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This paper studies an unmanned aerial vehicle (UAV)-enabled two-user interference channel for wireless powered communication networks (WPCNs). In this system, two UAVs wirelessly charge two low-power Internet-of-things (IoT)-devices on the ground and collect information from them. We consider two scenarios when both UAVs cooperate in energy transmission and/or information reception via interference coordination and coordinated multi-point (CoMP), respectively. For both scenarios, the UAVs’ trajectories are designed to not only enhance the wireless power transfer (WPT) efficiency in the downlink, but also mitigate the co-channel interference for wireless information transfer (WIT) in the uplink. In particular, the objective is to maximize the uplink common (minimum) throughput of the two IoT-devices over a finite UAV mission period, by jointly optimizing the trajectories of both UAVs and the downlink/uplink wireless resource allocation, subject to the maximum flying speed and collision avoidance constraints for UAVs, as well as the individual energy neutrality constraints at IoT-devices. Under both scenarios with interference coordination and CoMP, we first obtain the optimal solutions to the two common-rate maximization problems for the special case with sufficiently long UAV mission duration. Next, we obtain high-quality solutions for the practical case with finite UAV mission duration by using the alternating optimization and successive convex approximation (SCA). Numerical results show that the proposed designs significantly outperform benchmark schemes, and the utilization of CoMP achieves much higher uplink throughput than interference coordination. [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, a low-feedback-sampling-rate digital predistortion (DPD) method is proposed for wideband wireless transmitters and radio-frequency power amplifiers (PAs). This DPD method inserts a non-ideal real band-pass filter into the feedback loop to limit the feedback bandwidth. Meanwhile, to recover the band-limited feedback signal, it introduces a signal-recovery module that is based on the deep neural network (DNN). A data-preprocessing technique is proposed to reduce the amount of input data for the DNN and thereby significantly reducing its structural complexity. Also, the use of DNN makes it feasible to implement off-line training. Both the simplicity of the proposed DNN and the availability of off-line training reduce the system complexity in DPD. Experimental validation was performed on a PA driven by wideband orthogonal-frequency-division-multiplexing (OFDM) signals. The results demonstrated the superiority of the proposed method in under-sampling applications. The proposed DPD method achieved the same linearization performance as the state-of-art DPD methods while requiring a sampling rate that was approximately 5% less. Meanwhile, the proposed DPD method has been validated to have stronger anti-noise and generalization capabilities. [ABSTRACT FROM AUTHOR]

This paper is devoted to attitude tracking control of fractionated spacecraft with wireless communication. We consider the practical case that the spacecraft suffers from uncertain inertia parameters, external disturbances, and even unknown and time-varying actuator faults. Within the framework of the backstepping method, a novel event-triggered adaptive fault-tolerant control scheme is proposed. In our design, an event-triggering mechanism is introduced to determine the time instants for communication, which successfully avoids continuous communication and Zeno phenomenon. Then, with the aid of a bound estimation approach and a smooth function, the impacts of the actuator faults, as well as the network-induced error, are effectively compensated for. Moreover, by employing the prescribed performance control technique, it is shown that the attitude tracking errors can converge to predefined arbitrarily small residual sets with prescribed convergence rate and maximum overshoot, no matter if there exist unknown actuator faults. Compared with conventional adaptive attitude control schemes, the proposed scheme significantly reduces the communication burden, while providing high reliability and stable, rapid, and accurate response for attitude maneuvers. Simulation results are presented to illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Strong correlation of link gains over multiple wavelengths has been demonstrated in non-line-of-sight optical wireless scattering communication. In this paper, we further demonstrate the strong correlation of the channel impulse responses for different wavelengths. A novel channel estimation method is proposed based on such correlation, where only certain reference wavelengths are assigned with pilot signals. On each channel assigned by the pilot signal, we adopt an improved least-squares method to estimate the channel tap coefficients and the tap length. The channel tap coefficients for other wavelengths can be estimated based on the inter-wavelength correlation. Under the proposed channel estimation, the channel estimation accuracy can be improved as shown by the simulations. We further propose an optimization method for the correlation-based channel estimation pilot pattern based on the receiver channel state feedback. Simulation results show that optimized pilot pattern can achieve significant performance gain over the fixed pilot pattern. Moreover, the channel estimation performance is insensitive to the channel state feedback frequency. [ABSTRACT FROM AUTHOR]

With the proliferation of portable devices, the exponential growth of the global mobile traffic brings great challenges to the traditional communication networks and the traditional wireless communication technologies. In this context, converged networks and cache-based data offloading have drawn more and more attention based on the strong correlation of services. This paper proposes a novel popular services pushing and caching scheme by using converged overlay networks. The most popular services are pushed by terrestrial broadcasting networks. And they are cached in ${n}$ router-nodes with limited cache sizes. Each router-node only interconnects with its neighbor nodes. Users are served through the router’s WiFi link. If the services requested are cached in the routers, the user can be immediately responded; otherwise, the requests can be responded through the link from cellular stations to the router. In the proposed scheme, the cache size of the router, the maximum number of requests each router can serve, and the whole-time delay are limited. Three node-selecting and dynamic programming algorithms are adopted to maximize the equivalent throughput. Analytical and numerical results demonstrate that the proposed scheme is very effective. [ABSTRACT FROM AUTHOR]

The conventional orthogonal multiple-access-based downlink transmission for the differential chaos shift keying system with pulse-position modulation (PPM-DCSK) suffers from lower energy efficiency and data rate. To tackle this problem, a low-complexity superposition coding PPM-DCSK (SC-PPM-DCSK) system for downlink multi-user chaotic communication is proposed in this paper. The proposed system exploits the superposition coding principle on the reference signal and the information-bearing signal to achieve multi-user simultaneous information transmission for the downlink scenario, thus significantly improving the energy efficiency and transmission rate. Furthermore, the analytical expression for the error performance and the throughput of the proposed system are precisely derived over additive white Gaussian noise and multipath Rayleigh fading channels. Simulation results not only verify the accuracy of the analytical method but also illustrate the proposed transmission scheme in achieving significant performance gain compared with the time-sharing-based PPM-DCSK and multiresolution DCSK systems. Due to such superiority, the proposed SC-PPM-DCSK system can be deemed to be an outstanding scheme for downlink multi-user short-range wireless communications. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output (MIMO) is a technical hotspot in physical layer with numerous applications in wireless communications, radars, sonars, and well beyond. In this paper, we focus on the multi-dimensional angle estimation problem in a bistatic electromagnetic vector sensors (EMVS) MIMO system. Namely, we need to simultaneously estimate two-dimensional (2D) direction-of-arrival (DOA), 2D direction-of-departure (DOD), 2D receive polarization angle (RPA) and 2D transmit polarization angle (TPA). To tackle this issue, a parallel factor (PARAFAC) analysis-based estimator is proposed. Firstly, a third-order PARAFAC analysis data model is established, which can efficiently exploit the tensor structure of the array measurement. After performing PARAFAC decomposition on the tensor measurement, the factor matrices are achieved. By combining the estimation method of signal parameters via rotational invariance technique (ESPRIT) with the vector cross-product method, joint estimates of 2D-DOD, 2D-DOA, 2D-TPA and 2D-RPA are obtained without further pairing calculation. Compared with the state-of-the-art ESPRIT-Like approach, the proposed method can achieve better performance by enforcing the third-order structure information, and it is suitable for arbitrary array manifolds. Theoretical analyses are given and numerical results corroborate our analysis. [ABSTRACT FROM AUTHOR]

