Search

Due to their flexibility, mobility and autonomy, unmanned aerial vehicles (UAVs) are considered as a potential candidate to operate as flying base stations to provide a specific geographical area with air-to-ground wireless communications services. Besides, the limitation of the on-board energy motivates the design of a more energy-efficient way to transmit information. Moreover, the deployment of multiple UAVs can affect the quality of experience (QoE) of users. In this paper, we propose a method that combines the concept of index modulation (IM) with the UAV communications systems, which we refer to as IM-UAV, to attain an improved energy-efficiency (EE). Furthermore, based on the proposed IM-UAV communication system, a gradient descent based UAV deployment scheme is designed to maximize the downlink average rate of the ground users (GUs) in the target area. On the other hand, the maximum likelihood (ML) detection for the IM-UAV requires a high computational complexity for detection at the GUs, while providing the best possible performance. Hence, we propose a low-complexity detection scheme that can separately detect the index symbols and data symbols to reduce the computational complexity at the receiver side. The simulation results demonstrate that the proposed deployment method is capable of attaining the appropriate positions to deploy the UAVs, while the EE is also improved by combining IM with UAV communication system. In addition, the proposed lowcomplexity detection scheme reduces the computation complexityby slightly sacrificing the bit error rate (BER) performance.

To alleviate the explosive growth of data trafficcaused by the increased use of smart devices, new transmissiontechniques are needed to increase the utilization of limitedbandwidth resources and for providing high transmission ratesin future wireless networks. On the other hand, due to theirflexibility and autonomy, unmanned aerial vehicles (UAVs) areconsidered as a potential candidate to support ubiquitous connectivity and operate as flying base stations, where the deploymentof UAVs can affect the quality of experience (QoE) of users.Hence, in this paper, we employ UAVs as aerial base stationsto transmit data to ground users (GUs) via air to ground (A2G)communication links, where we show how content awareness canhelp improve the data rate. Specifically, we design two contentsharing(CS) data transmission schemes to improve the averagedata rate of the GUs. Additionally, two UAV deployment strategies,namely the fixed-point deployment scheme and traversesearchdeployment scheme, are proposed based on the proposedCS transmission schemes. The simulation results demonstratethat our proposed data transmission schemes combined withtheir proposed deployment schemes outperform the traditionaltransmission scheme by 26 bits/s/Hz and 51 bits/s/Hz, respectively.

The concept of the “connected car” offers the potential for safer, more enjoyable and more efficient driving and eventually autonomous driving. However, in urban Vehicular Networks (VNs) , the high mobility of vehicles along roads poses major challenges to the routing protocols needed for a reliable and flexible vehicular communications system. Thus, urban VNs rely on static Road-Side-Units (RSUs) to forward data and to extend coverage across the network. In this paper, we first propose a new Q-learning-based routing algorithm, namely Infrastructure-aided Traffic-Aware Routing (I-TAR), which leverages the static wired RSU infrastructure for packet forwarding. Then, we focus on the multi-source, multi-destination problem and the effect this imposes on node availability, as nodes also participate in other communications paths. This motivates our new hybrid approach, namely Hybrid Infrastructure-aided Traffic Aware Routing (HITAR)that aims to select the best Vehicle-to-Vehicle/Infrastructure (V2V/I) route. Our findings demonstrate that I-TAR can achieve up to 19% higher average packet-delivery-ratio (APDR) compared to the state-of-the-art. Under a more realistic scenario, where node availability is considered, a decline of up to 51% in APDR performance is observed, whereas the proposed HI-TAR in turn can increase the APDR performance by up to 50% compared to both I-TAR and the state-of-the-art. Finally, when multiple source destination vehicle pairs are considered, all the schemes that model and consider node availability, i.e. limited-availability, achieve from 72.2% to 82.3% lower APDR, when compared to those that do not, i.e. assuming full-availability. However, HI-TAR still provides 34.6% better APDR performance than I-TAR, and ∼40% more than the state-of-the-art.

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.

The concept of Index Modulation ({IM}) has been actively researched as a benefit of its flexible trade-off between performance, achievable rate, energy efficiency, hardware cost and complexity. In order to fully exploit its the degrees of freedom, the concept of Multi-dimensional IM ({MIM}) has been developed in literature, where Compressed Sensing ({CS}) is often utilized to exploit the sparsity of the multi-dimensional transmitted signals. However, this flexibility and performance gains are attained at the cost of a substantially increased detection complexity. In this paper, we propose Deep Learning ({DL}) based detection for {CS}-aided {MIM} ({CS-MIM}), where both Hard-Decision ({HD}) as well as Soft-Decision ({SD}) detection combined with iterative decoding are conceived.More explicitly, firstly, we propose learning aided hard and soft detection for CS-MIM. Secondly, two novel neural network aided methods are proposed for Iterative Soft Detection ({ISD}), where iterations are carried out between the {CS-MIM} detector and a channel decoder. In contrast to the conventional detection of {CS-MIM} system, which critically relies on the knowledge of Channel State Information ({CSI}) at the receiver, the proposed learning-aided methods are capable of eliminating the overhead and complexity of Channel Estimation ({CE}), which results in an improved transmission rate. Explicitly, we develop an advanced {DL} architecture for blind-detection-aided {MIM} for the first time in the open literature, where the {HD} and {SD} {CS} algorithms are implemented by learning without the need for {CE}. Our simulation results demonstrate that the proposed learning techniques conceived for {SD} {CS-MIM} combined with iterative detection are capable of achieving near-capacity performance at a reduced complexity compared to the conventional model-based {SD} relying on {CSI} acquisition.

