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In this paper, we propose a novel multiuser generalized spatial modulation (GSM) detection scheme for uplink massive MIMO systems. In GSM, the indices of the active antennas of each user terminal are used to convey information in addition to the transmitted symbols. Hence, a two-stage detection structure is developed consisting of preprocessing (identification) and postprocessing (detection). At the receiver front end, we propose an eigenvalue decomposition-based active antennas identification algorithm to decode the first part of data. Based on the acquired channel state information, a least-square-based decorrelating detector is developed to extract the second part of data symbol. The system capacity (transmitted bits per channel use) is extensively increased compared to the conventional spatial modulation scheme, and the complexity is significantly reduced than existing algorithms. Computer simulations demonstrate that the proposed algorithm is near-far resistant and works reliably for small window size, which is essential for the low-latency requirement in 5G and future networks. [ABSTRACT FROM AUTHOR]

Exploiting the sparse user activity induced by sporadic transmission, compressed sensing (CS) has been widely applied in multiple-input multiple-output (MIMO) enabled non-orthogonal multiple access (NOMA) for efficient multiuser detection. However, most of the existing detection schemes in MIMO enabled NOMA systems focus mainly on the spatial structure in user activity induced by multiantenna reception, while the temporal correlation in user activity has rarely been incorporated for further performance improvement. To address this issue, we propose a novel Multiuser Detection framework in MIMO enabled NOMA (MDMN), which explicitly integrates the temporal correlation in user activity into the detection process to improve the user detection accuracy. Specifically, we first formulate multiuser detection with multiantenna reception in MDMN as a block CS problem, by exploiting the spatial correlation in user activity. Furthermore, through incorporating the temporal correlation in active user sets into block CS, an adaptive CS algorithm based on subspace pursuit is developed for MDMN, named spatial-temporal correlation enhanced adaptive subspace pursuit (STASP). In particular, STASP does not require any prior knowledge of the user sparsity, as the cross validation designed in STASP can properly terminate the algorithm. The superior performance of the proposed MDMN framework and the corresponding algorithms is corroborated by extensive simulation results. [ABSTRACT FROM AUTHOR]

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The large scale multiuser multiple input multiple output (MU-MIMO) is one of the promising communication technology for 5G wireless networks as it offers reliability, high spectral efficiency and high throughput. The lattice reduction (LR) precoding based user level local likelihood ascent search (ULAS) detection scheme is proposed in this paper for efficient signal detection in large scale MU-MIMO system. The initial solution of ULAS algorithm is obtained from the LR precoding assisted zero forcing detector. The LR precoding transforms the non-orthogonal channel matrix into nearly orthogonal channel, which helps to mitigate inter antenna interference (IAI) exists at each user. The remaining multiuser interference (MUI) imposed to each user from undesired users is cancelled by the proposed ULAS multiuser detection scheme. Thus, the proposed LR precoding assisted ULAS mitigates both IAI and MUI unlike the classical detector, those try to moderate either IAI or MUI. By contrast, the proposed ULAS detector provides performance close to optimal maximum likelihood detector with just a fraction of its complexity. [ABSTRACT FROM AUTHOR]

Analysis on the exact error rate of jointly optimal (JO) maximum likelihood (ML) multiuser detection is limited in the existing literature owing to its high computational complexity. In this paper, the JO ML detection of two quadrature phase-shift keying (QPSK) signals with an arbitrary relative phase offset is investigated. Exact, analytical symbol error rate (SER) and bit error rate (BER) formulas are derived for two users with no less than 3 dB power difference between them. Closed-form union bounds on the user SER and BER with an arbitrary phase offset and an arbitrary user power ratio are also given as a simpler approach to acquire the asymptotic error rate performance. Furthermore, insights on the potentials and properties of the JO ML detector regarding its error rate behaviors for each user are revealed through comparisons with the successive interference cancellation receiver. The accuracies of the obtained formulas are demonstrated through simulation. The results show the error rates for the two-user QPSK case no longer follow the classic knowledge on the error rate behaviors in the single signal detection. In addition, the performance and dB penalty employing different modulation types are also compared and discussed. [ABSTRACT FROM AUTHOR]

A full‐duplex (FD) multiuser multiple‐input multiple‐output (MU‐MIMO) system, where a FD base station (BS) with multiple antennas serves multiple half‐duplex (HD) user equipments (UEs) in both uplink (UL) and downlink (DL) via the same time‐frequency resources, is considered. UE scheduling is in demand to manage the UL‐to‐DL interference (UDI) incurred by the FD operation. Existing scheduling algorithms require UDI channel state information between each pair of the candidate UEs, which incurs a significant amount of overhead as the number of UEs grows. To reduce the overhead, a new UE scheduling algorithm that uses channel reciprocity and UL‐DL duality to design a scheduling algorithm based on downlink performance was designed. By selecting UEs only based on their DL channels and received UDI strength, the proposed scheme no longer requires the massive UDI channel state information (CSI). Numerical results demonstrate the proposed algorithm can achieve a near optimal performance without knowing any UDI CSI. [ABSTRACT FROM AUTHOR]