In this paper, we study the arbitrarily varying broadcast channel (AVBC) when the state information is available at the transmitter in a causal manner. We establish the inner and outer bounds on both the random code capacity region and the deterministic code capacity region with degraded message sets. The capacity region is then determined for a class of channels satisfying a condition on the mutual information between the strategy variables and the channel outputs. As an example, we consider the arbitrarily varying binary symmetric broadcast channel. We show the cases where the condition holds and, hence, the capacity region is determined and other cases where there is a gap between the bounds. This gap shows that the minimax theorem does not hold for rate regions. [ABSTRACT FROM AUTHOR]

This paper presents two secure transmission algorithms for millimeter-wave wireless communication, which are computationally attractive and have analytical solutions. In the proposed algorithms, we consider phased-array transmission structure and focus on phase shift keying (PSK) modulation. It is found that the traditional constellation synthesis problem can be solved with the aid of polygon construction in the complex plane. A detailed analysis is then carried out and an analytical procedure is developed to obtain a qualified phase solution. For a given synthesis task, it is derived that there exist infinite weight vector solutions under a mild condition. Based on this result, we propose the first secure transmission algorithm by varying the transmitting weight vector at symbol rate, thus resulting exact phases at the intended receiver and producing randomnesses at the undesired eavesdroppers. To improve the security without significantly degrading the symbol detection reliability for target receiver, the second secure transmission algorithm is devised by allowing a relaxed symbol region for the intended receiver. Compared to the first algorithm, the second one incorporates an additional random phase rotation operation to the transmitting weight vector and brings extra disturbance for the undesired eavesdroppers. Different from the existing works that are only feasible for the case of single-path mmWave channels, our proposed algorithms are applicable to more general multi-path channels. Moreover, all the antennas are active in the proposed algorithms and the on-off switching circuit is not needed. Simulations are presented to demonstrate the effectivenesses of the proposed algorithms under various situations. [ABSTRACT FROM AUTHOR]

This paper studies caching in $(K\!+\!L\!-\!1)\!\times \!K$ partially connected wireless linear networks, where each of the $K$ receivers locally communicates with $L$ out of the $K\!+\!L\!-\!1$ transmitters, and caches are at all nodes. The goal is to design caching and delivery schemes to reduce the transmission latency, by using normalized delivery time (NDT) as the performance metric. For small transmitter cache size (any $L$ transmitters can collectively store the database just once), we propose a cyclic caching strategy so that each of every $L$ consecutive transmitters caches a distinct part of each file; the delivery strategy exploits coded multicasting and interference alignment by introducing virtual receivers. The obtained NDT is within a multiplicative gap of 2 to the optimum in the entire cache size region, and optimal in certain region. For large transmitter cache size (any $L$ transmitters can collectively store the database for multiple copies), we propose a modified caching strategy so that every bit is repeatedly cached at consecutive transmitters; the delivery strategy exploits self-interference cancellation and interference neutralization. By combining these schemes, the NDT is optimal in a larger region. We also extend our results to linear networks with heterogeneous receiver connectivity and partially connected circular networks. [ABSTRACT FROM AUTHOR]

Accurately modeling and predicting wireless channelquality variations is essential for a number of networking applications such as scheduling and improved video streaming over 4G LTE networks and bit rate adaptation for improved performance in WiFi networks. In this paper, we design DeepChannel, an encoder-decoder based sequence-to-sequence deep learning model that is capable of predicting future wireless signal strength variations based on past signal strength data. We consider two different versions of DeepChannel; the first and second versions use LSTM and GRU as their basic cell structure, respectively. In contrast to prior work that is primarily focused on designing models for particular network settings, DeepChannel is highly adaptable and can predict future channel conditions for different networks, sampling rates, mobility patterns, and communication standards. We compare the performance (i.e., the root mean squared error, mean absolute error and relative error of future predictions) of DeepChannel with respect to two baselines—i) linear regression, and ii) ARIMA for multiple networks and communication standards. In particular, we consider 4G LTE, WiFi, WiMAX, an industrial network operating in the 5.8 GHz range, and Zigbee networks operating under varying levels of user mobility and observe that DeepChannel provides significantly superior performance. Finally, we provide a detailed discussion of the key design decisions including insights into hyper-parameter tuning and the applicability of our model in other networking scenarios. [ABSTRACT FROM AUTHOR]

Integration of backscatter communication and wireless powered communication is a promising way to improve the performance of future Internet of Things (IoT) networks. However, this integration needs to be studied in practical scenarios with realistic models for the network elements. In this paper, we investigate optimal resource allocation in a backscatter assisted wireless powered communication network (BS-WPCN), where a piece-wise linear energy harvesting (EH) model is assumed at the users, which accounts for the saturation effect of practical energy harvesters. We study the problem of throughput maximization and apply a block coordinate descent (BCD) method to find the optimal allocation of resources for maximizing the total throughput. Numerical results demonstrate that the proposed scheme considerably improves the performance compared to the baseline scheme, which assumes linear EH model at the users. [ABSTRACT FROM AUTHOR]

