According to the recent 3GPP decisions on 6G air interface, orthogonal frequency-division multiplexing (OFDM)-based waveforms are the primary candidates for future integrated sensing and communication (ISAC) systems. In this paper, we consider a monostatic sensing scenario in which OFDM is used for the downlink and its reflected echo signal is used for sensing. OFDM and discrete Fourier transform-spread OFDM (DFT-s-OFDM) are the options for uplink transmission. When OFDM is used in the uplink, the power difference between this signal and the echo signal leads to a power-domain non-orthogonal multiple access (PD-NOMA) scenario. In contrast, adopting DFT-s-OFDM as uplink signal enables a waveform-domain NOMA(WD-NOMA). Affine frequency-division multiplexing (AFDM) and orthogonal time frequency space (OTFS) have been proven to be DFT-s-OFDM based waveforms. This work focuses on such a WD-NOMA system, where AFDM or OTFS is used as uplink waveform and OFDM is employed for downlink transmission and sensing. We show that the OFDM signal exhibits additive white Gaussian noise (AWGN)-like behavior in the affine domain, allowing it to be modeled as white noise in uplink symbol detection. To enable accurate data detection performance, an AFDM frame design and a noise power estimation (NPE) method are developed. Furthermore, a two-dimensional orthogonal matching pursuit (2D-OMP) algorithm is applied for sensing by iteratively identifying delay-Doppler components of each target. Simulation results demonstrate that the WD-NOMA ISAC system, employing either AFDM or OTFS, outperforms the PD-NOMA ISAC system that uses only the OFDM waveform in terms of bit error rate (BER) performance. Furthermore, the proposed NPE method yields additional improvements in BER.

Delay-Doppler (DD) signal processing has emerged as a powerful tool for analyzing multipath and time-varying channel effects. Due to the inherent sparsity of the wireless channel in the DD domain, compressed sensing (CS) based techniques, such as orthogonal matching pursuit (OMP), are commonly used for channel estimation. However, many of these methods assume integer Doppler shifts, which can lead to performance degradation in the presence of fractional Doppler. In this paper, we propose a windowed dictionary design technique while we develop a delay-aware orthogonal matching pursuit (DA-OMP) algorithm that mitigates the impact of fractional Doppler shifts on DD domain channel estimation. First, we apply receiver windowing to reduce the correlation between the columns of our proposed dictionary matrix. Second, we introduce a delay-aware interference block to quantify the interference caused by fractional Doppler. This approach removes the need for a predetermined stopping criterion, which is typically based on the number of propagation paths, in conventional OMP algorithm. Our simulation results confirm the effective performance of our proposed DA-OMP algorithm using the proposed windowed dictionary in terms of normalized mean square error (NMSE) of the channel estimate. In particular, our proposed DA-OMP algorithm demonstrates substantial gains compared to standard OMP algorithm in terms of channel estimation NMSE with and without windowed dictionary.

In this paper, we propose a novel network architecture where two types of aerial infrastructures together with a ground station provide connectivity to a remote area. A high altitude platform station (HAPS) is equipped with reconfigurable intelligent surface (RIS), called HAPS-RIS, to be exploited to assist the unmanned aerial vehicle (UAV)-based wireless networks. A key challenge in such networks is the restricted number of UAVs, which limits full coverage and leaves some users unsupported. To tackle this issue, we propose a hierarchical bilevel optimization framework including a leader and a follower problem. The users served by HAPS-RIS are in a zone called the HAPS-RIS zone and the users served by the UAVs are in another zone called the UAV zone. In the leader problem, the goal is to establish the zone boundary and practical RIS phase shift design that maximizes the number of users covered by HAPS-RIS while ensuring that users in this zone meet their rate requirements. This is achieved through our proposed practical relaxation method and the proposed dynamic radius-based zone association with RIS clustering (DyRaZARC) technique. The follower problem focuses on minimizing the number of UAVs required, ensuring that the rate requirements of the users in the UAV zone are met. This is addressed through our proposed novel geometry-informed machine learning method, called k-means adaptive dynamic UAV selection (KADUS) technique. Our study reveals that increasing the number of RIS elements significantly decreases the number of required UAVs.

