In this paper, we investigate maximum likelihood (ML) time delay (TD) and carrier frequency offset (CFO) synchronization in multi-node decode-and-forward (DF) cooperative relaying systems operating over time-varying channels (TVCs). This new synchronization scheme is embedded into a distributed multiple input multiple output (MIMO)-relay beamforming transceiver structure to avoid the drawbacks of multidimensional ML estimation at the destination and to minimize the overhead cost. The new technique can be jointly implemented with any Doppler spread estimator in an iterative scheme using a time-constant channel (TCC) based synchronization method at the initialization step. The resulting TD and CFO estimates along with the channel estimates are then fed into a distributed MIMO-relay beamforming transceiver of K single-antenna nodes, for pre-compensation at each node of the transmitted signals, to ensure constructive maximum ratio combining (MRC) at the destination. Simulation results show significant synchronization accuracy improvement over previous distributed multi-node synchronization techniques assuming TCCs. The latter translates into noticeable gains in terms of useful link-level throughput, more so at higher Doppler or with more relaying nodes.

In this paper, we investigate maximum likelihood (ML) time delay (TD) and carrier frequency offset (CFO) synchronization in multi-node decode-and-forward cooperative relaying systems operating over time-varying channels. This new synchronization scheme is embedded into a distributed multiple input multiple output (MIMO)-relay beamforming transceiver structure to avoid the drawbacks of multidimensional ML estimation at the destination and to minimize the overhead cost. By accounting for a perfect Doppler spread value, the new synchronization solution delivers accurate TD and CFO estimates. For real-world operation, however, this new technique can be jointly implemented with any Doppler spread estimator in a new iterative scheme using a time-constant channel (TCC)-based synchronization method at the initialization step. The resulting TD and CFO estimates along with the channel estimates are then fed into a distributed MIMO-relay beamforming transceiver of K single-antenna nodes, for pre-compensation at each node of the transmitted signals, to ensure constructive maximum ratio combining (MRC) at the destination. Simulation results show significant synchronization accuracy improvement over previous distributed multi-node synchronization techniques assuming TCCs. The latter translates into noticeable gains in terms of useful link-level throughput, more so at higher Doppler or with more relaying nodes.

User-centric wireless access virtualization (WAV) allows each user to be served by a set of carefully selected transmission points (TPs) forming a user-specific virtual base station (uVBS) adapted to its environment and quality-of-service (QoS) requirement. In this way, this new concept breaks away from the conventional cell-centric architecture to provide boundaryless communications in future fifth-generation (5G) networks. This fundamental structural 5G evolution and the ultra-dense multi-tier heterogeneous context foreseen in such networks require an inevitable rethinking of efficient scalable TP clustering. As such, this paper proposes three innovative low-cost clustering approaches that enable the user-centric WAV and provide dynamic, adaptive, and overlapping TP clusters while requiring not only negligible overhead cost but also minimum signaling changes at both network and user sides. Contrary to existing clustering techniques, the new ones we propose better leverage the 5G features such as extreme densification and massive connectivity as well as new concepts such as millimeter wave (mmWave) spectrum and massive multiple-input-multiple-output (MIMO). The simulations show that they may achieve until 154% and 282% of throughput and coverage gains, respectively. Furthermore, these approaches are flexible enough to be adapted to different network dimensions (i.e., space and time), thereby paving the way for achieving the dramatic performance improvements required by the 5G networks to cope with the upcoming mobile data deluge.

In this paper, we investigate maximum likelihood (ML) time delay (TD) and carrier frequency offset (CFO) synchronization (i.e., estimation and pre- compensation) in decode-and-forward (DF) cooperative systems operating over time-varying channels (TVCs). The new technique is embedded at each relay node in order to avoid the drawbacks of multidimensional ML estimation at the destination and to minimize the overhead cost. By accounting for a perfect Doppler spread value, the new synchronization solution delivers accurate TD and CFO estimates at each relay. The resulting TD and CFO estimates along with the channel estimates are then exploited by the MIMO relay for precompensation at each node of the distributed transmit beamforming signals to ensure constructive maximum ratio combining (MRC) at the destination. Simulation results show significant synchronization accuracy improvement over previous distributed multi-node synchronization techniques assuming time-constant channels (TCCs). The latter translates into noticeable gains in terms of useful (i.e., after accounting for incurred overhead) link-level throughput, more so at higher Doppler.

This paper develops an innovative scalable and low-cost QoS-based user equipment (UE) virtualization (UEV) scheme that capitalizes on the massive connectivity and the enhanced resources of the new UE generation in terms of connectivity, computing, battery/power, etc. Exploiting the need/excess duality and the heterogeneity in such resources at the UE plan, we form virtual UEs (VUE)s, dynamically, owing to a carefully-designed time-adjusting scheme for the selection of the proper cooperative UE sets. The new UEV scheme is able to adapt to each target UE (TUE) environment, meet its demands, and scale with its needs, offers a reliable and efficient yet low-cost inter-UE cooperation, reduces the overhead and power consumption with respect to conventional approaches, and substantially reduces the number of communication links and, hence, incurs much less interference. System-level simulation results show that the proposed QoS-based UEV scheme largely outperforms the “dummy UEs” approach.