New reconfigurable intelligent surface (RIS) based amplitude and phase modulation schemes are proposed as an evolution how the phase-only modulation schemes available in the literature. Explicitly, both the amplitude-phase shift keying (A-PSK) and quadrature amplitude-phase shift keying (QA-PSK) are conceived, where the RIS is assumed to be part of a transmitter to deliver information to the multi-antenna aided downlink receiver. In the proposed design, the RIS is partitioned into multiple blocks, and the information bits are conveyed by controlling both the ON-OFF state and the phase shift of the RIS elements in each block. Since the propagation paths spanning from each RIS block to the receiver can be coherently combined as a benefit of appropriately configuring the phase of the RIS elements, the received signal constellations can be designed by controlling both the ON-OFF pattern of the RIS blocks as well as the phase shift of the RIS elements. Both the theoretical analysis and the simulation results show that our proposed RIS-aided modulation schemes outperform the state-of-the-art RIS-based PSK modulation both in terms of its discrete-input-continuous-output memoryless channel (DCMC) capacity and its symbol error probability, especially in the high signal-to-noise-ratio (SNR) region, when considering realistic finite resolution RIS phase shifts.

The linear minimal mean square error (LMMSE) estimator for active reconfigurable intelligent surface (RIS)-aided wireless systems is formulated. Furthermore, based on the moment-matching method, we employ the Gamma distribution to approximate the distribution of the instantaneous received signal-to-interference-plus-noise ratio (SINR), and then derive the closed-form outage probability and ergodic channel capacity in the presence of realistic channel estimation errors, the thermal noise of RIS amplifiers and the RIS phase shift noise. Our theoretical analysis and simulation results show that the introduction of RIS amplifiers is equivalent to increasing of the transmit power, and also present the performance degradation resulting from the channel estimation error and the RIS phase noise.

The efficiency of link adaptation in wireless communications relies greatly on the accuracy of channel knowledge and transmission mode selection. In this paper, a novel deep learning based link adaptation framework is proposed for the orthogonal frequency-division multiplexing (OFDM) systems with compressed-sensing-assisted index modulation, termed as OFDM-CSIM, communicating over millimeter-wave (mmWave) channels. To achieve link adaptation, a novel multi-layer sparse Bayesian learning (SBL) algorithm is proposed for accurately and instantaneously providing the required channel state information. Meanwhile, a deep neural networks (DNN)-assisted adaptive modulation algorithm is proposed to choose the best possible transmission mode to maximize the achievable throughput. Simulation results show that the proposed multi-layer SBL algorithm enables more accurate channel estimation than the conventional techniques. The DNN-based adaptive modulator is capable of achieving a higher throughput than the learning-assisted solution based on the k nearest neighbor (k-NN) algorithm, and also the classic average signal-to-noise ratio (SNR)-based solutions. Moreover, analysis shows that both the multi-layer SBL algorithm and the DNN-assisted adaptive modulator achieve better performance than their respective conventional counterparts while at a significantly lower computational complexity cost.

Reconfigurable intelligent surfaces (RIS) have been actively researched as a potential technique for future wireless communications, which intelligently ameliorate the signal propagation environment. In the conventional design, each RIS element configures and reflects its received signal independently of all other RIS elements, which results in a diagonal phase shift matrix. By contrast, we propose a novel RIS architecture, where the incident signal impinging on one element can be reflected from another element after an appropriate phase shift adjustment, which increases the flexibility in the design of RIS phase shifts, hence, potentially improving the system performance. The resultant RIS phase shift matrix also has off-diagonal elements, as opposed to the pure diagonal structure of the conventional design. Compared to the state-of-art fully-connected/group-connected RIS structures, our proposed RIS architecture has lower complexity, while attaining a higher channel gain than the group-connected RIS structure, and approaching that of the fully-connected RIS structure. We formulate and solve the problem of maximizing the achievable rate of our proposed RIS architecture by jointly optimizing the transmit beamforming and the non-diagonal phase shift matrix based on alternating optimization and semi-define relaxation (SDR) methods. Moreover, the closed-form expressions of the channel gain, the outage probability and bit error ratio (BER) are derived. Simulation results demonstrate that our proposed RIS architecture results in an improved performance in terms of the achievable rate compared to the conventional architecture, both in single-user as well as in multi-user scenarios.