This paper presents an integrated platoon control framework for heterogeneous vehicles on curved roads with varying slopes, aerodynamic drag, and wireless communication delays. First, a linear heterogeneous vehicle platoon model with decoupled longitudinal and lateral dynamics is built based on nonlinear feedback linearization and arc-length parametric transformation of an arbitrary curved road. The external disturbances are also considered, including the up-down road slopes, wind and equivalent time-delays caused by the wireless communication delay and discrete data in onboard sensors. Second, to achieve stable platoon control on a curved road, the platoon uses the state-feedback control method in the longitudinal direction while each vehicle tracks the centerline of the curved road to realize lateral control. Longitudinally, an $ H_\infty$ platoon controller is designed based on the Lyapunov-Krasovskii functional to ensure the inner-vehicle and string stability of the platoon, which suffers from parameter uncertainty, and external disturbances. Additionally, the $ \mathcal {L}_2$ string stability is defined to guarantee that the perturbations do not grow unbounded as they propagate through the platoon. Simulation results indicate that the proposed robust controller achieves proper platoon intervehicle spacing in both the longitudinal and lateral directions. [ABSTRACT FROM AUTHOR]

Radio Frequency Identification (RFID) is a widely used wireless communication technology. In terms of mobile RFID tags, the relative position between the tags and the reader changes, and consumers can obtain product-related information in tags by using readers. Anti-collision is an important scheme for readers to identify RFID tags. Tag estimation is at the core of the efficient anti-collision process, especially when tags move. In this paper, we propose a Mobile tags Identification Procedure model (MTIP), and establish a feasible mobile tags estimation model based on MTIP. In the mobile tags estimation model, we use superposition principle of Poisson process to solve the tag estimation problem. Based on these models, a new anti-collision algorithm specifically for the mobile RFID tags is proposed. Performance evaluation shows that the proposed algorithm significantly outperforms classical Q algorithm of the Electronic Product Code Class-1 Generation-2 system (EPC-C1G2) and the recent Symbolic Single Resolution Blocking (SSRB) algorithm in terms of success-rate and achieves similar efficiency for static RFID system. [ABSTRACT FROM AUTHOR]

Friendly jamming is an unconventional approach to secure wireless communications. Specifically, a friendly jammer transmits jamming signals to an eavesdropper while a legitimate transmitter is sending data. The jamming signals only interfere with the eavesdropper, and thus, prevent data from being disclosed to unintended parties. Mainstream jamming schemes adopt a continuous jamming strategy (CJS), where the jammer is required to constantly transmit jamming signals in the entire duration of the legitimate transmission. In certain scenarios, however, the CJS may lead to excessive jamming, and cause a waste of energy and the degradation of jamming efficiency. To address the drawbacks of the CJS, we propose the concept of an intermittent jamming strategy (IJS), where a jammer alternates between jamming and non-jamming modes during the legitimate transmission. In this paper, we study the feasibility of the IJS for physical layer security. We first introduce a new metric to jointly measure security requirements and energy costs. Next, we formulate and solve an optimization problem with respect to the jamming duration proportion and the jamming power. Finally, we verify the feasibility of the IJS through extensive simulation experiments under different modulation methods. [ABSTRACT FROM AUTHOR]

This paper investigates a new scenario of spectrum sharing between unmanned aerial vehicle (UAV) and terrestrial wireless communication, in which a cognitive/secondary UAV transmitter communicates with a ground secondary receiver (SR), in the presence of a number of primary terrestrial communication links that operate over the same frequency band. We exploit the UAV’s mobility in three-dimensional (3D) space to improve its cognitive communication performance while controlling the co-channel interference at the primary receivers (PRs), such that the received interference power at each PR is below a prescribed threshold termed as interference temperature (IT). First, we consider the quasi-stationary UAV scenario, where the UAV is placed at a static location during each communication period of interest. In this case, we jointly optimize the UAV’s 3D placement and power control to maximize the SR’s achievable rate, subject to the UAV’s altitude and transmit power constraints, as well as a set of IT constraints at the PRs to protect their communications. Second, we consider the mobile UAV scenario, in which the UAV is dispatched to fly from an initial location to a final location within a given task period. We propose an efficient algorithm to maximize the SR’s average achievable rate over this period by jointly optimizing the UAV’s 3D trajectory and power control, subject to the additional constraints on UAV’s maximum flying speed and initial/final locations. Finally, numerical results are provided to evaluate the performance of the proposed designs for different scenarios, as compared to various benchmark schemes. It is shown that in the quasi-stationary scenario the UAV should be placed at its minimum altitude while in the mobile scenario the UAV should adjust its altitude along with horizontal trajectory, so as to maximize the SR’s achievable rate in both scenarios. [ABSTRACT FROM AUTHOR]

Virtual reality (VR) over wireless is emerging as an important use case of 5G networks. Fully-immersive VR experience requires the wireless delivery of huge data at ultra-low latency, thus leading to ultra-high transmission rate requirement for wireless communications. This challenge can be largely addressed by the recent network architecture known as mobile edge computing (MEC) network, which enables caching and computing capabilities at the edge of wireless networks. This paper presents a novel MEC-based mobile VR delivery framework that is able to cache parts of the field of views (FOVs) in advance and compute certain post-processing procedures on demand at the mobile VR device. To minimize the average required transmission rate, we formulate the joint caching and computing optimization problem to determine which FOVs to cache, whether to cache them in 2D or 3D as well as which FOVs to compute at the mobile device under cache size, average power consumption as well as latency constraints. When FOVs are homogeneous, we obtain a closed-form expression for the optimal joint policy which reveals interesting communications-caching-computing tradeoffs. When FOVs are heterogeneous, we obtain a local optima of the problem by transforming it into a linearly constrained indefinite quadratic problem and then applying concave convex procedure. Numerical results demonstrate the proposed mobile VR delivery framework can significantly reduce communication bandwidth while meeting low latency requirement. [ABSTRACT FROM AUTHOR]