Sparse-aware (SA) detectors have attracted a lot attention due to its significant performance and low-complexity, in particular for large-scale multiple-input multiple-output (MIMO) systems. Similar to the conventional multiuser detectors, the nonlinear or compressive sensing based SA detectors provide the better performance but are not appropriate for the overdetermined multiuser MIMO systems in sense of power and time consumption. The linear SA detector provides a more elegant tradeoff between performance and complexity compared to the nonlinear ones. However, the major limitation of the linear SA detector is that, as the zero-forcing or minimum mean square error detector, it was derived by relaxing the finite-alphabet constraints, and therefore its performance is still sub-optimal. In this paper, we propose a novel SA detector, named single-dimensional search-based SA (SDSB-SA) detector, for overdetermined uplink MIMO systems. The proposed SDSB-SA detector adheres to the finite-alphabet constraints so that it outperforms the conventional linear SA detector, in particular, in high SNR regime. Meanwhile, the proposed detector follows a single-dimensional search manner, so it has a very low computational complexity which is feasible for light-ware Internet of Thing devices for ultra-reliable low-latency communication. Numerical results show that the the proposed SDSB-SA detector provides a relatively better tradeoff between the performance and complexity compared with several existing detectors. [ABSTRACT FROM AUTHOR]

Inter-symbol interference (ISI) causes many errors in modulated symbols, when they are transmitted through band-limited channels. According to the multipath delay profile of the channel, the modulated symbol may disperse over more than one symbol period casing interferences among the received symbols. In this paper, the ISI signal is not considered as a problem, but it is exploited as a source of time diversity for the modulated symbols. The ISI signal is considered as if the modulated symbols are transmitted more than one time through different symbols periods. The number of periods over which the modulated symbol extends, represents the time diversity gain of the proposed system. In the proposed receiver, the interfering symbols are considered as symbols from different users. A multiuser detector is used to demodulate these interfering symbols. Moreover, a signal combiner is used to collect the detected symbol from the output of the multiuser detector through the dispersion period of the channel. The output of the combiner represents the decision variable to the baseband detector. The diversity gain in the decision variable in the proposed receiver is proportional to the dispersion period of the channel. [ABSTRACT FROM AUTHOR]

In this paper, a new mode selection (MS) scheme for device-to-device (D2D) enabled cellular networks is proposed. The MS is carried out using a predefined signal-to-interference plus noise ratio (SINR) threshold and it aims to guarantee a minimum level of quality of service. With the new scheme, interfering effects are taken into consideration, while realistic assumptions for the acquisition of the channel information are made. Assuming a single-user case, an analytical framework is developed, which is based on the Markov-chain theory, and is used to study the system's performance. The various performance results obtained reveal that with the proposed MS, the probability of mode switching can be reduced (as compared to other systems), and thus, an increase on the overhead and signal processing is avoided. Moreover, a new approach is applied in a multi-user communication scenario, where a joint MS, resource allocation (RA), and scheduling optimization problem is formulated. The solution to this problem is based on a greedy heuristic algorithm that properly assigns the available resources among cellular users and D2D pairs. The joint MS, RA, and scheduling algorithm considers limited SINR awareness and it provides significant performance improvement in terms of sum-rate. [ABSTRACT FROM AUTHOR]

To achieve ultra-low latency mobile networking, recent efforts to integrate virtual cell with open-loop communications and proactive network association suggest the facilitation of new technological paradigm, but the interference from different co-locating virtual cells is hard to handle. Open-loop transmissions make beam-forming/interference alignment infeasible due to the need of channel state information feedback. Multiuser detection (MUD) is therefore employed to address the downlink interference. We note that the bit error rate (BER) of maximum-likelihood MUD (ML-MUD) is sensitive to the modulation of the interference. As the interferer uses low-order modulation, the BER of desired signal can approach the ideal case without interference. But if the interferer adopts high-order modulation, the resultant BER is significantly degraded. Our study shows that, such modulation sensitivity can be eased by the multi-antenna technique. We also propose two methods to reduce the notorious computational complexity of MUD, particularly involving higher order modulations. The first scheme is termed as the reduced-computation ML-MUD (R-ML-MUD) that exploits the characteristic of downlink to shrink the ML solution space, consequently leading to lower detection complexity. The second scheme is a new projection receiver, called generalized linear minimum mean square error equalizer, resulting in notable signal-to-noise ratio gain over the conventional projection method. The simulation results indicate that the proposed schemes and their integration can achieve satisfactory BER performance. [ABSTRACT FROM AUTHOR]

We propose a method for multiple-input multiple-output (MIMO) decoding when channel-state information (CSI) is unknown to both the transmitter and receiver. The proposed method requires some structure in the transmitted signal for the decoding to be effective, in particular that the underlying sources are drawn from a hypercubic space. Our proposed technique fits a minimum volume parallelepiped to the received samples. This problem can be expressed as a non-convex optimization problem that can be solved with high probability by gradient descent. Our blind decoding algorithm can be used when communicating over unknown MIMO wireless channels using either binary phase-shift keying or MPAM modulation. We apply our technique to jointly estimate MIMO-channel gain matrices and decode the underlying transmissions with only knowledge of the transmitted constellation and without the use of pilot symbols. Our results provide theoretical guarantees that the proposed algorithm is correct when applied to MIMO systems with four or fewer transmit antennas. Empirical results show small sample size requirements, making this algorithm suitable for block-fading channels with coherence times typically seen in practice. Our approach has a loss of less than 3 dB compared to zero forcing with perfect CSI, imposing a similar performance penalty as space-time coding techniques without the loss of rate incurred by those techniques. [ABSTRACT FROM AUTHOR]

