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Deployment of unmanned aerial vehicles (UAVs) as flying base stations to provide specific geographical area with air-to-ground wireless communications is expected to increase dramatically in the coming decades, owing to its flexibility, mobility and autonomy. Moreover, mobile edge computing (MEC) promises significant reduction in latency by caching popular contents at the mobile edge. In this paper, we propose a method to apply mobile edge caching on UAVs in wireless communication systems. By investigating the user request preference with the aid of latent Dirichlet allocation (LDA), the caching strategy can be optimized. In the proposed system, we consider the design of intelligent caching strategies when a number of UAVs are deployed to serve ground users, where each UAV has a limited storage capacity for caching useful user contents. We use LDA to extract the user request preferences in order to intelligently cache data in the UAVs, while we use K-means clustering to associate users with the UAVs. We consider three caching criteria, namely the user received signal to noise ratio (SNR), user preferences and the delay. Our simulation results show that, when compared to random caching, the average caching efficiency could be significantly improved from $50 \%$ to $70 \%$ , while the latency of our proposed system can also be greatly reduced.

As a key technique of supporting the fixed backbone network, radio over fiber (RoF) systems transmit the radio frequency signals over optical fiber in order to take advantage of their large available bandwidth. In this context, optical fiber aided phased antenna array (PAA) based beamforming techniques have attracted substantial research interest with the goal of improving the cell-edge coverage of cellular base stations. In this paper, we conceive a novel optical fiber aided beamforming technique based on the fiber's nonlinearity to be applied in cloud radio access network (C-RAN). In our proposed technique, the PAA elements are fed by the phase-shifted signals introduced by our highly nonlinear fiber (HNLF) aided phase-shifting solution, which results in an angular beamsteering range of around 90 $^{\circ }$ . This can be exploited by sectorization in cellular networks to reduce the cochannel interference imposed. Furthermore, we exploit the proposed RoF-aided phase shifting technique in C-RAN, where our proposed system takes advantage of the centralized signal processing capability of the RoF system to conceive an all-optical processing based tunable beamforming system. While our flexible HNLF-aided phase-shifting process is confined to the central office of the C-RAN, the end users in the C-RAN cellular networks are capable of flexibly choosing the serving remote radio heads and employing diverse wireless transmission techniques. Through integrating our HNLF-aided phase-shifting design into the proposed C-RAN, we impose as little as 0.1 dB signal-to-noise ratio degradation compared to its traditional electronic counterpart, which requires extra phase-shifters.

A new constellation is designed for the multiuser noncoherent large-scale single-input multiple-output uplink system based on M-ary differential phase-shift keying, which is combined with a bit interleaved coded modulation-iterative decoding scheme for attaining improved performance. We conceive a new approach for constructing EXIT charts parameterized by the number of antennas used for optimizing the design. Finally, the system performance is analyzed and compared to previous work. This evaluation shows an overall improvement of two orders of magnitude demonstrating a dramatic reduction in the required number of antennas.

The recently proposed concept of multiset space-time shift keying (MS-STSK) is intrinsically amalgamated with the multiple-input multiple-output (MIMO) philosophy for the sake of enhancing the attainable system throughput. Explicitly, we propose a multiuser steered MS-STSK (MU-SMS-STSK) scheme for the downlink of millimeter-wave (mmWave) communications, which is combined with analogue beamforming (BF) that relies on phase shifters and power amplifiers to overcome the high attenuation of mmWaves. Hence, our MU-SMS-STSK system combines the concepts of MU-MIMO, MS-STSK, BF, and orthogonal frequency-division multiplexing for communicating with multiple users relying on the same time and frequency resources.

Unmanned Aerial Vehicles (UAV) are more suitable for surveillance systems than their traditional stationary counterparts. To meet the associated demanding video compression requirements, the H.265/High Efficiency Video Coding (HEVC) codec is invoked. Its scalable video coding extension is capable of supporting diverse video resolutions by encoding the video clips captured into multiple layers, namely the Base Layer (BL) and several Enhancement Layers (EL). In this treatise, we propose a multi-functional Multiple-Input Multiple-Output (MIMO) transceiver relying on Multi-Set Space-Time Shift Keying (MS-STSK) for UAV-aided near-instantaneously adaptive layered video streaming, which is capable of promptly varying the throughput as a function of both the estimated channel quality as well as of the UAV mobility, while maintaining near-flawless video quality. Additionally, we invoke EXtrinsic Information Transfer (EXIT) charts for characterizing our Unequal Error Protection (UEP) based video transceiver with the aid of near-capacity channel coding. Some of the perceptually less important ELs may have to be dropped during instances of low channel quality to retain the robustness of the transmitted video stream when a low-throughput MIMO configuration is activated. The simulation results show that our proposed UEP assisted adaptive system is capable of attaining the best Y-Peak SNR (PSNR) performance in comparison to both its non-adaptive and Equal Error Protection (EEP) counterparts.