Visible light communication (VLC) and non-orthogonal multiple access (NOMA) are deemed two promising technologies in the next generation wireless communication systems in achieving high capacity and massive connectivity. In this paper we study the performance of a NOMA-enabled VLC system using different modulation schemes. In particular system level bit error rate (BER) is derived for different modulation schemes. Conventional methods used for analyzing the BER under orthogonal multiple access cannot be directly applied to NOMA. In order to obtain the closed-form BER expressions for the NOMA-enabled VLC systems, an analytical framework based on bitwise-decision axis and signal space is proposed.Moreover, the analysis method can be extended to the any wireless communication networks with NOMA. Simulation results demonstrate the accuracy of the theoretical analysis. The study shows that the BER gap among users decreases with the increase of the modulation order but at the cost of a higher power consumption in order to achieve a better signal to noise ratio. It is observed that 8-PSK modulation in NOMA-enabled VLC systems strikes a good tradeoff between the power cost and the achievable BER. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed energy-harvesting random access protocol called harvest-or-access by applying slotted ALOHA to wireless powered communication networks (WPCNs). From the fact that there are a considerable number of idle slots during which any nodes do not attempt transmission in slotted ALOHA, the idle slots are made available for wireless energy transfer (WET). If any random access (RA) slot is recognized as an idle slot, the hybrid access point (HAP) opportunistically performs the WET in this slot. The wireless devices (WDs) can harvest energy for every idle slot and attempt random access by using this harvested energy. An asymptotic throughput analysis in a high signal-to-noise ratio (SNR) environment with a sufficient number of accessing WDs shows that there is an optimal number of RA slots allocated to maximize throughput and this optimal number of RA slots depends only on the average of the minimum SNRs of the WDs without knowledge of full channel state information. Monte Carlo simulation results further show that the proposed harvest-or-access protocol outperforms the conventional harvest-then-transmit-based random access protocols especially when the number of WDs is large. [ABSTRACT FROM AUTHOR]

This paper studies the threat that an aerial eavesdropper can pose to terrestrial wireless communications, from an information-theoretic point of view. The achievable ergodic and the average $\epsilon $ -outage secrecy rates with no channel state information at the transmitter (i.e., with no CSIT) are analyzed for a transmitter–receiver pair on the ground, in the presence of an aerial eavesdropper which flies a random trajectory following a smooth turn (ST) mobility model in a three-dimensional (3D) space. The ST mobility model induces a uniform distribution (of the eavesdropper’s waypoints) within the considered 3D volume. Closed-form asymptotic approximations of the achievable secrecy rates are derived based on the almost sure convergence and non-trivial mathematical manipulations. Validated by simulations, our analysis is tight and reveals that the ground transmission is particularly vulnerable to aerial eavesdropping which can be carried out in a distance without being noticed. 3D spherical regions are identified, within which the secrecy rates vanish. This sheds useful insights to protect terrestrial wireless networks from aerial eavesdropping. [ABSTRACT FROM AUTHOR]

In this paper, we focus on one of the key technologies for the fifth-generation wireless communication networks, massive multiple-input-multiple-output (mMIMO), by investigating two of its most relevant architectures: 1) to provide in-band backhaul for the ultra-dense network (UDN) of self-backhauled small cells (SCs), and 2) to provide direct access (DA) to user equipments (UEs). Through comprehensive 3GPP-based system-level simulations and analytical formulations, we show the end-to-end UE rates achievable with these two architectures. Differently from the existing works, we provide results for two strategies of self-backhauled SC deployments, namely random and ad-hoc, where in the latter SCs are purposely positioned close to UEs to achieve line-of-sight (LoS) access links. We also evaluate the optimal backhaul and access time resource partition due to the in-band self-backhauling (s-BH) operations. Our results show that the ad-hoc deployment of self-backhauled SCs closer to the UEs with optimal resource partition and with directive antenna patterns, provides rate improvements for cell-edge UEs that amount to ${30\%}$ and tenfold gain, as compared to mMIMO DA architecture with pilot reuse 3 and reuse 1, respectively. On the other hand, mMIMO s-BH underperforms mMIMO DA above the median value of the UE rates when the effect of pilot contamination is less severe, and the LoS probability of the DA links improves. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new concept of a knowledge management framework to enable a self-optimizing and self-learning for wireless system operation in real time. The framework encapsulates both environment and intelligent agent to reach optimal operation through sensing, perception, reasoning, and learning in a truly autonomous fashion. The agent derives adequate knowledge from previous actions improving the quality of future decisions. Domain experience was provided to guide the agent while exploring and exploiting the set of possible actions in the environment. Thus, it guarantees low-cost learning and achieves a near-optimal network configuration addressing the non-deterministic polynomial-time hardness problem of joint channel and location optimization in a wireless system. Extensive simulations are run to validate its fast convergence, high throughput, and resilience to dynamic interference conditions. We deploy the framework on off-the-shelf wireless devices to propose autonomous self-optimization with knowledge management. [ABSTRACT FROM AUTHOR]

Multi-channel data broadcast attracts increasingly focus in recent years. For the complex and large multimedia data like images, audios, and videos etc, multi-channel data broadcast is a promising approach to mitigate various limitations of data dissemination in mobile environment, such as narrow bandwidth, unreliable connections, and battery limitation. However, existing data broadcast schemes are inefficient for employing multiple channels. In this paper, we present five novel multimedia data broadcast schemes (SDAA, ISDAA, LDAA, AEA, and COA) specifically designed for wireless multichannel communications. The key idea behind those schemes is to utilize SVC (Scalable Video Coding) to generate data segments with different qualities and implement indexing and channel assignment to minimize the expected waiting time for clients. In terms of waiting time minimization, we prove theoretically that SDAA is a $\tfrac{4}{3}$43-approximation algorithm and ISDAA is a $\tfrac{6}{5}$65-approximation algorithm for global allocation, and AEA can achieve locally optimal solution. We show that integrating SDAA and AEA form a best schedule for practical applications. We provide numerical experiments by using a SVC dataset and a YouTube dataset to evaluate the system performance and prove the efficiency of our schemes. We also propose a multiple video broadcast framework and analyze its performance. [ABSTRACT FROM AUTHOR]

Special attention has been devoted to joint wireless communication and radar sensing systems in recent years. However, since communication and radar have conflict requirements in terms of waveforms, transceiver developments, and signal processing algorithms, realization of this system concept is still a great challenge. In this paper, we introduce an airborne multi-input multi-output (MIMO) radar, along with the modified orthogonal frequency-division multiplexing (OFDM) and space–time coding (STC) waveform schemes, for the implementation of the joint wireless communication and synthetic aperture radar (SAR) imaging. The proposed system, which simultaneously transmits multidimensional waveforms with reconfigurable channels, can acquire adequate degrees of freedom. Thereby, it becomes a feasible method to perform both data transmission and high-resolution SAR imaging at the same time without intramodal interference. Theoretical analysis is validated by laboratory and flight experiments. Through our analysis, we aim to open up a new perspective of using MIMO radar to realize joint wireless communication and SAR imaging. [ABSTRACT FROM AUTHOR]