The fifth generation of cellular wireless networks known as 5G is based on user-centric non-cellular concept where the users are surrounded by many network nodes cooperating to serve the users providing a “cell-center” experience throughout the network. Traditional multi point cooperation techniques often rely on centralized coordination and require different and often stringent requirement on the central controller, backhaul capacity and overall network synchronization. A novel two tiered, open loop and distributed cooperation technique is proposed in this paper where the lower tier with fixed or slowly changing parameters and preferably using SCMA provide a ubiquitous performance to mobile users and users exposed to multiple network nodes, while the higher tier provides service to the users close to the network nodes and maintain the overall network throughput. Users scheduled by the lower tier signaling use joint detection techniques from multiple network nodes. Other users scheduled to the higher tier jointly decode the lower tier signal from one or multiple network nodes before proceeding with the detection of their intended signal. The proposed algorithm is based on distributed scheduling and imposes limited requirements on the central controller and backhaul capacity and does not require stringent network time and frequency synchronization among network nodes. Unlike traditional cooperation techniques, the proposed method is open loop and requires very limited feedback and signaling overhead. Performance evaluations show that the proposed technique provides significant network coverage enhancement especially for high speed mobile users.

Sparse Code Multiple Access (SCMA), a non-orthogonal multiple access scheme, has been introduced as a key 5G technology to improve spectral efficiency. In this work, we propose SCMA to enable open-loop coordinated multipoint (CoMP) joint transmission (JT). The scheme combines CoMP techniques with multi-user SCMA (MU-SCMA) in downlink. This scheme provides open-loop user multiplexing and JT in power and code domains, with robustness to mobility and low overhead of channel state information (CSI) acquisition. The combined scheme is called MU-SCMA- CoMP, in which SCMA layers and transmit power of multiple transmit points (TPs) are shared among multiple users while a user may receive multiple SCMA layers from multiple TPs within a CoMP cluster. The benefits of the proposed scheme includes: i) drastic overhead reduction of CSI acquisition, ii) significant increase in throughput and coverage, and iii) robustness to channel aging. Various algorithms of MU-SCMA-CoMP are presented, including the detection strategy, power sharing optimization, and scheduling. System level evaluation shows that the proposed schemes provide significant throughput and coverage gains over OFDMA for both pedestrian and vehicular users.

This work presents the channel estimation for Generalized Frequency Division Multiplexing (GFDM). GFDM can be considered as a filtered bank multicarrier scheme, where a spectrally-contained pulse shaping is applied over each subcarrier to reduce out of band radiation (OOB). However, due to pulse shaping, subcarriers in GFDM are no longer orthogonal and there is inherent interference. Due to such interference, the channel estimation for GFDM is not trivial. In this work, two channel estimation methods for GFDM are proposed, 1) Pilot Interference Cancellation (Pilot-IC) where interference is pre-canceled only at pilot symbols, 2) Transmitter IC (Tx-IC) where interference is pre-cancelled at both data and pilot symbols. With scattered pilots over frequency and time grid, this allows frequency selective and time varying fading channels to be estimated, with reduced overhead. The simulation results show that these two methods can provide the same MSE performance. Moreover, the Pilot-IC pairing with a Zero Forcing (ZF) receiver, and the Tx-IC pairing with a simple Matched Filter (MF) receiver, also provide the same BER performance. Hence, it is possible to cancel the interference either at the transmitter or the receiver.

Phase ambiguities affect any joint decoding and channel estimation algorithm over fading channels, making codes that mitigate this problem of considerable interest. This work presents a design that transforms a Space-Time Trellis Code (STTC), prone to carrier phase ambiguities, into a Phase Ambiguity Diminishing STTC (PAD-STTC) that is robust to such impairment. A PAD-STTC can be considered as a Multiple STTC (MSTTC) with special constellation mappings. The design criteria for these mappings are developed in this work by trading among the PAD property, diversity, and coding gain. Two PAD-STTC structures termed PAD1-STTC and PAD2-STTC are proposed, where PAD2-STTC increases the number of states over the constituent STTC. Computer simulation results indicate that PAD-STTCs can solve the phase ambiguity problem and provide a larger diversity gain than the constituent STTC over high Doppler fading channels. Moreover, with the same constituent STTC, the PAD2-STTC outperforms the PAD1-STTC at the expense of increased complexity.