The demanding bitrate requirements of supporting flawless streaming of immersive video remains a challenge. To minimize the bandwidth without degrading the user’s experience, we may opt for partitioning the panoramic video frame into numerous tiles and only transmit those covered by the predicted Field of View (FoV), but naturally, this philosophy critically hinges on the accuracy of the Head Movement Prediction (HMP). However, since the HMP is never 100% accurate, rebuffering of the missing portions due to misprediction is likely to introduce video freezes or artefacts, which may significantly degrade the users’ experience. Hence, instead of only transmitting the FoV tiles, Scalable Video Coding (SVC) comes to rescue. Explicitly, in SVC schemes, multiple layers having different importance provide a promising solution, where the basic quality of the entire panoramic video is supported by the Base Layer (BL) that only requires a low bitrate, while the Enhancement Layers (EL) are invoked for enhancing the quality of the predicted FoV. Inthis treatise, we propose coding rate adaptation assisted near instantaneously Adaptive Quadrature Amplitude Modulation (AQAM) for layered panoramic video streaming. In our design, we categorize the video streaming into three priority classes according to the FoV and the SVC layer index, each of which ismapped to the most appropriate modulation mode determined by the instantaneous channel quality. Furthermore, we conceive an Evolutionary Algorithm (EA) assisted Forward Error Correction (FEC) coding rate optimization method for providing Unequal Error Protection (UEP) in order to maximize the uncoded source rate according to the inter-frame and inter-layer decoding dependency for tile-based panoramic video streaming. The simulation results show that the proposed AQAM assisted UEP scheme configured by our EA assisted coding rate optimization algorithm significantly improves the overall video performance compared to its Equal Error Protection (EEP) counterpart, and provides perceptually pleasing video quality across a wide range of channelconditions by selecting the most appropriate modulation mode based on the instantaneous channel Signal-to-Noise Ratio (SNR).

Interlayer forward error correction (IL-FEC) coding constitutes an effective unequal error protection (UEP) scheme conceived for transmitting layered video over wireless channels. In contrast to traditional UEP schemes, it operates by embedding extra information concerning the base layer (BL) into the enhancement layers (ELs) without requiring extra transmission resources. The received EL packets assist in the decoding of the BL to reduce the distortion of the reconstructed video. The optimum scheduling of the IL-FEC coded layered video streaming in a truncated hybrid automatic repeat request (THARQ)-aided system is an open problem. Hence, in this paper, we conceive an adaptive THARQ (ATHARQ) algorithm for finding the most appropriate scheduling of the IL-FEC coded layered video packets for the sake of minimizing the video distortion under the constraint of a given total number of transmission time slots (TSs). Furthermore, we develop a method of online coding-rate optimization algorithm for our IL-ATHARQ transmission scheme to find the best FEC code rate distribution among the video layers that results in the lowest possible video distortion. When using a recursive systematic convolutional (RSC) code, our simulation results show that the proposed rate-optimized (RO) IL-ATHARQ system outperforms the traditional THARQ transmission scheme by about 5.3 dB of $E_{b}/N_{0}$ at a peak signal-to-noise ratio (PSNR) of 38.5 dB. Viewing the improvements in terms of the video quality, 2.5 dB of PSNR improvement is attained at an $E_{b}/N_{0}$ of 15 dB.