As a bandwidth-efficient technique, bit-interleaved coded modulation with iterative demapping and decoding (BICM-ID) has attracted much research attention in the field of wireless communication. In this paper, we put forth a joint design of root-protograph (RP) low-density parity-check (LDPC) codes and BICM-ID, referred to as RP-based BICM-ID (RP-BICM-ID), over block-fading (BF) channels so as to boost the throughput under limited bandwidth. To preserve the full-diversity property of RP codes, we propose an efficient modulation strategy for the RP-BICM-ID system by taking the fading-block length into consideration. We also analyze the outage-probability limit of the RP-BICM-ID systems to establish the fundamental lower-limit on their word-error-rate (WER) performance. Moreover, we conceive a multi-level protograph extrinsic information transfer (ML-PEXIT) algorithm to derive the asymptotic WER and bit error rate (BER) of the RP-BICM-ID systems over BF channels. As a further insight, we develop a novel unequal-error-protection (UEP) bit-to-symbol (B2S) mapping scheme for the RP-BICM-ID systems, which gives rise to an additional performance improvement. Analyses and simulations show that the proposed RP-BICM-ID systems can not only realize desirable spectral efficiency, but also obtain near-outage-limit performance over BF channels. Therefore, the proposed RP-BICM-ID systems are very promising in achieving high-reliability and high-rate transmissions under slow-fading wireless-communication environments. [ABSTRACT FROM AUTHOR]

The broadcast channel with mutual secrecy requirement at the receivers (BC-MSR-R) is a basic model characterizing the physical layer security (PLS) in the down-link of the wireless communication systems, where one transmitter sends two independent messages to two receivers via a broadcast channel, and each receiver can successfully decode his/her intended message and wishes to overhear the other one’s message. This paper studies how to enhance the already existing secrecy rate region of the BC-MSR-R via receivers’ feedback. Specifically, we propose two feedback strategies for the BC-MSR-R, where one uses the feedback to generate pure secret keys protecting the transmitted messages, and the other uses the feedback to generate not only keys but also cooperative messages helping the receivers to improve their decoding performance. Different inner bounds on the secrecy capacity region of the BC-MSR-R with noiseless feedback are constructed according to different feedback strategies, and these bounds are further illustrated by a Dueck-type example. [ABSTRACT FROM AUTHOR]

This paper investigates the secrecy performance of multiple-input multiple-output systems under generalized $\alpha -\mu $ fading conditions. To this end, we focus on two distinct scenarios: 1) the transmitter has knowledge of the channel state information (CSI) of the eavesdropper channel and 2) the transmitter is not aware of the CSI of the wiretap link. By considering transmit antenna selection in the underlying system, we develop closed-form analytical expressions for the lower bound of the secrecy outage probability (SOP) and the probability of the strictly positive secrecy capacity. Furthermore, two novel approaches are proposed to derive an analytical expression of the average secrecy capacity (ASC). First, the ASC is expressed as a function of the average capacity of the desired link and an interaction term regarded as the ASC loss. Second, the ASC is expressed in terms of the average capacities of the desired and eavesdropper links, plus an interaction term that can be regarded as some sort of ASC gain due to the statistical independence between the desired and eavesdropper links. In addition, asymptotic studies of the SOP and the ASC at high signal-to-noise ratio are carried out, which precisely reveal the secrecy diversity and array gains. [ABSTRACT FROM AUTHOR]

Recently, the newly emerging wireless powered communication network (WPCN) has drawn significant interests, where the network nodes are powered by the energy harvested from the radio-frequency (RF) signal. This paper focuses on the widely studied WPCN, where one hybrid sink (H-sink) coordinates the wireless energy/information transmissions to/from a set of one-hop nodes powered by the harvested RF energy only, and aims to minimize the network-throughput constrained H-sink’s energy provision (EP). Specifically, we investigate the performance of two important MAC protocols: time-division multiple access (TDMA) and non-orthogonal multiple access (NOMA). For both the TDMA-based WPCN (T-WPCN) and NOMA-based WPCN (N-WPCN), we first formulate the EP minimization problems as the non-linear optimization problems, then transform them into convex problems, and finally propose an efficient algorithm, which jointly uses the golden-section search and bisection search methods to determine the optimal time allocation of H-sink’s energy transfer and each node’s information transmission as well as the optimal H-sink’s transmit power. Furthermore, for the scenarios where the circuit power is negligible, we first prove that the optimal H-sink’s transmit power is the maximum allowable value, then prove theoretically that the NOMA and TDMA achieve the same EP, and also present a more efficient algorithm for the EP minimization problem. Simulation results demonstrate that the TDMA outperforms NOMA when the circuit power is non-negligible because the circuit energy consumption of NOMA accounts for a large percentage of the total energy consumption. [ABSTRACT FROM AUTHOR]

In the mobile edge computing (MEC) network, the applications of devices can be offloaded to the MEC server via the wireless link and then processed through the computation resource, to satisfy the computation and latency demand. Thus, a two-stage tandem queue is formed in the MEC network, consisting of the transmission queue and computation processing queue. However, the fluctuating wireless channel environment not only leads to the stochasticity of service in the first transmission queue, but also brings random computation task arrival in the second computation processing queue, which makes it difficult to guarantee the end-to-end quality of service (QoS) requirement. In this paper, we firstly derive the effective capacity of MEC with the two-stage tandem queue. Further, we formulate the joint bandwidth and computation resource allocation problem under the statistical QoS guarantee, to maximize the total revenue of network. This problem is proven to be NP-hard by the reduction to the two-dimensional knapsack problem. Then we propose an efficient algorithm based on alternating direction method of multipliers (ADMM) to reduce the computation complexity, where the complicated problem can be decomposed and transformed into some convex subproblems. Simulation results reveal the inherent relationship between the required bandwidth and computation resource in terms of the supported arrival rate and end-to-end delay, and also demonstrate the proposed scheme can achieve better performance than other schemes. [ABSTRACT FROM AUTHOR]