In this paper, we propose time and frequency synchronization techniques for the uplink of multiuser orthogonal time frequency space (MU-OTFS) in high-mobility scenarios. We introduce a spectrally efficient and practical pilot pattern where each user utilizes a pilot with a cyclic prefix (PCP) within a shared pilot region on the delay-Doppler plane. At the receiver, a bank of filters is deployed to separate the users' signals and accurately estimate their timing offsets (TOs) and carrier frequency offsets (CFOs). Our technique employs a threshold-based approach that provides precise TO estimates. Our proposed CFO estimation technique reduces the multi-dimensional maximum likelihood (ML) search problem into multiple one-dimensional search problems. Furthermore, we apply the Chebyshev polynomials of the first kind basis expansion model (CPF-BEM) to effectively handle the time-variations of the channel in obtaining the CFO estimates for all the users. Finally, we numerically investigate the error performance of our proposed synchronization technique in high mobility scenarios for the MU-OTFS uplink. Our simulation results confirm the efficacy of the proposed technique in estimating the TOs and CFOs which also leads to an improved channel estimation performance.

In this paper, we explore the integration of two groundbreaking technologies, reconfigurable intelligent surfaces (RISs) and orthogonal time frequency space (OTFS) modulation, with a focus on their use in multicast communications to improve high-speed wireless connectivity. We introduce a phase shift design algorithm for RIS-assisted OTFS systems to maximize the channel gain in the presence of both delay and Doppler spread. Furthermore, we propose a method that utilizes the majorization-minimization (MM) algorithm to jointly optimize beamforming and adjust the phase shifts of RIS elements in a multicast scenario. We validate the effectiveness of the proposed algorithms by numerical simulations. The results demonstrate significant performance improvements over existing benchmark approaches.

Orthogonal time frequency space (OTFS) is a strong candidate waveform for sixth generation wireless communication networks (6G), which can effectively handle time varying wireless channels. In this paper, we analyze the effect of fractional delay in delay Doppler (DD) domain multiplexing techniques. We develop a vector-matrix input-output relationship for the DD domain data transmission system by incorporating the effective pulse shaping filter between the transmitter and receiver along with the channel. Using this input-output relationship, we analyze the effect of the pulse shaping filter on the channel estimation and BER performance in the presence of fractional delay and uncompensated fractional timing offset (TO). For the first time, we propose the use of time-frequency localized (TFL) pulse shaping for the OTFS waveform to overcome the interference due to fractional delays. We show that our proposed TFL-OTFS outperforms the widely used raised cosine pulse-shaped OTFS (RC-OTFS) in the presence of fractional delays. Additionally, TFL-OTFS also shows very high robustness against uncompensated fractional TO, compared to RC-OTFS.

This paper proposes a novel modulation technique called globally filtered orthogonal time frequency space (GFOTFS) which integrates single-carrier frequency division multiple access (SC-FDMA)-based delay-Doppler representation with universal filtered multi-carrier (UFMC) modulation. Our proposed technique first arranges the frequency-Doppler bins of an orthogonal time frequency space (OTFS) frame in adjacency using SC-FDMA and then applies universal filtering to the neighboring signals to mitigate inter-Doppler interference (IDI). By employing this approach, GF-OTFS achieves superior spectral containment and effectively mitigates interference caused by Doppler shifts in dynamic, time-varying channels. This paper also presents a detailed mathematical formulation of the proposed modulation technique. Furthermore, a comprehensive performance evaluation is conducted, comparing our GF-OTFS approach to state-of-the-art techniques, including Doppler-resilient UFMC (DR-UFMC) and receiver windowed OTFS (RW-OTFS). Key performance metrics, such as bit error rate (BER) and out-of-band (OOB) emissions, as well as the Doppler spread reduction are analyzed to assess the effectiveness of each approach. The results indicate that our proposed technique achieves comparable BER performance while significantly improving spectral containment.