Abstract Next-generation IEEE 802.11ax Wireless Local Area Networks (WLANs) will make extensive use of multi-user communications in both Downlink (DL) and Uplink (UL) directions to achieve high and efficient spectrum utilization in scenarios with many user stations per access point. It will become possible with the support of Multiuser (MU) Multiple Input, Multiple output (MIMO) and Orthogonal Frequency Division Multiple Access (OFDMA) transmissions. In this paper, we first overview the novel characteristics introduced by IEEE 802.11ax to implement AP-initiated OFDMA and multiuser MIMO (MU-MIMO) transmissions in both DL and UL directions. Namely, we describe the changes made at the Physical (PHY) layer and at the Medium Access Control (MAC) layer to support OFDMA, the use of trigger frames to schedule uplink multi-user transmissions, and the new multiuser RTS/CTS mechanism to protect large multi-user transmissions from collisions. Then, in order to study the achievable throughput of an IEEE 802.11ax WLAN, we use both mathematical analysis and simulations to numerically quantify the gains of MU transmissions and the impact of IEEE 802.11ax overheads on the WLAN saturation throughput. Results show the advantages of using MU transmissions in scenarios with many user stations. Additionally, we provide novel insights on the conditions in which IEEE 802.11ax WLANs are able to maximize their performance, such as the need to provide strict prioritization to AP-initiated MU transmissions to avoid collisions with transmissions from user stations. [ABSTRACT FROM AUTHOR]

Multi-view plus-depth-map (MVD) video streaming with autostereoscopic displays provides multi-user immersive media experiences. In this context, delivery of MVD representation to multiple clients remains a challenging problem because of the high-volume of data involved and the inherent limitations imposed by the delivery networks. To this end, this paper investigates the side information (SI) assisted adaptation algorithm using peer-to-peer (P2P) systems. P2P delivery systems for MVD video can maximize link utilization, preventing the transport of multiple video copies of the same packet for many users. However, the quality of experience (QoE) can be significantly degraded by dynamic variations caused by network congestions. To this end, our solution comprises the extraction of low-overhead metadata at the encoding server that is distributed through the P2P network as SI and used by P2P clients performing network adaptation. In the proposed adaptation strategy, pre-selected views are discarded at times of network congestion and reconstructed with an optimal reconstruction performance using the delivered SI and the delivered neighboring camera views. The experimental results show that the robustness of P2P multi-view streaming using the proposed adaptation scheme is significantly increased in the P2P network. [ABSTRACT FROM AUTHOR]

A multiuser detection (MUD) algorithm based on deep learning network is proposed for the satellite mobile communication system. Due to relative motion between the satellite and users, multiple access interference (MUI) introduced by multipath fading channel reduces system performance. The proposed MUD algorithm based on deep learning network firstly establishes the CINR optimal loss function according to the multiuser access mode and then obtains the best multiuser detection weight through the steepest gradient iteration. Multilayer nonlinear learning obtains interference cancellation sharing weights to achieve maximum signal-to-noise ratio through gradient iteration, which is superior than the traditional serial interference cancellation algorithm and parallel interference cancellation algorithm. Then, the weights with multiuser detection through multilayer network forward learning iteration are obtained with traditional multiuser detecting quality characteristics. The proposed multiuser access detection based on deep learning network algorithm improves the MUD accuracy and reduces the number of traditional multiusers. The performance of the satellite multifading uplink system shows that the proposed deep learning network can provide high precision and better iteration times. [ABSTRACT FROM AUTHOR]

This paper investigates an iterative multiuser detection for nonbinary low density parity check (LDPC) coded multicarrier multiple level frequency shift keying system to increase system performance under specific signal-to-noise ratio and data rate. We propose three-level hard-limited detection probabilities over both additive white Gaussian noise (AWGN) channels and Rayleigh fading channels. During multiuser detection (MUD) process, the hard-limited detection probabilities are computed in advanced and stored in tables. By using table looking up, the MUD soft outputs can be computed efficiently. We test the reliability of soft outputs from nonbinary LDPC channel decoder for all users. If the soft output exceeds a reliability threshold, the user is declared as a reliable user. For each symbol, we count the number of reliable users on it, and, use this information to update the soft output of MUD during the iterative multiuser detection and decoding process, which cancel multiple access interference iteratively. Numerical results show that the performances of three-level hard-limited systems outperform two-level hard-limited systems over AWGN channels and Rayleigh fading channels. [ABSTRACT FROM AUTHOR]

Summary: This paper addresses the problem of multiuser interference in the forward downlink channel of a multibeam satellite system. A symbol‐level precoding scheme is considered, to exploit the multiuser interference and transform it into useful power at the receiver side, through a joint utilization of the data information and the channel state information. In this context, a per‐antenna power minimization scheme is proposed, under quality‐of‐service constraints, for multilevel modulation schemes. The consideration of the power limitations individually for each transmitting radio frequency chain is a central aspect of this work, and it allows to deal with systems using separate per‐antenna amplifiers. Moreover, this feature is also particularly relevant for systems suffering nonlinear effects of the channel. This is the case of satellite systems, where the nonlinear amplifiers should be properly driven to reduce the detrimental saturation effect. In the proposed scheme, the transmitted signals are designed to reduce the power peaks, while guaranteeing some specific target signal‐to‐noise ratios at the receivers. Numerical results are presented to show the effectiveness of the proposed scheme, which is compared both with the state of the art in symbol‐level precoding and with the conventional minimum mean square error precoding approach. This paper presents a symbol‐level precoding scheme which performs a per‐antenna power minimization under quality‐of‐service constraints, for multi‐level modulations. Besides exploiting constructive interference, the proposed technique allows a reduction of the power peaks at the transmitting antennas, which is particularly important for satellite systems corrupted by nonlinear effects. Numerical results are presented to show the effectiveness of the proposed scheme, compared with the state‐of‐the‐art symbol‐level precoding and to the conventional MMSE scheme. [ABSTRACT FROM AUTHOR]