Mobile cloud computing systems, or simply mobile clouds, have attracted tremendous attention because they allow mobile devices with limited computational resources to offload complex computations. However, due to the channel uncertainty and the complexity of a computation task, mobile computation offloading may suffer from poor outage performance that the offloaded task cannot be completed within the desired delay constraint. Thus, how to efficiently identify and overcome the outage bottleneck, which could be used to optimize resource allocation schemes and improve the system performance effectively is an open problem. In this paper, we shall develop a unified framework that minimizes the overall outage probability in various mobile computation offloading scenarios. More specifically, the outage bottleneck is defined and identified by adopting asymptotic analysis, without any need of the accurate outage probabilities in both transmissions and computations. To overcome the outage bottleneck, resource pairing, matching, and allocation policies are investigated. Both theoretical analysis and numerical results show that the outage bottleneck relies on not only the availability of spectrum and computation resources but also the probability distributions of computation complexities of the computation tasks. [ABSTRACT FROM AUTHOR]

One of the goals of this paper is to contribute to finding distributed power control strategies, which exploit efficiently the information available about the global channel state; it may be local or noisy. A suited way of measuring the global efficiency of a distributed power control scheme is to use the long-term utility region. First, we provide the utility region characterization for general utility functions when the channel state obeys an independent block fading law and the observation structure is memoryless. Second, the corresponding theorem is exploited to construct an iterative algorithm, which provides one-shot power control strategies. The performance of the proposed algorithm is assessed for energy-efficient and spectrally efficient communications and shown to perform much better than state-of-the-art techniques, with the additional advantage of being applicable even in the presence of arbitrary observation structures such as those corresponding to noisy channel gain estimates. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) have attracted a lot of attention due to their enormous potentiality in civil and military applications over the past years. In order to allow accurate control action of UAV, a robust and real-time state estimation technique is required. In this paper, we propose a Kalman filter based UAV state estimation technique when the communication takes place over wireless links in an Internet of Things (IoT) network. We consider that a set of sensors observes the state of the UAV and transmits the observation to a control center (central server) over a distributed wireless IoT network. To deal with the communication impairments due to wireless communication links between the UAV's sensors and the IoT system components, e.g., IoT gateways, a Bose–Chaudhuri–Hocquenghem coded communication system is presented. Based on the received signals at the IoT gateways, a global state estimation technique is proposed. Performance of the proposed communication and estimation scheme is demonstrated through numerical results for different conditions. From the comparison with a conventional estimation scheme, it is observed that the proposed scheme significantly outperforms the conventional scheme in terms of state estimation and error performance. [ABSTRACT FROM AUTHOR]

This paper proposes a selective, tracking, and power adaptive far-field wireless power transfer (WPT) system that may be integrated into passive wireless sensor networks (PWSNs). Both transmitter and receiving nodes are developed with features that allow them to cooperate. The system operates based on a backscattered pilot signal, which is used to control and focus the radiated energy. The transmitter may change between several states by turning on or off sets of antenna elements. Each of these states will transmit and consume a specific amount of power, and they will be selected based on the node’s received signal strength (RSS). The receiving nodes are low complexity and battery-less devices, which use a small portion of the rectified energy to create an RSS-dependent modulation frequency, used to drive a backscatter modulator. Based on the nonlinear response of the rectifying devices, additional hardware was integrated into the nodes to activate/wake up them from specific wireless power signals. A complete system operating at 5.8 GHz for WPT and 3.6 GHz for the pilot signal is reported. It will be shown that effective far-field WPT links can be created with reasonable simplicity. [ABSTRACT FROM AUTHOR]

Full-duplex (FD) jamming transceivers recently have been shown to enhance the information security of wireless communication systems by simultaneously transmitting artificial noise (AN) while receiving information. In this paper, we investigate whether FD jamming can also improve the system’s secrecy energy efficiency (SEE) in terms of securely communicated bits per Joule when considering the additional power used for jamming and self-interference (SI) cancellation. Moreover, the degrading effect of the residual SI is also taken into account. In this regard, we formulate a set of SEE maximization problems for a FD multiple-input-multiple-output multiple-antenna eavesdropper (MIMOME) wiretap channel, considering both cases where exact or statistical channel state information (CSI) is available. Due to the intractable problem structure, we propose iterative solutions in each case with a proven convergence to a stationary point. Numerical simulations indicate only a marginal SEE gain, through the utilization of FD jamming, for a wide range of system conditions. However, when SI can efficiently be mitigated, the observed gain is considerable for scenarios with a small distance between the FD node and the eavesdropper, a high signal-to-noise ratio (SNR), or for a bidirectional FD communication setup. [ABSTRACT FROM AUTHOR]

In this paper, imperfect feedback-based linear precoding schemes are proposed for multiple-input-multiple-output (MIMO) wireless communication systems, where input symbol streams are encoded by using generalized-orthogonal space-time block codes. The imperfect feedback information drastically degrades the system performance. Therefore, to overcome the effect of erroneous feedback information, error-tolerant weighting (ETW) schemes are implemented by employing diagonal precoder. The communication links are assumed to be Nakagami- $m$ distributed for accurately characterizing practical wireless channels under different fading scenarios. Exact and asymptotic symbol-error-rate (SER) expressions of the considered MIMO system are derived under imperfect feedback with the help of order statistics. The most appropriate values of the transmit weights of the precoder matrix are obtained by minimizing the derived average SER over fixed and adaptive signal-to-noise ratio. Further, we study the trade-off between the proposed optimal and suboptimal feedback-based precoding schemes. Moreover, the ergodic-rate of the ETW schemes is also derived with imperfect feedback for arbitrary MIMO system by using the moment generating function approach. The simulated and analytical results show that a significant performance gain is achieved by the ETW schemes as compared to the uniform power allocation and existing precoding techniques under erroneous feedback information. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the problem of power control for streaming variable bit rate (VBR) videos over wireless links. A system model involving a transmitter (e.g., a base station) that sends VBR video data to a receiver (e.g., a mobile user) equipped with a playout buffer is adopted, as used in dynamic adaptive streaming video applications. In this setting, we analyze power control policies considering the following two objectives: 1) the minimization of the transmit power consumption and 2) the minimization of the transmission completion time of the communication session. In order to play the video without interruptions, the power control policy should also satisfy the requirement in which the VBR video data is delivered to the mobile user without causing playout buffer underflow or overflows. A directional water-filling algorithm, which provides a simple and concise interpretation of the necessary optimality conditions, is identified as the optimal offline policy. Following this, two online policies are proposed for power control based on channel side information (CSI) prediction within a short time window. Dynamic programming is employed to implement the optimal offline and the initial online power control policies that minimize the transmit power consumption in the communication session. Subsequently, reinforcement learning (RL)-based approach is employed for the second online power control policy. Through the simulation results, we show that the optimal offline power control policy that minimizes the overall power consumption leads to substantial energy savings compared with the strategy of minimizing the time duration of video streaming. We also demonstrate that the RL algorithm performs better than the dynamic programming-based online grouped water-filling (GWF) strategy unless the channel is highly correlated. [ABSTRACT FROM AUTHOR]