The primary objective of this paper is to establish a generalized framework for pulse-shaping on the delay-Doppler plane. To this end, we classify delay-Doppler pulse-shaping techniques into two types, namely, circular and linear pulse-shaping. This paves the way towards the development of a generalized pulse-shaping framework. Our generalized framework provides the opportunity to compare different pulse-shaping techniques under the same umbrella while bringing new insights into their properties. In particular, our derivations based on this framework reveal that the recently emerged waveform orthogonal delay-Doppler multiplexing (ODDM) is a linear pulse-shaping technique. By presenting ODDM under our generalized framework, we clearly explain the observed staircase behavior of its spectrum which has not been previously reported in the literature. Another contribution of this paper is the proposal of a simple out-of-band (OOB) emission reduction technique by inserting a small number of zero-guard (ZG) symbols along the delay dimension of the circularly pulse-shaped signals. Additionally, inserting the zero-guards improves the bit-error-rate (BER) performance of both circular and linear pulse-shaping techniques. Finally, our simulation results confirm the validity of our mathematical derivations, claims and the effectiveness of the ZGs in OOB reduction and BER performance improvement.

In the existing literature on joint timing and frequency synchronization of orthogonal time frequency space modulation (OTFS), practically infeasible impulse pilot with large peak-to-average power ratio (PAPR) is deployed. Hence, in this paper, we propose a timing offset (TO) and carrier frequency offset (CFO) estimation for OTFS over a linear time-varying (LTV) channel, using a low PAPR pilot structure. The proposed technique utilizes the recently proposed practically feasible pilot structure with a cyclic prefix (PCP). We exploit the periodic properties of PCP in both delay and time domains to find the starting point of each OTFS block. Furthermore, we propose a two-stage CFO estimation technique with over an order of magnitude higher estimation accuracy than the existing estimator using the impulse pilot. In the first stage, a coarse CFO estimate is obtained which is refined in the second stage, through our proposed maximum likelihood (ML) based approach. The proposed ML-based approach deploys the generalized complex exponential basis expansion model (GCE-BEM) to capture the time variations of the channel, absorb them into the pilot and provide an accurate CFO estimate. Since our proposed synchronization technique utilizes the same pilot deployed for channel estimation, it does not require any additional overhead. Finally, we evaluate the performance of our proposed synchronization technique through simulations. We also compare and show the superior performance of our proposed technique to the only other existing joint TO and CFO estimation method in OTFS literature.

The widely used embedded impulse pilot for channel estimation of orthogonal time frequency space modulation (OTFS) has a prohibitively large peak to average power ratio (PAPR). Hence, in this paper, we propose a novel embedded pilot with cyclic prefix (PCP) that has a significantly reduced PAPR compared to the impulse pilot. This is achieved by spreading the pilot power along the delay dimension using a constant amplitude Zadoff-Chu (ZC) sequence with a cyclic prefix (CP). We analytically derive upper bound PAPR expressions for the impulse pilot and the proposed PCP. Together with our numerical results, these upper bounds attest the significant PAPR improvement that is achieved by PCP. We also develop a two-stage channel estimation technique with a superior performance to the threshold-based channel estimation for the impulse pilot. At the first stage, the channel is estimated by a linear estimator under the assumption of the channel being locally linear time invariant over each time-slot within the OTFS block. Taking advantage of the benefits that are offered by the CP in our proposed pilot structure, we develop a low complexity least squares based estimator for implementation of the first stage. At the second stage, we use the channel estimate from the first stage and the generalized complex exponential basis expansion model (GCE-BEM) to accurately estimate the full channel. Finally, we numerically analyse and show the superior estimation performance of our proposed channel estimator for PCP to the threshold-based estimator for the impulse pilot.