This work considers a joint channel estimation and data detection technique for Multiple Space-Time Trellis Codes (MSTTCs) operating over unknown time-varying channels with large Doppler spread. We propose an algorithm, called Doppler Adaptive Smoothed Data Detection and Kalman Estimation (DA-SDD-KE), that jointly detects data and estimates the channel as well as the time-varying Doppler. In this scheme, an Adaptive Kalman Predictor (AKP) consisting of a KP and a covariance-based Doppler estimator is incorporated into a Per-Survivor Processing (PSP)-based algorithm that utilizes the past, present and future received symbols for smoothed data detection. For comparison purposes, we also develop a Doppler Adaptive version of the Delayed Mixture Kalman Filtering (DMKF) technique, referred to as DA-DMKF, where the adaptive estimations of the channel and the Doppler shift are based on sequences of importance samples. Moreover, we propose a model for generating a Rayleigh fading process with time-varying Doppler using the sum of sinusoids method. The performance of the DA-SDD-KE and DA-DMKF algorithms over channels with constant, linear and quadratic Doppler functions is evaluated using computer simulations, revealing that the DA-SDD-KE algorithm performs well for all considered Doppler functions, and provides a considerably gain over the DA-DMKF algorithm.

This work presents a joint channel estimation and data detection algorithm over high Doppler fading channels, for space-time trellis codes (STTCs) having more than one code vector per trellis branch. Such codes are referred to as multiple STTCs (MSTTCs). This algorithm belongs to the per-survivor processing (PSP) family, where a survivor sequence associated with a trellis state can be considered as the data sequence aiding per-path channel estimation in a joint detection and estimation procedure.We propose a smoothed data detection technique that utilizes past, present and future received symbols to increase the probability of the survivor being a correct data sequence. A symbol by symbol maximum a posteriori probability (MAP) criterion, with a fixed delay D, is employed for data detection, combined with a Kalman Predictor (KP) for channel estimation. This novel algorithm, called smoothed data detection and Kalman estimation (SDD-KE), provides a significant performance gain when D > 0 over D = 0, with a linear increase in complexity when D increases. Comparison with the delayed mixture Kalman filtering (D-MKF) technique shows that the SDD-KE algorithm provides important performance and complexity advantages.

This work generalizes the "MAP-PSP" algorithm for joint channel estimation and data detection to space-time trellis codes (STTCs) having more than one code vector per trellis branch. The latter codes are referred to as multiple STTCs (MSTTCs). We consider fast fading multiple transmit antenna channels, and investigate the effect of spatial correlation on the performance of this MAP-PSP algorithm where no knowledge of spatial correlation is required. Simulation results show that a significant performance gain is obtained by using this MAP-PSP algorithm with delay D = 4 compared to that with D = 0, that is robust to spatial correlation effects.

This work considers joint channel estimation and data detection of space-time trellis codes (STTCs) over time-varying flat fading channels with unknown normalized Doppler shift,fdT. An algorithm based on an improved per survivor processing (PSP) technique, where the survivor branch decision is formulated in the symbol by symbol maximum a posteriori probability (MAP) framework, is presented. An adaptive Kalman predictor (AKP) is employed to track the fading channel andfdT. In the AKP, the sequence of channel estimates produced by the Kalman predictor (KP) is utilized forfdT estimation. In turn, the estimatedfdT is used in the KP for channel tracking. This coupled process adaptively estimates both the channel coefficients and Doppler shift. The performance of STTC using the proposed receiver is robust againstfdT mismatch, and it is within 0.3 dB from the knownfdT case.

This paper considers the performance analysis of space-time trellis codes over quasistatic Rayleigh fading channels. We present three methods to calculate the frame error rate (FER) of such codes. The first is based on the union bound using the exact pair wise error probability (PEP). The second method is a generalization of the PEP-based union bound, employing the exact FER of orthogonal subcodes. The third method uses the technique of limiting the conditional union bound before averaging over channel coefficients. Numerical results show that employing the exact orthogonal subcode FER improves the union bound significantly. Limiting before averaging, however, provides the closest approximation to FER among these three methods.

Block turbo codes with trellis-based decoding are proposed for use in cell-based satellite communication. Shortened Reed-Muller (RM) codes are used as the component codes because their minimal trellis is known. Simulation results for RM turbo codes and shortened RM turbo codes are presented over additive white Gaussian noise and Rayleigh fading channels. The performance of the shortened codes with different shortening patterns are shown. In some cases, the codes have the unequal error protection property, useful in asynchronous transfer mode cell formatting. In order to test the suitability of the proposed coding scheme from a practical point of view, the effect of channel impairments, including channel signal-to-noise ratio mismatch and carrier phase offset, are investigated.

In this paper, block turbo codes (BTCs) with trellis-based decoding are proposed for use in digital video broadcasting-return channel via satellite (DVB-RCS) for ATM transmission. Reed-Muller (RM) codes are used as the component codes. The BTCs are shortened in order to accommodate a satellite ATM cell. It is shown that different shortening patterns can be used. In some cases, the codes have unequal error protection (UEP) property. In order to test the suitability of the proposed coding scheme from a practical point of view, the effect of channel impairment, channel signal to noise ratio (SNR) mismatch, is investigated. Simulation results for RM-turbo codes and shortened turbo codes are presented over AWGN and Rayleigh-fading channels. The performance of the shortened codes with different shortening patterns and with the effect of channel SNR mismatch are shown.