In this paper, the user-relay assignment based antenna selection scheme for multi-user cooperative network is proposed to improve the transmission bit rate and system performance. The low complexity suboptimal user-relay assignment algorithm is first proposed to simultaneously improve both the system performance and individual user' performance in the multi-user amplify-and-forward (AF) cooperative user-relay network, where each user can fairly select its best relay according to the instantaneous channel state information (CSI). Based on the user-relay assignment scheme and space shift keying (SSK), we further present the antenna selection scheme to further enhance the system performance for the multi-user AF cooperative user-relay network. In order to minimize the system bit error rate (BER), three antenna selection criteria based on the maximum likelihood (ML) detection have been proposed. Numerical results and theoretical analysis show that the proposed schemes can effectively improve the average system sum rate, the outage probability of the worst user, and the system BER performance, compared with the other schemes. [ABSTRACT FROM AUTHOR]

A key challenge of massive MTC (mMTC), is the joint detection of device activity and decoding of data. The sparse characteristics of mMTC makes compressed sensing (CS) approaches a promising solution to the device detection problem. However, utilizing CS-based approaches for device detection along with channel estimation, and using the acquired estimates for coherent data transmission is suboptimal, especially when the goal is to convey only a few bits of data. First, we focus on the coherent transmission and demonstrate that it is possible to obtain more accurate channel state information by combining conventional estimators with CS-based techniques. Moreover, we illustrate that even simple power control techniques can enhance the device detection performance in mMTC setups. Second, we devise a new non-coherent transmission scheme for mMTC and specifically for grant-free random access. We design an algorithm that jointly detects device activity along with embedded information bits. The approach leverages elements from the approximate message passing (AMP) algorithm, and exploits the structured sparsity introduced by the non-coherent transmission scheme. Our analysis reveals that the proposed approach has superior performance compared with application of the original AMP approach. [ABSTRACT FROM AUTHOR]

Abstract In the presence of nonlinear distortion, the performance degradation of multiuser multiple-input multiple-output (MU-MIMO) systems becomes significant. The performance loss comes not only from the in-band nonlinear distortion, but also from the imperfect cancellation of multiuser interference (MUI) due to the nonlinear distortion. In this regard, we analyze characteristics of nonlinear distortion in an MU-MIMO system. Numerical results show that even tiny nonlinear distortion severely degrades the performance of MU-MIMO system. A nonlinear minimum mean square error (NMMSE) detection algorithm is proposed to improve the system performance. The proposed detection algorithm improves the system performance at low additional cost. [ABSTRACT FROM AUTHOR]

Abstract: For wideband Cognitive Radio (CR) devices, the availability of primary user (PU) activity prediction model can save sensing energy and time, track spectrum variations, reduce switching overhead, improve spectrum usage and lower interference to PU. Using Universal Software Radio Peripheral (USRP) generated data, this paper has verified the superiority of Hidden Semi-Markov model (HSMM) over the conventional HMM in learning and predicting temporal correlations in PU spectral activity under non-geometric distribution of state durations. Numerical simulations further show that in a coordinated multi-SU/PU scenario, compared to the traditional random Carrier Sense Multiple Access (CSMA), the proposed HSMM-dynamic spectrum allocation (DSA) protocol significantly reduces aggregate interference to PU. Depending on the number of SU, there exists a trade-off between "interference-free coexistence with PU" and "self-existence of a large number of SU". This problem is addressed further by statistically modeling probability of free channels and using it to optimize the number of SU that can be allocated. The proposed scheme outperforms the conventional sensing based dynamic spectrum allocation (DSA) in terms of reduced PU interference, lower spectrum handoff requirements and higher spectrum utilization efficiency. The predictive optimized HSMM-DSA can be used as an additional layer of intelligence for any CR device for efficient spectrum sharing. [ABSTRACT FROM AUTHOR]

This paper presents a memory-efficient receiver architecture for interleave division multiple access (IDMA). For the iterative multiuser detection, existing IDMA architectures first store all log-likelihood ratios (LLRs) into a memory in an iteration, and then despread them in the following iteration. To store new LLRs in the following iteration without overwriting the previous ones to be despread, the memory needs to be duplicated. The proposed architecture, on the other hand, despreads the LLRs on-the-fly while storing them by immediately processing one LLR per cycle. As a result, the architecture finishes despreading within one iteration and is free of the duplicate memory. Since the hardware complexity and the power consumption of an IDMA receiver are dominated by the memory usage, the proposed architecture is particularly effective in alleviating such measures. Moreover, the proposed architecture mitigates the overall latency slightly, as it is exempted from the additional cycles required to despread in the last iteration. Implementation results demonstrate that the IDMA receivers based on the proposed architecture require 57% bits in memories, occupy only 39% silicon area, and consume only 30% power on average, compared to the latest low-latency architecture. [ABSTRACT FROM AUTHOR]

For an uplink sparse code multiple access (SCMA) system, a codebook-domain superposition transmission can be applied to increase the multiplexing gain by efficient utilization of the codebooks as multiple access resources. However, the destructive collision of superposed codewords can restrict the performance improvement of the system because of the increasing interlayer interferences. In this paper, we analyze the effects of the interlayer interferences on the bit error rates, and optimize the SCMA codebooks that can mitigate the interlayer interferences. Simulation results show that the optimized codebooks can provide a noticeable gain to improve the performance of uplink SCMA systems applied with superposition transmission. [ABSTRACT FROM AUTHOR]

The rapid development of mobile Internet triggered massive data exchange among multiple sources, which then results in challenges in the efficiency of multi-user data transmission. Spatial coupling multiple access, where different users share the same resource blocks by superimposing data streams with different time offsets, has been proposed to obtain higher spectral efficiency. The optimization of the system can be carried out through for example constellation rotation or power allocation, which mitigates the interferences and distinguishes users/data streams better. The optimization aims for the maximization of the average mutual information between the transmitted data symbols and the received signal. To solve the optimization problem, we employ machine learning based methods to locate the possibly global optimal solution. Simulation results show that the optimization clearly contributes to the performance improvement of the system. [ABSTRACT FROM AUTHOR]