Current multiple access technologies, Orthogonal Multiple Access (OMA) and Non-Orthogonal Multiple Access (NOMA) alone cannot satisfy 6G requirements and provide the connectivity to future networks. Hence, in this work, we propose an Adaptive NOMA-OMA (A-NOMA) that can benefit from interchanging multiple access technologies enhancing the Spectral Efficiency (SE). To turn feasible the interchange of transmission techniques, we model a spectrum sharing problem to exploiting the OMA-NOMA trade-off. We propose an architecture to the total spectral efficiency. Simulations resulted on an enhanced SE and provided more than 20% compared to NOMA SE and over 50% with OMA SE.

Orthogonal time frequency space (OTFS) modulation has recently emerged as a potential 6G candidate waveform which provides improved performance in high-mobility scenarios. In this paper we investigate the combination of OTFS with non-orthogonal multiple access (NOMA). Existing equalization and detection methods for OTFS-NOMA, such as minimum-mean-squared error with successive interference cancellation (MMSE-SIC), suffer from poor performance. Additionally, existing iterative methods for single-user OTFS based on low-complexity iterative least-squares solvers are not directly applicable to the NOMA scenario due to the presence of multi-user interference (MUI). Motivated by this, in this paper we propose a low-complexity method for equalization and detection for OTFS-NOMA. The proposed method uses a novel reliability zone (RZ) detection scheme which estimates the reliable symbols of the users and then uses interference cancellation to remove MUI. The thresholds for the RZ detector are optimized in a greedy manner to further improve detection performance. In order to optimize these thresholds, we modify the least squares with QR-factorization (LSQR) algorithm used for channel equalization to compute the post-equalization mean-squared error (MSE), and track the evolution of this MSE throughout the iterative detection process. Numerical results demonstrate the superiority of the proposed equalization and detection technique to the existing MMSE-SIC benchmark in terms of symbol error rate (SER).

In this paper, a practical precoding method for the downlink of filter bank multicarrier-based (FBMC-based) massive multiple-input multiple-output (MIMO) is developed. The proposed method includes a two-stage precoder consisting of a fractionally spaced prefilter (FSP) per subcarrier for flattening/equalizing the channel across the subcarrier band, followed by a conventional precoder whose goal is to concentrate the signals of different users at their spatial locations. This way, each user receives only the intended information. In this paper, we take note that channel reciprocity may not hold perfectly in practical scenarios due to the mismatch of radio chains in uplink and downlink. Additionally, channel state information (CSI) at the base station may not be perfectly known. This, together with imperfect channel reciprocity can lead to detrimental effects on the downlink precoder performance. We theoretically analyze the performance of the proposed precoder in the presence of imperfect CSI and channel reciprocity calibration errors. This leads to an effective method for compensating these effects. Finally, we numerically evaluate the performance of the proposed precoder. Our results show that the proposed precoder leads to an excellent performance when benchmarked against OFDM.

Orthogonal time frequency space (OTFS) modulation has recently emerged as an effective waveform to tackle the linear time-varying channels. In OTFS literature, approximately constant channel gains for every group of samples within each OTFS block are assumed. This leads to limitations for OTFS on the maximum Doppler frequency that it can tolerate. Additionally, presence of cyclic prefix (CP) in OTFS signal limits the flexibility in adjusting its parameters to improve its robustness against channel time variations. Therefore, in this paper, we study the possibility of removing the CP overhead from OTFS and breaking its Doppler limitations through multiple antenna processing in the large antenna regime. We asymptotically analyze the performance of time-reversal maximum ratio combining (TR-MRC) for OTFS without CP. We show that doubly dispersive channel effects average out in the large antenna regime when the maximum Doppler shift is within OTFS limitations. However, for considerably large Doppler shifts exceeding OTFS limitations, a residual Doppler effect remains. Our asymptotic derivations reveal that this effect converges to scaling of the received symbols in delay dimension with the samples of a Bessel function that depends on the maximum Doppler shift. Hence, we propose a novel residual Doppler correction (RDC) windowing technique that can break the Doppler limitations of OTFS and lead to a performance close to that of the linear time-invariant channels. Finally, we confirm the validity of our claims through simulations.