Large intelligent surface (LIS)-assisted wireless communications have drawn attention worldwide. With the use of low-cost LIS on building walls, signals can be reflected by the LIS and sent out along desired directions by controlling its phases, thereby providing supplementary links for wireless communication systems. In this paper, we evaluate the performance of an LIS-assisted large-scale antenna system by formulating a tight upper bound of the ergodic spectral efficiency and investigate the effect of the phase shifts on the ergodic spectral efficiency in different propagation scenarios. In particular, we propose an optimal phase shift design based on the upper bound of the ergodic spectral efficiency and statistical channel state information. Furthermore, we derive the requirement on the quantization bits of the LIS to promise an acceptable spectral efficiency degradation. Numerical results show that using the proposed phase shift design can achieve the maximum ergodic spectral efficiency, and a 2-bit quantizer is sufficient to ensure spectral efficiency degradation of no more than 1 bit/s/Hz. [ABSTRACT FROM AUTHOR]

Caching is a promising approach to address the backhaul traffic congestion problem and boost throughput in fog radio access networks. In this correspondence paper, we investigate a proactive probabilistic caching optimization in wireless fog radio access network where multiple users request different files from multiple base stations (BSs). To assess the performance, we first derive the analytical results of successful transmission probability (STP) using tools of stochastic geometry. With the derived closed-form STP expressions, our objective is to optimize the proactive probabilistic caching distribution to maximize the STP. To reduce the computational complexity, we specially discuss the optimization in high signal-to-noise ratio (SNR). We propose a projection gradient method to get a local optimal solution. Simulation results show that the caching placement optimized by our proposed algorithm increases the STP by about $18\%$ over the best existing caching distribution when ${\rm SNR}=10$ dB with user density $\lambda _u=0.09$ , BS density $\lambda _b=0.1$ and file number $N=100$. [ABSTRACT FROM AUTHOR]

In this paper, we analyze energy-efficient communications based on an advanced energy consumption model for wireless devices. The developed model captures relationships between transmission power, transceiver distance, modulation order, channel fading, power amplifier (PA) effects, as well as other circuit components in the radio frequency transceiver. Based the developed model, we are able to identify the optimal modulation order in terms of energy-efficiency under different situations (e.g., different transceiver distance, different PA classes and efficiencies, different pulse shape, etc). This provides an important framework for analyzing energy-efficient communications for different wireless systems ranging from cellular networks to wireless Internet of Things. [ABSTRACT FROM AUTHOR]

We present the Bio-Matched Horn antenna: a novel 1.773 cm3 on-body antenna for very low-loss communication with wireless implants across the 1–9 GHz bandwidth. To achieve this unique performance, the Bio-Matched Horn is composed of water-filled holes used to mimic the frequency-dependent permittivity of the underlying tissue over its entire bandwidth. The horn shape further allows the proposed antenna to communicate efficiently through the biological tissue for both subcutaneous and deep-tissue wireless implants. Measurement results at 2.4 GHz are in good agreement with simulations and show a transmission loss of 8.01 dB to a 4 mm-deep implant and 19.21 dB to a 2 cm-deep implant. Compared to the previous designs, this is a remarkable improvement by 14.5 and 10.8 dB for subcutaneous and deep-tissue communication, respectively. In this paper, we discuss the operation principle and design of the Bio-Matched Horn, its performance for subcutaneous and deep-tissue implant telemetry, sensitivity to rotational and positional misalignments, and specific absorption rate performance. [ABSTRACT FROM AUTHOR]

Multi-group multicast beamforming in wireless systems with large antenna arrays and massive audience is investigated in this paper. Multicast beamforming design is a well-known non-convex quadratically constrained quadratic programming (QCQP) problem. A conventional method to tackle this problem is to approximate it as a semi-definite programming problem via semi-definite relaxation, whose performance, however, deteriorates considerably as the number of per-group users goes large. A recent attempt is to apply convex-concave procedure (CCP) to find a stationary solution by treating it as a difference of convex programming problem, whose complexity, however, increases dramatically as the problem size increases. In this paper, we propose a low-complexity high-performance algorithm for multi-group multicast beamforming design in large-scale wireless systems by leveraging the alternating direction method of multipliers (ADMM) together with CCP. In specific, the original non-convex QCQP problem is first approximated as a sequence of convex subproblems via CCP. Each convex subproblem is then reformulated as a novel ADMM form. Our ADMM reformulation enables that each updating step is performed by solving multiple small-size subproblems with closed-form solutions in parallel. Numerical results show that our fast algorithm maintains the same favorable performance as state-of-the-art algorithms but reduces the complexity by orders of magnitude. [ABSTRACT FROM PUBLISHER]

In this paper, the finite-time filtering problem is investigated for a class of wireless networked multirate systems (NMSs) with fading channels. The system measurements are transmitted through fading channels described by a modified stochastic Rice fading model, and the event-based wireless relay communication scheme is proposed to determine whether the received fading measurements in the relay nodes should be transmitted to the filter. With the aid of the stochastic analysis approach, sufficient conditions are established under which the stochastic finite-time boundedness (FTB) of the estimation error dynamics is guaranteed and the prescribed finite-time H\infty performance constraint is achieved. Based on the derived conditions, the addressed finite-time filtering problem of NMSs is recast as a convex optimization one that can be solved via the semidefinite program method. Furthermore, the explicit expression of the desired filter is obtained by means of the feasibility of certain matrix inequalities. Two additional optimization problems are considered with respect to the FTB parameter and the finite-time H\infty performance index. Finally, a numerical simulation example on a continuous stirred tank reactor is employed to show the effectiveness of the filtering scheme proposed in this paper. [ABSTRACT FROM PUBLISHER]

This paper considers both nondistributed and distributed multilevel amplify-and-forward (AF) wireless relay networks. For a fair comparison, the nondistributed multilevel AF relay network consists of a one-source–one-destination pair and a relay at each level with multiple antennas, whereas the distributed network consists of a one-source–one-destination pair and multiple distributed relays at each level with a single antenna at each relay. In this paper, relay beamforming matrices are determined for both networks based on the minimum mean square error (MMSE) criterion. During data transmission, power is independently and individually constrained at the relays at each level. Finally, an iterative algorithm is proposed to solve the desired optimization problem. [ABSTRACT FROM PUBLISHER]