Recently, compressive sensing based massive multiple input multiple output (MIMO) channel estimation (CE) has attracted intensive research interest. By exploiting the structured sparsity of massive MIMO channels, it is possible to design structured sparse channel estimation (SSCE) algorithms to significantly reduce the pilot/feedback overheads in massive MIMO downlink CE. However, most existing SSCE algorithms are designed based on oversimplified channel models with restrictive assumptions, and thus perform poorly under realistic channels. In this paper, we propose a Hidden-Markov-Model (HMM) to capture the structured sparsity of multiuser massive MIMO channels. The HMM has the flexibility to model different propagation environments that occur in practice. We derive an efficient approximate message passing algorithm called Turbo-orthogonal approximate message passing (OAMP) to solve the resulting sparse CE problem with an HMM prior. The proposed Turbo-OAMP does not require knowledge of the HMM channel parameters, which is automatically learned based on the expectation maximization framework. As a result, the proposed Turbo-OAMP algorithm derived from the HMM works well for realistic channels with complicated propagation environments and unknown channel parameters. Extensive simulations verify that the proposed Turbo-OAMP can achieve significant gains over the existing SSCE algorithms under realistic channels. [ABSTRACT FROM AUTHOR]

This paper considers two possible approaches, which enable multiple pairs of users to exchange information via multiple multiantenna relays within one time-slot to save communication bandwidth in low-latency communications. The first approach is to deploy full-duplexes for both users and relays to make their simultaneous signal transmission and reception possible. In the second approach, the users use a fraction of a time slot to send their information to the relays and the relays use the remaining complementary fraction of the time slot to send the beamformed signals to the users. The inherent loop self-interference in the duplexes and inter-full-duplexing-user interference in the first approach are absent in the second approach. Under both these approaches, the joint design of the users’ power allocation and relays’ beamformers to either optimize the users’ exchange of information or maximize the energy-efficiency subject to user quality-of-service (QoS) constraints in terms of minimal rate thresholds leads to complex nonconvex optimization problems. Path-following algorithms are developed for their computational solutions. Numerical examples show the advantages of the second approach over the first approach. [ABSTRACT FROM AUTHOR]

We focus on a dual-functional multi-input-multi-output (MIMO) radar-communication (RadCom) system, where a single transmitter with multiple antennas communicates with downlink cellular users and detects radar targets simultaneously. Several design criteria are considered for minimizing the downlink multiuser interference. First, we consider both omnidirectional and directional beampattern design problems, where the closed-form globally optimal solutions are obtained. Based on the derived waveforms, we further consider weighted optimizations targeting a flexible tradeoff between radar and communications performance and introduce low-complexity algorithms. Moreover, to address the more practical constant modulus waveform design problem, we propose a branch-and-bound algorithm that obtains a globally optimal solution, and derive its worst-case complexity as function of the maximum iteration number. Finally, we assess the effectiveness of the proposed waveform design approaches via numerical results. [ABSTRACT FROM AUTHOR]

The secondary users (SUs) in cognitive radio (CR) networks exploit the underutilized radio spectrum of the primary networks. In overlay CR systems, transmit waveforms can be designed either in orthogonal frequency-division multiplexing or in multicarrier code division multiple access modulation formats by deactivating subcarriers corresponding to primary users’ frequency bands to avoid interference. Transmissions of these overlay CR waveforms are expected to be extremely wideband, occupying up to 1 GHz of bandwidth. As reception of such wideband signals requires very high Nyquist sampling rates, we propose to employ a sub-Nyquist sampling front end. The proposed sub-Nyquist sampling receiver collects as coherently as possible all the SU signals spread across the entire frequency span of interest. Our theoretical analysis and simulation results demonstrate that the proposed receiver performs very close to the Nyquist rate receiver with significantly reduced complexity. [ABSTRACT FROM AUTHOR]

We propose novel jointly optimized transceivers for multiuser multicellular networks for both the uplink and the downlink. The optimization is based on minimizing the total mean square error at each base station given that out-of-cell precoders and the cross-channel information for the weaker interferers are not known. As the transceivers are jointly optimized at the base stations, the proposed schemes do not require multiple feedback iterations between the base stations and the users; thus, significantly reducing the overhead. We also investigate the performance considering a cooperation scheme and propose optimization for noncooperative users. We show that our proposed optimized transceivers outperform the existing schemes even with imperfect channel estimations. [ABSTRACT FROM AUTHOR]

To accommodate the ever-increasing data traffic, the 5G system has adopted the enormous swathes of unlicensed spectrum at millimeter-wave band. The millimeter-wave band however exhibits orders-of-magnitude more path loss than the microwave band. The upcoming 5G system thus necessitates the use of large-scale antenna arrays to compensate for the notable path loss with beamforming gain. Nevertheless, the large number of antenna elements also poses some challenges. For example, it is impractical to assign one dedicated transceiver unit (TXRU) for each individual element and the complexity of channel estimation on spatial (antenna) domain is prohibitively high. In this paper, we design low complexity multiuser transmission on beam domain at millimeter-wave band. Specifically, we propose the beam channel set selection and user grouping schemes to significantly lower the complexity of channel estimation and precoder design by exploiting the salient feature of channel sparsity. Moreover, 2-D TXRU virtualization together with beam sweeping strategies is presented as the TXRU number is less than the number of columns of planar antenna array. Simulation results show that the proposed beam-group division 5G system can significantly reduce the complexity and keep the system throughput. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is considered as one of the candidate techniques to be implemented in 5G communication networks. In this paper, a dual-hop amplify-and-forward NOMA relaying network with partial relay selection protocol over Nakagami- m fading channels is studied. Closed-form expressions for the outage probability are derived, and also lower and upper bounds are obtained under high signal-to-noise ratio approximation. Numerical results are corroborated with Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