In wireless sensor networks (WSNs), the network lifetime (NL) is a crucial metric since the sensor nodes usually rely on limited energy supply. In this paper, we consider the joint optimal design of the physical, medium access control (MAC), and network layers to maximize the NL of the energy-constrained WSN. The problem of NL maximization can be formulated as a nonlinear optimization problem encompassing the routing flow, link scheduling, transmission rate, and power allocation operations for all active time slots (TSs). The resultant nonconvex rate constraint is relaxed by employing an approximation of the signal-to-interference-plus-noise ratio (SINR), which transforms the problem to a convex one. Hence, the resultant dual problem may be solved to obtain the optimal solution to the relaxed problem with a zero duality gap. Therefore, the problem is formulated in its Lagrangian form, and the Karush–Kuhn–Tucker (KKT) optimality conditions are employed for deriving analytical expressions of the globally optimal transmission rate and power allocation variables for the network topology considered. The nonlinear Gauss–Seidel algorithm is adopted for iteratively updating the rate and power allocation variables using these expressions until convergence is attained. Furthermore, the gradient method is applied for updating the dual variables in each iteration. Using this approach, the maximum NL, the energy dissipation per node, the average transmission power per link, and the lifetime of all nodes in the network are evaluated for a given source rate and fixed link schedule under different channel conditions.

We present a novel trifunctional multiple-input-multiple-output (MIMO) scheme that intrinsically amalgamates space-time spreading (STS) to achieve a diversity gain and a Vertical Bell Labs layered space-time (V-BLAST) scheme to attain a multiplexing gain in the context of generalized multicarrier direct-sequence code-division multiple access (MC DS-CDMA), as well as beamforming. Furthermore, the proposed system employs both time- and frequency-domain spreading to increase the number of users, which is also combined with a user-grouping technique to reduce the effects of multiuser interference. Further system performance improvements can be attained by serially concatenating our proposed scheme with an outer code that is amalgamated with a unity-rate code for the sake of improving the achievable decoding convergence behavior of the proposed system, which is evaluated with the aid of extrinsic information transfer charts. We also propose a novel logarithmic likelihood ratio (LLR) postprocessing technique to improve the iteratively detected system's performance. Explicitly, the proposed system can attain a second-order spatial diversity gain and a frequency diversity gain of order V, where V is the number of subcarriers. Additionally, the proposed system attains a beamforming gain and a multiplexing gain that is twice that of a single-input-single-output system. Furthermore, after I = 10 decoding iterations and employing an interleaver depth of Dint = 160 000 bits, a time-domain spreading factor of Ne = 4, and V = 4 subcarriers, the overloaded system supporting K = 8 users requires an Eb/N0 that is only about 0.45 dB higher than the single-user system.

In this paper, we present a novel system that invokes jointly optimized iterative source and channel decoding for enhancing the error resilience of the adaptive multirate wideband (AMR-WB) speech codec. The resultant AMR-WB-coded speech signal is protected by a recursive systematic convolutional (RSC) code and transmitted using a noncoherently detected multiple-input-multiple-output (MIMO) differential space-time spreading (DSTS) scheme. To further enhance the attainable system performance and to maximize the coding advantage of the proposed transmission scheme, the system is also combined with multidimensional sphere-packing (SP) modulation. Furthermore, the convergence behavior of the proposed scheme is evaluated with the aid of extrinsic information transfer (EXIT) charts. The proposed system exhibits an Eb/N 0 gain of about 1 dB, as compared with the benchmark scheme carrying out joint channel decoding and DSTS-aided SP demodulation in conjunction with separate AMR-WB decoding, when using only I system = 2 system iterations and when communicating over narrow-band correlated Rayleigh fading channels.

Harnessing the abundant availability of spectral resources at millimeter wave (mmWave) frequencies is an attractive solution to meet the escalating data rate demands. Additionally,it has been shown that full-duplex (FD) communication has the potential of doubling the bandwidth efficiency. However, the presence of significant residual self-interference (SI), which is especially more pronounced at mmWave frequencies because of the non-linearities in the hardware components, erodes the full potential of FD in practice. Conventionally, the residual SI is canceled in the baseband using digital processing with the aid of a transmit precoder. In this work, we propose a hybrid beamforming design for FD mmWave communications, where the SI is canceled by the joint design of beamformer weights at the radio-frequency (RF) and the precoder as well as combiner in the baseband. Our proposed design preserves the dimensions of the transmit signal, while suppressing the SI. We demonstrate that our joint design is capable of reducing the SI by upto 30 dB, hence performing similarly to the interference-free FD system while being computationally efficient. Our simulation results show that the proposed design significantly outperforms eigen-beamforming.