Building on the recent coded-caching breakthrough by Maddah-Ali and Niesen, the work here considers the $K$ -user cache-aided wireless multi-antenna symmetric broadcast channel with random fading and imperfect feedback, and analyzes the throughput performance as a function of feedback statistics and cache size. In this setting, this paper identifies the optimal cache-aided degrees-of-freedom (DoF) within a factor of 4, by identifying near-optimal schemes that exploit a new synergy between coded caching and delayed CSIT, as well as by exploiting the unexplored interplay between caching and feedback-quality. The DoF expressions reveal an initial gain due to current CSIT, and an additional gain due to coded caching, which is exponential in the sense that any linear decrease in the required DoF performance, allows for an exponential reduction in the required cache size. In the end, this paper reveals three new aspects of caching: a synergy between memory and delayed feedback, a tradeoff between memory and current CSIT, and a powerful ability to provide cache-aided feedback savings. [ABSTRACT FROM PUBLISHER]

The rapid proliferation of wireless devices offers new means to infer current conditions surrounding mobile users, their locations, and their actions. This is especially true for industrial, scientific, and medical (ISM) radio bands where communication protocols are often open and information about neighboring devices abounds. This paper examines efficient occupancy estimation based on Wi-Fi metadata, with an emphasis on algorithms attuned to directional antenna technology. Certain Wi-Fi interfaces can be switched into monitoring mode, an operating state where all local packets are observed and recorded. Using a network of such monitoring sensors, it is then possible to estimate the number of active devices within a specific area. The envisioned estimators take as input received signal strength indicators and media access control addresses. By using directional monitoring antennas, one can gain additional and/or more discriminating information about current conditions, thereby yielding enhanced occupancy estimates. This paper introduces novel estimation algorithms and characterizes the performance gains associated with RF-aware sensing devices. Experimental results based on a prototype implementation of this distributed monitoring system provide further supporting evidence for the proposed techniques. [ABSTRACT FROM PUBLISHER]

The Gamma–Gamma distribution has recently emerged in a number of applications ranging from modeling scattering and reverberation in sonar and radar systems to modeling atmospheric turbulence in wireless optical channels. In this respect, assessing the outage probability achieved by some diversity techniques over this kind of channels is of major practical importance. In many circumstances, this is related to the difficult question of analyzing the statistics of a sum of Gamma–Gamma random variables. Answering this question is not a simple matter. This is essentially because outage probabilities encountered in practice are often very small, and hence, the use of classical Monte Carlo methods is not a reasonable choice. This lies behind the main motivation of this paper. In particular, this paper proposes a new approach to estimate the left tail of the sum of Gamma–Gamma variates. More specifically, we propose robust importance sampling schemes that efficiently evaluates the outage probability of diversity receivers over Gamma–Gamma fading channels. The proposed estimators satisfy the well-known bounded relative error criterion for both maximum ratio combining and equal gain combining cases. We show the accuracy and the efficiency of our approach compared with naive Monte Carlo via some selected numerical simulations. [ABSTRACT FROM PUBLISHER]

The severe bandwidth shortage in conventional microwave bands has spurred the exploration of the millimeter wave (MMW) spectrum for the next revolution in wireless communications. However, there is still a lack of proper channel modeling for the MMW wireless propagation, particularly in the case of outdoor environments. In this paper, we develop a geometry-based stochastic channel model to statistically characterize the effect of all the first-order reflection paths between the transmitter and the receiver. These first-order reflections are generated by the single bounce of signals reflected from the walls of randomly distributed buildings. Based on this geometric model, a closed-form expression for the power delay profile contributed by all the first-order reflection paths is obtained and then used to evaluate their impact on the MMW outdoor propagation characteristics. Numerical results are provided to validate the accuracy of the proposed model under various channel parameter settings. The findings in this paper provide a promising step toward more complex and practical MMW propagation channel modeling. [ABSTRACT FROM PUBLISHER]

Multi-channel (MC) optical wireless communication (OWC) systems employing wave-division multiplexing for outdoors free-space optical communications, or multi-user time-division multiple access for indoors visible-light communications, e.g., can be modeled as parallel channels. Multi-input multi-output OWC systems can also be transformed, possibly with some performance loss, to parallel channels using pre-/post-coding. Studying the performance of such MC-OWC systems requires characterizing the capacity of the underlying parallel channels. In this paper, upper and lower bounds on the capacity of constant parallel OWC channels with a total average intensity constraint are derived. Then, this paper focuses on finding intensity allocations that maximize the lower bounds given channel-state information at the transmitter (CSIT). Due to its nonconvexity, the Karush–Kuhn–Tucker conditions are used to describe a list of candidate allocations. Instead searching exhaustively for the best solution, low-complexity near-optimal algorithms are proposed. The resulting optimized lower bound nearly coincides with capacity at high signal-to-noise ratio (SNR). Under a quasi-static channel model and in the absence of CSIT, outage probability upper and lower bounds are derived. Those bounds also meet at high SNR, thus characterizing the outage capacity in this regime. Finally, the results are extended to a system with both average and peak intensity constraints. [ABSTRACT FROM PUBLISHER]

The emergence of interference alignment (IA) as a degrees-of-freedom optimal strategy motivates the need to investigate whether IA can be leveraged to aid conventional network utility maximization algorithms, which are typically only capable of finding locally optimal solutions. To test the usefulness of IA in this context, this paper proposes a two-stage optimization framework for the downlink of a $G$ -cell multi-antenna network with $K$ users/cell. The first stage of the proposed framework focuses on nulling interference from a set of dominant interferers using IA, while the second stage optimizes transmit and receive beamformers to maximize a network-wide utility using the IA solution as the initial condition. Further, this paper establishes a set of new feasibility results for partial IA that can be used to guide the number of dominant interferers to be nulled in the first stage. Through simulations on specific topologies of a cluster of base stations, it is observed that the impact of IA depends on the choice of the utility function and the presence of out-of-cluster interference. In the absence of out-of-cluster interference, the proposed framework outperforms straightforward optimization when maximizing the minimum rate, while providing marginal gains when maximizing sum rate. However, the benefit of IA is greatly diminished in the presence of significant out-of-cluster interference. [ABSTRACT FROM AUTHOR]