In this letter, we present a structure for two-channel spline graph filter bank with spectral sampling (SGFBSS) on arbitrary undirected graphs. Our proposed structure has many desirable properties; namely, perfect reconstruction, critical sampling in spectral domain, flexibility in the choice of shape and cut-off frequency of the filters, and low complexity implementation of the synthesis section, thanks to our closed-form derivation of the synthesis filter and its sparse structure. These properties play a pivotal role in multi-scale transforms of graph signals. Additionally, this framework can use both normalized and non-normalized Laplacian of any undirected graph. We evaluate the performance of our proposed SGFBSS structure in nonlinear approximation and denoising applications through simulations. We also compare our method with the existing graph filter bank structures and show its superior performance.

A key distinction between today’s and future networks is the appetite for reliable communication to support emerging critical-communication services. In this paper, we study multi-operator connectivity as a form of redundancy to support the design of reliable networks and investigate its trade-offs. This approach is motivated by 3GPP standardisation initiatives of dual-connectivity and similar techniques in industrial wired networks. We deploy a risk awareness performance metric to assess reliability: this superquantile metric accounts for periods of connectivity shortfalls. Our analysis shows that multi-operator connectivity brings significant reliability gains, in particular when network deployments by different operators exhibit high complementarity in coverage. We also explore the effects of multi-connectivity on spectral efficiency in times of high demand for bandwidth. Our study is based on a real-world dataset comprising signal strength indicators of three mobile operators in Dublin, Ireland.

The next generation of mobile networks will bring an appetite for reliable communication, which enables emerging critical-communication services. In this paper, we present network sharing between operators as a way to provide increased reliability while using the already existing mobile network infrastructure. Our results indicate that network sharing significantly improves network performance during periods of connectivity shortfalls, benefiting the design of reliable networks. Our conclusions are drawn from a real-world dataset of signal quality indicators for three mobile operators in Dublin, Ireland.

In this paper, we consider channel estimation problem in the uplink of filter bank multicarrier (FBMC) systems. We propose a pilot structure and a joint multiuser channel estimation method for FBMC. Opposed to the available solutions in the literature, our proposed technique does not rely on the flat-channel condition over each subcarrier band or any requirement for placing guard symbols between different users' pilots. Our proposed pilot structure reduces the training overhead by interleaving the users' pilots in time and frequency. Thus, we can accommodate a larger number of training signals within the same bandwidth and improve the spectral efficiency. Furthermore, this pilot structure inherently leads to a reduced peak-to-average power ratio (PAPR) compared with the solutions that use all the subcarriers for training. We analytically derive the Cramér-Rao lower bound (CRLB) and mean square error (MSE) expressions for our proposed method. We show that these expressions are the same. This confirms the optimality of our proposed method, which is numerically evaluated through simulations. Relying on its improved spectral efficiency, our proposed method can serve a large number of users and relax pilot contamination problem in FBMC-based massive MIMO systems. This is corroborated through simulations in terms of sum-rate performance for both single cell and multicell scenarios.

