more radical counterpart, which entirely consists of FD entities for the sake of adapting to emerging FD communication scenarios. In more detail, the proposed bidirectional relaying-aided FD network operates in a decode-and-forward (DF) style and exploits the advanced network coding (NC) concept. We analyze its achievable error-free data rate, where the effects of both the self-interference (SI) and of the geographic location of the relay node (RN) are evaluated. Furthermore, the potential variations of the networking scenario are also taken into account. Based on this theoretical analysis, the optimum rate allocation scheme maximizing the system's error-free data rate is found. Our results demonstrate that a significant spectral efficiency gain is achieved by the proposed system. [ABSTRACT FROM PUBLISHER]

An interference alignment (IA) transceiver design scheme for multiple-input–multiple-output (MIMO) multicell multiuser wireless communication systems is proposed by minimizing the maximum mean square error (MSE) of the received symbols to improve fairness among users. The formulated Min-Max MSE optimization problem is not jointly convex on the transmit precoders and receive filters and, thus, is very difficult to solve directly. An iterative method is proposed to solve the optimization problem to get a suboptimal solution instead. Considering that if the receive filters are fixed, the Min-Max MSE problem can be reformulated as a second-order cone programming problem, and if the transmit precoders are fixed, the closed-form receive filters minimizing the receive MSE can be easily obtained, and the formulated Min-Max MSE problem is solved by alternatively optimizing the transmit precoders and the receive filters. The convergence of the proposed algorithm is proved, which shows its feasibility. Furthermore, a robust Min-Max MSE algorithm is proposed to counter the channel uncertainty. Simulation results show that the proposed Min-Max MSE algorithm can achieve IA when the antennas are configured to be strong IA proper and when the users in the network are of the same signal-to-noise ratio (SNR). Analysis indicates that the proposed Min-Max IA transceiver design scheme can significantly improve user fairness with a possible cost of sum-rate reduction. Results also show that the proposed robust design algorithm provides better performance when lacking perfect channel state information (CSI). [ABSTRACT FROM AUTHOR]