A large-scale differential-detection aided generalized spatial modulation (GSM) system is proposed, which relies on a novel Gram-Schmidt basis set and an adaptive low-complexity detector, and is evidently suitable for high-mobility millimeter-wave (mmWave) channels. We consider non-stationary time-varying mmWave channels and assume that the beam-angles remain relatively fixed, while the channel coefficients vary rapidly. In this scenario, it is a challenging task to find the accurate estimates of channel coefficients for digital beamforming, which becomes an even more severe problem, as the numbers of subarrays and subcarriers increase. Our analog-beamforming-aided nonsquare differentially-detected scheme achieves a higher transmission rate than the conventional coherent multiple-input multiple-output schemes because the pilot overhead and the complex-valued feedback are eliminated. Our simulation results following the IEEE 802.11ad specifications show that the performance of our proposed nonsquare differential GSM improved upon increasing the number of subarrays, where the maximum transmission rate of 16 [bps/Hz] was considered.

In this paper, we conceive a compressed sensing (CS)-aided multi-dimensional index modulation (IM) scheme, where the benefits of space–time shift keying, orthogonal frequency-division multiplexing relying on the frequency domain IM, and spatial modulation are explored. Explicitly, extra information bits are transmitted through the active indices of both the transmit antennas and subcarriers, while striking a flexible design tradeoff between the throughput and the diversity order. Furthermore, CS is invoked in both the transmitter and the receiver of our multi-dimensional system for the sake of improving the system’s design flexibility, while reducing the detector’s complexity. We first present the maximum likelihood (ML) detector of the proposed CS-aided multi-dimensional IM system for characterizing the best-case bound of the proposed system’s performance. Specifically, an upper bound is derived for the average bit error probability, and it is observed that the derived theoretical upper bound becomes very tight with the ML detector simulation curves as the signal-to-noise ratio increases. Then, we propose a reduced complexity detector imposing only a modest bit-error-ratio degradation, where we analyze the computational complexities of both the ML detector and the reduced complexity detector. Furthermore, a soft-input soft-output decoder is proposed for attaining a near-capacity performance, which is analyzed with the aid of extrinsic information transfer (EXIT) charts. The maximum achievable rate of the proposed CS-aided multi-dimensional IM system relying both on the ML detection and on our reduced-complexity-based detector is also evaluated using EXIT charts. In addition, the discrete-input continuous-output memoryless channel capacity of the proposed CS-aided multi-dimensional IM scheme is formulated.

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.

To mitigate the burden of the tele-traffic imposed by video streaming, Scalable Video Coding (SVC) is invoked for mapping the video clips to multiple layers, which allows us to improve the coverage quality. Although numerous non-orthogonal techniques have been conceived in the literature for maximizing the theoretical capacity relying on the idealized simplifying assumption of perfect channel coding. There is a paucity of practical finite-delay channel-coded solutions capable of mitigating the avalanche-like error proliferation routinely encountered in the face of hostile channels. Against this background, we propose SVC based Superposition Coding (SC) assisted video broadcasting, which curbs the error propagation introduced both by the inter-layer dependency and the Successive Interference Cancellation (SIC) required by the superimposed signal. Specifically, we formulate an Objective Function (OF) based on the average video quality across the Base Station's (BS) coverage area and then determine the optimal power scaling coefficients of each video layer using a bespoke Evolutionary Algorithm (EA). Our solution strikes a compelling compromise between the best possible video service provided for the cell-centre and the cell-edge users. Explicitly, our simulation results show that the optimal-power SC system guarantees a better compromise than its Time Division Multiplexing (TDM) and conventional QAM assisted counterparts, despite its reduced receiver complexity.

Wireless communication is facing an ever-increasing thirst for high-quality data transmission. However, this imposes high demands on the radio access networks (RAN), where optical fiber has been widely used both for the backhaul and fronthaul. However, the explosive escalation of wireless teletraffic tests the limits of the RAN’s revenue vs cost trade-off, which motivates low-cost designs. Hence, we present a costefficient yet high-performance radio over fiber (RoF) aided RAN concept. We commence by introducing this motivation, followed by a brief introduction to analogue RoF (A-RoF) and digitised RoF (D-RoF), as well as to wireless multiple-input-multiple-input (MIMO) techniques. Then, we present the centralised RAN (CRAN) concept relying on A-RoF aided MIMO signal processing, where the MIMO signal is carried by fiber and it is processed optically in a central unit. Subsequently, we focus our attention on a C-RAN small-cell application followed by our performance vs cost analysis of the A-RoF system compared to that of its baseband counterparts, demonstrating that the A-RoF design is capable of reducing the RAN’s total cost, whilst meeting the third generation partnership project’s (3GPP) requirements