Streaming video is becoming the predominant type of traffic over the Internet with reports forecasting the video content to account for 82% of all traffic by 2021. With significant investment on Internet backbone, the main bottleneck remains at the edge servers (e.g., WiFi access points, small cells, etc.). In this paper, we obtain and prove the optimality of a multiuser resource allocation mechanism operating at the edge server that minimizes the probability of stalling of video streams due to buffer under-flows. Our derived policy utilizes media presentation description files of clients that are sent in compliant to dynamic adaptive streaming over HTTP protocol to be cognizant of the deadlines of each of the media file to be displayed by the clients. Our policy allocates the available channel resources to the users, in a time division manner, in the order of their deadlines. After establishing the optimality of this policy to minimize the stalling probability for a network with links associated with fixed loss rates, the utility of the algorithm is verified under realistic network conditions with detailed NS-3 simulations. [ABSTRACT FROM AUTHOR]

In this paper, the problem of transmit beam design and user scheduling is investigated for multiuser (MU) multiple-input single-output (MISO) nonorthogonal multiple access (NOMA) downlink. First, Pareto-optimal beam design is solved for two-user MISO broadcast channels (BCs) with successive interference cancelation (SIC), and certain properties of Pareto-optimal beam vectors are obtained. Based on this result, a beam design and user scheduling method is proposed for MU-MISO NOMA. In the proposed method, simultaneously served users are grouped into multiple clusters with two users in each cluster, and a hierarchical beam structure composed of zero forcing intercluster beamforming and two-user Pareto-optimal intracluster beamforming is applied. The proposed method has the ability to control the rates of strong and weak users and hence provides great flexibility to MU-MISO NOMA operation. In addition, the problem of Pareto-optimal beam design for general $M$ -user MISO BCs with SIC is solved. [ABSTRACT FROM AUTHOR]

This two-part paper considers an uplink massive device communication scenario in which a large number of devices are connected to a base station (BS), but user traffic is sporadic so that in any given coherence interval, only a subset of users is active. The objective is to quantify the cost of active user detection and channel estimation and to characterize the overall achievable rate of a grant-free two-phase access scheme in which device activity detection and channel estimation are performed jointly using pilot sequences in the first phase and data is transmitted in the second phase. In order to accommodate a large number of simultaneously transmitting devices, this paper studies an asymptotic regime where the BS is equipped with a massive number of antennas. The main contributions of Part I of this paper are as follows. First, we note that as a consequence of having a large pool of potentially active devices but limited coherence time, the pilot sequences cannot all be orthogonal. However, despite the nonorthogonality, this paper shows that in the asymptotic massive multiple-input multiple-output regime, both the missed device detection and the false alarm probabilities for activity detection can always be made to go to zero by utilizing compressed sensing techniques that exploit sparsity in the user activity pattern. Part II of this paper further characterizes the achievable rates using the proposed scheme and quantifies the cost of using nonorthogonal pilot sequences for channel estimation in achievable rates. [ABSTRACT FROM AUTHOR]

Nonorthogonal multiple access (NOMA) can improve the spectrum efficiency through reusing the power-level space by different users. Although NOMA in single-input single-output channels has been thoroughly explored, it is still underexploited in multiple-input multiple-output (MIMO) channels. Precoding design in multiuser MIMO channels with nonorthogonal transmission is a multidimensional nesting problem, it is hard to compare two matrix channels if only their power levels are considered. In this paper, we first propose a method to compare the covariance matrices of two channel matrices, and then derive a channel condition under which the linear precoding scheme can achieve the sum capacity. Considering arbitrary realizations of multiuser channels, we provide a nested precoding algorithm that can work well in highly correlated multiuser channels. Based on this idea, a specialized superposition transmission scheme between signaling and data information is proposed, where plenty of resources beneath the signaling signal are utilized to transmit data information for dedicated users, and a large amount of extra rates are achieved. In addition, space-time coding is used for signaling information and spatial-division multiplexing is used for multiuser data information. Under the constraint that signaling information should be correctly decoded at any position in the cell, we seek to maximize the sum rate of the underneath multiuser data streams. To this end, the optimal and a low-complexity simplified precoding algorithms are developed. Finally, simulation results verify the throughput improvement and the correct decoding probability of the signaling information. [ABSTRACT FROM AUTHOR]

In this paper, a joint relay-user selection (JRUS) scheme is proposed for an amplify-and-forward full-duplex (FD) relay network which includes one source node, multi-relay node and multi-user node, and the direct link between the source node and the user node is considered to convey information. Each FD relay node is energy-constrained and the simultaneous wireless information and power transfer technology is employed to harvest energy. A power splitter at each FD relay node splits the received signals into two components for energy harvesting and information processing. The implementation of the proposed JRUS scheme includes two steps: (1) the optimal user node is selected according to signal-to-noise ratio of the direct link between the source node and the user nodes; (2) the optimal energy harvesting relay node with optimal power splitting (PS) factor is picked out based on signal-to-interference-plus-noise ratio of the relaying link. The outage probability of the investigated relay network with the JRUS scheme is derived. In order to characterize the diversity order, we further present the asymptotic outage probability at high SNR. Moreover, the optimal PS factor of each relay node is calculated by minimizing the outage probability of the reconstructed relay network. Finally, numerical results demonstrate the accuracy of our performance analysis and the efficiency of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper considers on-off random access channels where the users transmit either a one or a zero to a base station or fusion center, and it is assumed that only a small fraction of users are active during any channel use. Under these assumptions, the problem of identifying the active users reduces to that of recovering a sparse binary vector from noisy random linear measurements. A hierarchical Bayesian approach is proposed in this paper to recover the set of active users. A fast approximate Bayesian inference based on Variational Bayes (VB) is then developed. Extensive simulation results are then provided to compare the performance of the proposed VB based Bayesian MUD approach to sparse estimation techniques such as OMP and LASSO. It is observed that the proposed approach is robust to variations in noise as well as sparsity levels. Further, for a given BER performance, the proposed approach requires substantially smaller dimensional codes as compared to OMP and LASSO, thus improving the spectral efficiency. [ABSTRACT FROM AUTHOR]