In this article, a full-duplex millimeter wave (mm-wave) enabled radio-over-fiber architecture is proposed for distributed antenna systems. This architecture is capable of achieving transmission of 16 × 16 optical multiple input multiple output spatial streams at 12 Gbps per spatial stream by employing wavelength division multiplexing and exploiting its other degrees of freedom such as polarization states and modes of wavelengths. A single laser source based multiwavelength comb and wavelength reuse techniques along with plastic optical fiber are employed to make the proposed architecture cost efficient. Optical heterodyne detection is performed at the radio access unit to generate mm-wave carrier frequency at 60 GHz. Channel equalization is achieved for pulse amplitude modulation data signal by employing least mean square equalizer to mitigate the optical fiber channel effects. Our proposed system supports 16 × 12 Gbps for downlink (DL) and uplink (UL) transmissions. To evaluate the performance of the proposed system, we compare the receiver sensitivities at forward error correction limit of 3.8 × 10 −3 of bit error ratio of back to back system, employing no fiber effects, with its counterparts. We show that acceptable power penalties for the fiber lengths of 200 and 400 m are achieved for both LP01 and LP11 modes in DL and UL directions.

In order to solve the security problem for fading channel, a pragmatic physical layer encryption (PLE) scheme is proposed, which utilizes diversity technique elaborately. Different from the conventional PLE schemes based on phase rotation for modulated symbol, the proposed scheme changed phase and amplitude together for a block of symbols each time, which can be defined as multi-dimensional PLE (MPLE). Unconventional constellation obfuscates eavesdropper, which can be seen as the first level security in physical layer. The correct probability based on chosen plaintext attacks (CPA) and known plaintext attacks (KPA) are deduced. It can be seen from the simulation results that the MPLE scheme can achieve lower attack success probability because of multi-level security and better performance based on diversity under fading channel.

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).

A novel compressed sensing-aided generalized space-frequency index modulation (CS-GSFIM) scheme is conceived for the large-scale multi-user multiple-input multiple-output uplink (LS-MU-MIMO-UL). Explicitly, the information bits are mapped both to the spatial- and frequency-domain indices, where we treat the activation patterns of the transmit antennas and of the subcarriers separately. Specifically, our indexing strategy strikes a flexible tradeoff between the throughput, performance, and complexity. In order to further increase the system's achievable rate, CS-aided pre-processing is applied to the subcarriers. An upper bound of the average bit error probability of the proposed system using the optimal maximum likelihood (ML) detector is derived, which is shown to be tight by our simulation results at moderate to high signal-to-noise ratios (SNR). Then, we design a CS-aided reduced-complexity detector, namely the reduced search-space based iterative matching pursuit (RSS-IMP), which significantly reduces the detection complexity compared to the ML detection and makes the proposed design a feasible one for LS-MU scenarios. Furthermore, the simulation results presented in this paper demonstrate that the proposed RSS-IMP detector significantly reduces the detection complexity, while attaining better performances than both the conventional MU-MIMO-OFDM (orthogonal frequency division multiplexing) system using the ML detector and the proposed system using the minimum mean square error detector. We also characterize the performances of the proposed system in the presence of channel estimation errors. Our simulation results show that the proposed CS-GSFIM system is more robust to imperfect channel than the conventional MU-MIMO-OFDM system. In order to achieve a near-capacity performance, soft-input soft-output decoders are designed for the proposed CS-GSFIM system using both the ML and the RSS-IMP multi-user detectors for detecting all users.

Emerging technologies, such as the Internet of Things, smart applications, smart grids, and machine-to-machine networks stimulate the deployment of autonomous, self-configuring, large-scale wireless sensor networks (WSNs). Efficient energy utilization is crucially important in order to maintain a fully operational network for the longest period of time possible. Therefore, network lifetime (NL) maximization techniques have attracted a lot of research attention owing to their importance in terms of extending the flawless operation of battery-constrained WSNs. In this paper, we review the recent developments in WSNs, including their applications, design constraints, and lifetime estimation models. Commencing with the portrayal of rich variety definitions of NL design objective used for WSNs, the family of NL maximization techniques is introduced and some design guidelines with examples are provided to show the potential improvements of the different design criteria.

In this study, the authors consider a two-hop network, where multiple source nodes (SNs) transmit to a destination node (DN) with the aid of a relay node (RN). The RN is equipped with a buffer, which is capable of storing multiple frames received from the SNs. During each time slot, the proposed protocol activates either the SN–RN hop or the RN–DN hop, depending on the channel quality of each hop and the buffer state at the RN. To optimise the hop activation for the network, they design a hop quality metric and propose a multi-user buffer-aided-relaying uplink (MU-BR-UL) protocol, with the aid of the minimum signal-to-noise power ratio approximation. The benefits of the proposed protocol are analysed in terms of the end-to-end (e2e) outage probability and the e2e transmission delay. Then, the optimal power allocation is proposed for minimising the e2e outage probability under the total power constraint. The results indicate that the outage performance is significantly improved when the proposed power allocation is utilised in the MU-BR-UL protocol.

Optical single sideband (OSSB) signals are conventionally generated using a dual-drive Mach–Zehnder modulator (MZM) or by using a single-drive MZM in conjunction with a fibre Bragg grating filter. In this study, the authors propose and mathematically characterise a novel radio over fibre downlink in which an OSSB signal is generated using a single-drive, rather than dual-drive, MZM without any additional filter. Additionally, their proposed scheme can achieve optical upconversion of the electronic signal. Furthermore, in addition to cost advantages, the proposed scheme’s BERQ3 performance is better than the classical OSSB signal generation scheme.

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 space-time shift keying (STSK), the information is conveyed by both the spatial and time dimensions, which can be used to strike a trade-off between the diversity and multiplexing gains. On the other hand, orthogonal frequency division multiplexing (OFDM) relying on index modulation (IM) conveys information not only by the conventional signal constellations as in classical OFDM, but also by the indices of the subcarriers. In this paper, we combine the benefits of STSK and IM in order to strike a flexible trade-off between the throughput and bit-error performance by transmitting extra information bits in each subcarrier block, whilst increasing the diversity order. In order to further improve this trade-off, as well as to decrease the complexity of the detector, compressed sensing (CS) is combined with the proposed STSK-aided IM system. We first present the Maximum LikeLihood (ML) detection, which forms the best-case bound on the proposed system's performance. Then we propose a pair of reduced-complexity detection algorithms capable of approaching the ML detector's performance. Furthermore, in order to attain a near capacity-performance, we propose a soft-input-soft-output (SISO) decoder that is capable of exchanging soft-information with a channel decoder through iterative decoding.

In this correspondence, we propose a dual-function hybrid beamforming architecture, where the antenna array is split into sub-arrays that are separated by a sufficiently large distance so that each sub-array experiences independent fading. The proposed architecture attains the dual-functions of beamforming and diversity. We then demonstrate that splitting the array into two sub-arrays provides the best performance in terms of the achievable rate as a benefit of the diversity gain obtained in addition to the beamforming gain. However, the performance starts depleting if the array is partitioned into more than two sub-arrays because of diminishing additional diversity gains, which fails to compensate for the beamforming gain erosion due to splitting the antenna arrays. Additionally, we analyze the so-called discrete Fourier transform-mutually unbiased bases (DFT-MUB) aided codebook invoked for the conceived design, which imposes an appealingly low complexity. Explicitly, we show that for the proposed dual-function sub-array-connected design, the DFT-MUB assisted codebook outperforms the state-of-the-art precoding benchmarks and performs close to the optimal precoding matrix.

An all-optical processing aided multi-functional wireless Multiple-Input-Multiple-Output (MIMO) architecture is designed, where both diversity and beamforming gains can be attained. Explicitly, we propose an architecture, where the twin-antenna Alamouti space-time block coded symbols are transmitted using a single Mach-Zenhder Modulator (MZM) over a plastic optical fiber. The signal is then transmitted through a set of Fiber Bragg Gratings (FBGs) for attaining the appropriate phase shifts for beamforming, followed by transmission over the wireless channel. The attainable angular beamsteering range is about 150, where beamsteering is realized without the need for a large number of complex electronic phase shifter networks. The tuning of the beamsteering angle can be readily implemented by carefully controlling the drive voltage in the Mach-Zenhder Modulator, where we use MZM aided multi-wavelength generation for supporting a large number of antennas.

A wireless personal area network (WPAN) allows the wireless devices in a user's personal workspace to be connected to the network. Due to the huge increase in both the number of wireless communication subscribers and the bandwidth required per customer with the proliferation of smart devices, the low-frequency radio spectrum is becoming overcrowded. A natural solution for future WPANs is to migrate to higher radio frequency (RF) carriers [1]. High data-rate WPANs may be implemented based on the Federal Communications Commission (FCC) compliant ultrawideband (UWB) standard [2] or on the IEEE 802.15.3c standard [3]. The UWB signal was defined by the FCC as a signal having a bandwidth larger than 20% of the carrier frequency or a bandwidth of at least 500 MHz in the 3.1-10.6-GHz band; IEEE 802.15.3c relies on a carrier frequency in the 60-GHz license-free industrial, scientific, and medical (ISM) band. The implementation of both the UWB standard and the IEEE 802.15.3c standard faces certain challenges, which may be tackled with the aid of radio over fiber (ROF) techniques that employ optical generation of the wireless signal. ROF networking solutions have been proposed for future high-bandwidth wireless communication systems that rely on the transmission of RF signals between the base station (BS) and remote antennas [1], [4]-[8].