Nonorthogonal multiple access (NOMA) is a promising technique which outperforms the traditional multiple access schemes in many aspects. It uses superposition coding (SC) to share the available resources among the users and adopts successive interference cancelation (SIC) for multiuser detection (MUD). Detection is performed in power domain where fairness can be supported through appropriate power allocation. Since power domain NOMA utilizes SC at the transmitter and SIC at the receiver, users cannot achieve equal rates and experience higher interference. In this paper, a novel NOMA scheme is proposed for multinumerology orthogonal frequency division multiplexing system, that is, different subcarrier spacings. The scheme uses the nature of mixed numerology systems to reduce the constraints associated with the MUD operation. This scheme not only enhances the fairness among the users but improves the bit error rate performance as well. Although the proposed scheme is less spectrally efficient than conventional NOMA schemes, it is still more spectrally efficient than orthogonal multiple access schemes. [ABSTRACT FROM AUTHOR]

This paper considers an uplink multiuser multiple-input-multiple-output (MIMO) system with low-resolution analog-to-digital converters (ADCs), in which K users equipped with a single-antenna communicate with one base station (BS) with N_{\mathrm{ r}} antennas. In this system, we present a novel multiuser MIMO detection framework inspired by coding theory. The key idea of the proposed framework is to create a code {\mathcal C} of length 2N\mathrm{ r} over a spatial domain. This code is constructed by an auto-encoding function that is completely described by a channel transformation followed by a quantization function of the ADCs for a fixed input constellation set. Using the proposed framework, we present a novel weighted minimum distance decoding (wMDD) that achieves the optimal detection performance by appropriately exploiting unequal channel reliabilities. In addition, we show that bit error rate exponentially decreases with the minimum distance of the code {\mathcal C} , which plays a similar role with a condition number in conventional MIMO systems. Furthermore, we develop the communication method that uses the wMDD when the explicit channel state information is not available at the BS. Finally, numerical results are provided to verify the superiority of the proposed method. [ABSTRACT FROM PUBLISHER]

MANET is a self-configuring network, in which topology is dynamic. These nodes are struggling to cope with the normal effect of radio communication channels, multi-user interference, multi-path fading etc. The design of an optimum routing protocol for MANET is highly difficult. To determine the connectivity of network organizations, there is a need for an efficient algorithm link scheduling, and routing in such dynamic scenarios, becomes very important. The efficiency of a routing algorithm depends on the proficient and winning route computation. Usually, the shortest path algorithm is a successful method to calculate the optimal way in static networks. But this idea is not possible in MANET platform. There are many factors which can be considered for routing. Multihop paths are used in MANET for interconnecting the nodes. All the nodes are present in the network which are used for path construction for delivering a packet from source to destination node. [ABSTRACT FROM AUTHOR]

Summary: In recent years, the need for increased satellite throughput has been tackled by extending the number of satellite beams thus allowing a higher spectrum reuse and peak throughput. However, the satellite antenna size and the number of simultaneous beams that can be generated onboard over a given coverage region cannot grow beyond certain limits because of payload accommodation constraints. The next step being pursued to increase the system throughput resides in extending the frequency reuse among the loaded beams and to mitigate the effects of the increased co‐channel interference through more advanced digital signal processing. This can be achieved in 2 different ways. The first one, which received a large attention in recent years, is to centrally mitigate the multibeam channel cross talk by exploiting precoding techniques at the gateway. The second approach, less investigated in the past, is to put in place decentralized multiuser detection (MUD) at the user terminal side. The precoding approach has the advantage of concentrating the extra processing complexity at the gateway, but it requires nonstandard payloads or accurate payload calibration techniques and periodic channel estimation reporting from the user terminal. Instead, the decentralized approach can operate in combination with existing payloads and does not require any terminal's periodic channel estimate reporting to the gateway. Only the signal‐to‐noise plus interference variations due to possible fading as for conventional adaptive coding and modulation shall be reported. One of the main barriers to the decentralized MUD approach so far was the demodulator complexity. Some simplified approach for conventional frequency/time division multiplexing schemes has been recently published, and its applicability to the forward link investigated. In this paper, we investigate the possible advantages deriving from the adoption of direct‐sequence code division multiplexing associated with affordable complexity of the MUD at the user terminal side. It is shown that the proposed MUD scheme can be practically implemented and provides sizeable advantages compared to current state‐of‐the‐art when the traffic is not evenly distributed among the beams, ie, when a subset of beams has a higher load than the others. [ABSTRACT FROM AUTHOR]

Bandwidth and energy constraints of underwater wireless sensors networks necessitate an efficient data transmission between sensor nodes and the fusion center. This paper considers the data gathering underwater networks for monitoring oceanic environmental elements (e.g. temperature, salinity) and only a portion of measurements from sensors allows for oceanic information map reconstruction under compressed sensing (CS) theory. By utilizing the spatial sparsity of active sensors’ data, we introduce an activity and data detection based on CS at the receiver side resulting in an efficient data communication by avoiding the necessity of conveying identity information. For an interleave division multiple access (IDMA) sporadic transmission, CS-CBC detection that combines the benefits from chip-by-chip (CBC) multi-user detection and CS detection is proposed. Further, by successively exploring the sparsity of sensor data in spatial and frequency domain, we propose a novel efficient data gathering scheme named Dual-domain compressed sensing (DCS). Simulation results validate the effectiveness of the proposed scheme compared to IDMA-CS scheme and an optimal sensing probability problem related to minimum reconstruction error is explored. [ABSTRACT FROM AUTHOR]