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 propose and mathematically characterize a novel radio-over-fiber (ROF) downlink, where a radio access point (RAP) benefits from the transmit diversity gain of space-time block coding (STBC). Significantly, this transmit diversity is achieved using a single optical modulator in the base station (BS). In the proposed architecture, each RAP is fed with a single optical double-sideband signal, where each sideband transmits one of the two STBC-encoded signals. This optical signal is generated in the BS by performing the simultaneous optical upconversion of the baseband STBC signals using a single Mach-Zehnder modulator. The proposed optical backhaul is designed and simulated to impose negligible degradation to that imposed by the dominant wireless link, thereby enabling a designer to exploit the advantages offered by a wireless link having a diversity gain.

We propose and mathematically characterize a novel Radio Over Fiber (ROF) architecture, which uses a single MZM for simultaneously modulating the intensity and phase of an optical carrier with either two different RF signals or a RF signal and a baseband signal. The detection of these two independent signals is conceived along with possible applications of the proposed architecture. The operation and performance of the proposed system is shown through simulations.

The millimeter wave (mmWave) frequency band spanning from 30 GHz to 300 GHz constitutes a substantial portion of the unused frequency spectrum, which is an important resource for future wireless communication systems in order to fulfill the escalating capacity demand. Given the improvements in integrated components and enhanced power efficiency at high frequencies, wireless systems can operate in the mmWave frequency band. In this paper, we present a survey of the mmWave propagation characteristics, channel modeling and design guidelines, such as system and antenna design considerations for mmWave, including the link budget of the network, which are essential for mmWave communication systems.We commence by introducing the main channel propagation characteristics of mmWaves followed by channel modeling and design guidelines. Then, we report on the main measurement and modeling campaigns conducted in order to understand the mmWave band’s properties and present the associated channel models. We survey the different channel models focusing on the channel models available for the 28 GHz, 38 GHz, 60 GHz and 73 GHz frequency bands. Finally, we present the mmWave channel model and its challenges in the context of mmWave communication systems design.

Fibre links that are a few hundreds of metres long are needed for in-building networks. However, the transmission of radio-frequency (RF) signals through low-cost, easily installable plastic optical fibre (POF) is severely limited by their bandwidth-length products. Digitised radio over fibre (DROF) converts the RF signal into a baseband signal through bandpass sampling prior to its transmission, thereby reducing the fibre bandwidth required for the RF signal's transmission. For the first time, a POF-based DROF link relying on the Ethernet protocol is proposed and the initial experimental results for a link that employs a 143 m long step-index POF and uncoded RF modulation are presented. A 5 GHz RF signal through the POF is transmitted. The same method can be employed for higher RF carriers as well. The RF bit rate was ∼30% of the protocol-dependent DROF bit rate.

A novel detect-and-forward (DeF) relaying aided cooperative SM scheme is proposed, which is capable of striking a flexible tradeoff in terms of the achievable bit error ratio (BER), complexity and unequal error protection (UEP). More specifically, SM is invoked at the source node (SN) and the information bit stream is divided into two different sets: the antenna index-bits (AI-bits) as well as the amplitude and phase modulation-bits (APM-bits). By exploiting the different importance of the AI-bits and the APM-bits in SM detection, we propose three low-complexity, yet powerful relay protocols, namely the partial, the hybrid and the hierarchical modulation (HM) based DeF relaying schemes. These schemes determine the most appropriate number of bits to be re-modulated by carefully considering their potential benefits and then assigning a specific modulation scheme for relaying the message. As a further benefit, the employment of multiple radio frequency (RF) chains and the requirement of tight inter-relay synchronization (IRS) can be avoided. Moreover, by exploiting the benefits of our low-complexity relaying protocols and our inter-element interference (IEI) model, a low-complexity maximum-likelihood (ML) detector is proposed for jointly detecting the signal received both via the source-destination (SD) and relay-destination (RD) links. Additionally, an upper bound of the BER is derived for our DeF-SM scheme. Our numerical results show that the bound is asymptotically tight in the high-SNR region and the proposed schemes provide beneficial system performance improvements compared to the conventional MIMO schemes in an identical cooperative scenario.

Layered video coding creates multiple layers of unequal importance that enables us to progressively refine the reconstructed video quality. When the base layer (BL) is corrupted or lost during transmission, the enhancement layers (ELs) must be dropped, regardless of whether they are perfectly decoded or not, which implies that the transmission power assigned to the ELs is wasted. In this treatise, we propose an inter-layer forward error correction (FEC) coded video transmission scheme for mobile TV. At the transmitter, the proposed interlayer (IL) coding technique implants the systematic information of the BL into the ELs by using exclusive-OR operations. At the receiver, the implanted bits of the ELs may be utilized for assisting in decoding the BL. Furthermore, the data partition mode of H.264 video coding is utilized as the source encoder, where the type B and type C partitions will assist in protecting the type A partition. The IL coded bitstream will then be modulated and transmitted over a multifunctional multiple input multiple output (MF-MIMO) scheme for the sake of improving the system's performance in mobile environments. The proposed system may be readily combined with the traditional unequal error protection (UEP) technique, where extrinsic mutual information (MI) measurements are used for characterizing the performance of our proposed technique. Finally, our simulation results show that the proposed system model outperforms the traditional UEP aided system by about 2.5 dB of Eb/N0 or 3.4 dB of peak signal-to-noise ratio (PSNR) at the cost of a 21% complexity increase, when employing a recursive systematic convolutional code. Furthermore, unlike the traditional UEP strategies, where typically stronger FEC-protection is assigned to the more important layer, employing our proposed IL coding technique requires weaker FEC to the more important layer. For example, the system relying on channel coding rates of 0.85, 0.44, and 0.44 for the type A, type B, and type C H.264 video partitions, respectively, achieves the best system performance when employing a recursive systematic convolutional (RSC) code.

We design distributed multiple-component turbo-codes (MCTCs) for cooperative automatic repeat request (CARQ) aided systems, which are capable of attaining both a similar performance and throughput as the conventional twin-component turbo code (TCTC) aided system, while imposing a significantly lower decoding complexity. The reduction in the decoding complexity of the MCTC-CARQ scheme is a direct benefit of using low-memory MCTC component encoders, combined with the novel principle of deferred iteration (DI), where the decoding process is only initiated when sufficient information has been accumulated at the receiver so that an open tunnel exists in the Extrinsic information transfer (EXIT) charts. In the presence of multiple collaborating relay nodes (RNs), the specific RN which succeeds in decoding the source message, and additionally, has the highest signal-to-noise ratio at the destination node is selected as the retransmission node. Our numerical results demonstrate that the proposed MCTC-CARQ protocol is capable of reducing the decoding complexity by up to 40% compared to its TCTC-CARQ counterpart, while achieving the same throughput and reliability.

Energy efficiency is a primary design goal for future green wireless communication technologies. Multiple-input multiple-output (MIMO) schemes have been proposed in the literature to improve the throughput of communication systems, and they are expected to play a prominent role in the upcoming fifth generation (5G) standard. This paper presents a novel, high-efficiency MIMO decoder based on the K-Best algorithm with lattice reduction. We have designed a novel hardware architecture for this decoder, which was implemented using 32 nm standard CMOS technology. Our results show that the proposed decoder can achieve on average a four-fold reduction in the power costs compared to recently published designs for 5G networks. The throughput of the design is 506 Mbits/s, which is comparable to existing designs.

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.

We analytically characterize the data-aided error vector magnitude (EVM) performance of a single-input multiple-output (SIMO) communication system relying on maximal ratio combining (MRC) having either independent or correlated branches that are nonidentically distributed. In particular, exact closed form expressions are derived for the EVM in $\eta\text{-}\mu$ fading and $\kappa W\mu$ shadowed fading channels and these expressions are validated by simulations. The derived expressions are expressed in terms of Lauricella’s function of the fourth kind $F_D^{(N)}(.)$ , which can be easily computed. Furthermore, we have simplified the derived expressions for various special cases such as independent and identically distributed branches, Rayleigh fading, Nakagami- m fading, and $\kappa\text{-}\mu$ fading. Additionally, a parametric study of the EVM performance of the wireless system is presented.

A study of advanced upconversion techniques used in Radio Over Fiber (ROF) is provided. With the huge increase in both the number of wireless communication subscribers and the bandwidth required per customer, migrating to higher frequencies i.e. from lower radio frequency to millimeter wave carriers is an essential solution. However, due to the short propagation range of millimeter waves, a large number of radio access points are required for providing reliable coverage, which would increase the infrastructure costs. Hence, the transmission of RF signals between the central (or control) points and radio access points (or remote antenna units) using optical fibers is one of the major access network solutions that have been proposed for future high-bandwidth wireless communication systems. In this paper we introduce the basics of Radio Over Fiber communication including optical modulation, the optical channel and the optical detection techniques. Then we survey the family of advanced optical upconversion techniques that exploit the non-linearity of the ROF link. Specifically, we describe how optical upconversion can be achieved by exploiting the Mach Zhender Modulator’s (MZM’s) non-linearity, wavelength conversion techniques or the photo-detector’s non-linearity. The wavelength conversion techniques rely on the non-linearities present in the fiber, in the optical amplifier or in the Electro-Absorption Modulator (EAM).