In this paper, the feasibility of a new downlink transmission mode in massive multi-input multi-output (MIMO) systems is investigated with two types of users, i.e., the users with only statistical channel state information (CSI) and the users with imperfect instantaneous CSI. The problem of downlink precoding design with mixed utilization of statistical and imperfect instantaneous CSI is addressed. We first theoretically analyze the impact of the mutual interference between the two types of users on their achievable rate. Then, considering the mutual interference suppression, we propose an extended zero forcing and an extended maximum ratio transmission precoding methods to minimize the total transmit power of base station and to maximize the received signal power of users, respectively. Thanks to the exploitation of statistical CSI, pilot-based channel estimation is avoided enabling more active users, higher system sum rate, and shorter transmission delay. Finally, simulations are performed to validate the accuracy of the theoretical analysis and the advantages of the proposed precoding methods. [ABSTRACT FROM PUBLISHER]

To cope with the interference problem in three-cell wireless relay systems, this paper proposes two schemes that perform interference suppression and multiuser detection. The proposed schemes do not require channel state information (CSI) feedback, and their computational complexity is much less than that of the maximum likelihood detection (MLD), which is considered in the optimal detection scheme. Of the two proposed schemes, the minimum mean-square error (MMSE)-based scheme estimates the weight coefficients for the interference suppression under the MMSE criterion. The other proposed scheme, the recursive least squares (RLS)-based scheme, directly estimates the weight coefficients using the RLS algorithm. The RLS-based scheme only requires two preamble sequences, whereas both the MMSE-based schemes and the MLD require the knowledge of all the three preamble sequences. Therefore, the RLS-based scheme can be considered more feasible. Moreover, computer simulations results and theoretical average bit error rate (BER) upper bounds of orthogonal frequency-division multiplexing transmission under three-cell and frequency-selective fading conditions were provided. It was observed that simulation results are consistent with theoretical upper bounds and that the RLS-based scheme achieves a BER performance that is identical to that of the MMSE-based scheme with perfect CSI while requiring much less computational complexity than the MLD. [ABSTRACT FROM AUTHOR]

Multiuser detection (MUD) and channel estimation techniques in space‐division multiple‐access aided orthogonal frequency‐division multiplexing systems recently has received intensive interest in receiver design technologies. The maximum likelihood (ML) MUD that provides optimal performance has the cost of a dramatically increased computational complexity. The minimum mean‐squared error (MMSE) MUD exhibits poor performance, although it achieves lower computational complexity. With almost the same complexity, an MMSE with successive interference cancellation (SIC) scheme achieves a better bit error rate performance than a linear MMSE multiuser detector. In this paper, hybrid ML‐MMSE with SIC adaptive multiuser detection based on the joint channel estimation method is suggested for signal detection. The simulation results show that the proposed method achieves good performance close to the optimal ML performance at low SNR values and a low computational complexity at high SNR values. [ABSTRACT FROM AUTHOR]

Accurate placement of pilot tones has been a crucial task in multicarrier transmission technologies since there is a strong relation between pilot positions and channel estimation performance. Therefore, the firey algorithm (FA) is proposed for achieving the optimal pilot distribution by optimizing the pilot positions in order to minimize the estimation errors of the least squares algorithm employed in orthogonal frequency division multiplexing-interleave division multiple access (OFDM-IDMA) systems. According to the simulation results, our proposed FA-based pilot optimizer provides a great performance increase in OFDM-IDMA systems by obtaining the most appropriate pilot distribution pattern among the considered pilot placement strategies. The upper bound of mean square error (MSE) is used as the fitness function in the optimization process for avoiding the matrix inversion operation that is needed when calculating MSE itself. [ABSTRACT FROM AUTHOR]

In this article, we present a holistic overview of the agile multi-user scheduling functionality in 5G. An E2E perspective is given, including the enhanced QoS architecture that comes with 5G, and the large number of scheduling related options from the new access stratum sub-layer, MAC, and PHY layer. A survey of the 5G design agreements from the recently concluded 5G Study in 3GPP is presented, and it is explained how to best utilize all these new degrees of freedom to arrive at an agile scheduling design that offers superior E2E performance for a variety of services with highly diverse QoS requirements. Enhancements to ensure efficient implementation of the 5G scheduler for different network architectures are outlined. Finally, state-of-the-art system level performance results are presented, showing the ability to efficiently multiplex services with highly diverse QoS requirements. [ABSTRACT FROM AUTHOR]

Simultaneous wireless information and power transfer (SWIPT) is a promising technique to transfer information and energy signals at the same time and frequency utilizing the multi-input multi-output (MIMO) beamforming. In this correspondence, the SWIPT MIMO technique is realized in the multicell cooperative transmission environment, namely, network-MIMO where the signals from different base-stations (BSs) to all the mobile users can be jointly designed based on the perfect knowledge of the downlink channels and transmit messages. To develop an efficient precoding matrix, we adopt the weighted minimum mean squared error criterion that can be generally applied to the sum-utility maximization of each receiver's information rate. In the SWIPT network-MIMO, a number of constraints arise including the power constraint at each BS, namely, the per-BS power constraints and the energy constraint at the energy harvesting users, which makes the problem challenging. A main contribution of the paper is to propose a simple bisection-based algorithm that finds a solution. The efficiency of the proposed algorithm is verified via computer simulation results. [ABSTRACT FROM AUTHOR]