In this study, the authors investigate the benefits of phase-rotation-assisted precoding (PRP) technique in spatial modulation (SM) systems, which are based on maximum free distance d min. First, a closed-form solution of the maximum-d min PRP matrix is derived for the scenario of having two transmit antennas (N t = 2). Moreover, two numerical methods are proposed for dealing with the case of N t > 2. The complexity of the proposed algorithms is presented. The authors simulation results show that the proposed PRP algorithms provide beneficial bit error ratio performance improvements compared with both the conventional SM and with the existing adaptive SM.

Compared to battery-powered wireless nodes having a constant but limited power supply, wireless nodes having energy harvesting (EH) capability may greatly prolong the network's sustainability. However, the energy usage policies (EUPs) have to be carefully designed according to the characteristics of the random power supply gleaned from the environment. In this paper, we carry out the outage analysis of a point-to-point (P2P) network relying on an EH transmitter, which has a finite energy buffer (EB) for transmission over a fading channel when having random energy arrival rates. A discrete Markov chain (DMC) model is proposed for characterizing the energy state of the EB, which is then used for quantifying the outage probability (OP) over the fading channels. Then, we propose both a novel 2-D and a low-complexity 1-D search algorithm for finding the specific EUPs, which are capable of minimizing the OP for the P2P network considered. It is shown that the EUP found by both algorithms outperforms the state-of-the-art EUPs disseminated in the open literature. Furthermore, we consider a multiple-access network having $M$ EH-aided sources, where we propose a distributed EUP optimization (DEUPO) algorithm and then minimize the OP relying on the local optimization of each EH-aided source.

We consider a network, where multiple source–destination (S–D) pairs communicate with the aid of a half-duplex relay node (RN), which adopts decode-and-forward (DF) relaying and superposition modulation (SPM) for combining the signals transmitted by the source nodes (SNs) and then forwards the composite signal to all the destination nodes (DNs). Each DN extracts the signals transmitted by its own SN from the composite signal by subtracting the signals overheard from the unwanted SNs. We derive tight lower bounds for the outage probability for transmission over Rayleigh fading channels and invoke diversity combining (DC) at the DNs, which is validated by simulation for both the symmetric and the asymmetric network configurations. For the high signal-to-noise ratio regime, we derive both an upper bound and a lower bound for the outage performance and analyze the achievable diversity gain. It is revealed that a diversity order of 2 is achieved, regardless of the number of SN–DN pairs in the network. We also highlight the fact that the outage performance is dominated by the quality of the worst overheated link because it contributes most substantially to the network coding (NC) noise. Finally, we use the lower bound for designing a relay selection scheme for the proposed SPM-based network-coded cooperative communication (SPM-NC-CC) system.

Advanced cost reduction and performance improvement techniques conceived for Radio Over Fiber (ROF) communications are considered. ROF techniques are expected to form the backbone of the future fifth generation of wireless networks. The achievable link performance and the associated deployment cost constitute the most salient metrics of an ROF architecture. In this paper, we commence by providing a rudimentary overview of the ROF architecture, and then we elaborate on ROF techniques designed for improving the attainable system performance. We conclude by describing the ROF techniques conceived for reducing the ROF system installation costs.

Pilot contamination constitutes a particularly significant impairment in large-scale multi-cell systems. We propose an effective pilot contamination elimination scheme for multi-cell time division duplexing based orthogonal frequency division multiplexing systems, by carefully designing a sophisticated amalgam of downlink (DL) training and `scheduled' uplink (UL) training. During the DL training stage, each base station (BS) transmits the DL pilot symbols (PSs) to its mobile stations (MSs) for them to estimate their frequency-domain channel transfer functions (FDCHTFs), which are then embedded in the UL PSs by `predistorting' the PSs with the estimated FDCHTFs. During the scheduled UL training, each BS's UL receiver in turn extracts the FDCHTFs of its MSs from their received PSs by eliminating the pilot contamination imposed by the simultaneously transmitted UL PSs of all other cells. Our simulation results demonstrate that the pilot contamination is completely eliminated by the proposed scheme, even for the network consisting of a large number of unity frequency reuse cells. Most significantly, unlike many existing pilot contamination reduction schemes, our scheme does not rely on the assumption that each BS knows the second-order statistics of all the interfering UL channels.

Wireless communications is taught in most electronics degree curricula worldwide, where the main focus is the theory of communications. While it is essential that students learn the theory of communications, this is not enough to prepare them for their careers in industry. This is due to the fact that there are several practical challenges in designing and implementing wireless communications systems that are overlooked when focusing only on theory. Hence, in this article we describe the main challenges in designing practical communications systems, and demonstrate how the National Instruments Universal Software Radio Peripheral can be used for introducing and educating students about these challenges.