5G communication systems and beyond are envisioned to support an extremely diverse set of use cases with different performance requirements. These different requirements necessitate the use of different numerologies for increased flexibility. Non-orthogonal multiple access (NOMA) can potentially attain this flexibility by superimposing user signals while offering improved spectral efficiency (SE). However, users with different numerologies have different symbol durations. When combined with NOMA, this changes the nature of the interference the users impose on each other. This paper investigates a multinumerology NOMA (MN-NOMA) scheme using successive interference cancellation (SIC) as an enabler for coexistence of users with with different numerologies. Analytical expressions for the inter-numerology interference (INI) experienced by each user at the receiver are derived, where mean-squared error (MSE) is the metric used to quantity INI. Using the MSE expressions, we analytically derive achievable rates for each user in the MN-NOMA system. These expressions are then evaluated and used to compare the SE performance of MN-NOMA with that of its single-numerology counterpart. The proposed scheme can achieve the desired flexibility in supporting diverse use cases in future wireless networks. The scheme also gains the SE benefits of NOMA compared to both multinumerology and single numerology orthogonal multiple access (OMA) schemes.

Large scale multiple-input multiple-output (MIMO) or Massive MIMO is one of the pivotal technologies for future wireless networks. However, the performance of massive MIMO systems heavily relies on accurate channel estimation. While the acquisition of channel state information (CSI) in such systems requires an increasingly large amount of training overhead as the number of users grows. To tackle this issue, in this paper, we propose a deep learning assisted blind channel estimation technique for orthogonal frequency division multiplexing (OFDM) based massive MIMO systems. We prove that by exploiting the asymptotic orthogonality of the massive MIMO channels, the channel distortion can be averaged out without the prior knowledge of channel impulse responses, and after some mathematical manipulation, different users' transmitted data symbols can be extracted. Thus, by deploying a denoising convolutional neural network algorithm (DnCNN), we mitigate a remaining channel and noise effect to accurately detect the transmitted data symbols at the channel sounding stage. Using the detected data symbols as virtual pilots, we estimate the CSI of all the users at each BS antennas. Our simulation results testify the efficacy of our proposed technique and demonstrate that it can provide a mean square error (MSE) performance which coincides with that of the data-aided channel estimation technique.

Carrier frequency offset (CFO) can significantly influence the performance of multiple-input multiple-output (MIMO) systems if not estimated and corrected. Most of the existing synchronization techniques are designed for MIMO systems with collocated antennas, where the same frequency error is experienced by the received signal at each antenna. In contrast, for MIMO systems with distributed antennas, the received signals at different receive antennas suffer from different frequency errors. This makes synchronization of such systems computationally complex, especially as the number of receive antennas grows large, i.e. massive MIMO. In this paper, we study the problem of CFO estimation for distributed massive MIMO and cell-free massive MIMO. In particular, we evaluate the performance of distributed large-scale MIMO systems with both collaborative and non-collaborative CFO estimation techniques based on the maximum likelihood (ML) criterion. These optimal CFO estimation results can then serve as benchmarks on the achievable estimation performance of practical collaborative and non-collaborative CFO estimation techniques for distributed MIMO systems. The proposed ML-based CFO estimation methods are tailored to work with periodic pilot sequences. We also show how exploiting the relationships which exist between the CFOs to be estimated can substantially reduce the computational load of CFO estimation in the collaborative approach.

Massive multiple‐input multiple‐output (MIMO) is currently entering the practical implementation phase, and key implementation issues for this technology have yet to be fully addressed. Crucial among these is the practical problem of frequency synchronisation, which refers to the adjustment of the clock frequency of local nodes to the clock frequency of a reference node by estimating and compensating carrier frequency offset. Existing theoretical studies on massive MIMO generally assume perfect frequency synchronisation; however, the potentially very high complexity of this process poses a major challenge for massive MIMO systems. Therefore, new frequency synchronisation techniques are urgently needed to make the practical implementation of massive MIMO feasible. In this study, the authors provide a comprehensive classification of the existing research efforts along this line, considering different antenna architectures and modulation schemes. They also highlight the key challenges in frequency synchronisation for massive MIMO, and they outline future research directions on this topic.

Orthogonal Time Frequency Space (OTFS) is a novel modulation scheme designed in the Doppler-delay domain to fully exploit time and frequency diversity of general time-varying channels. In this paper, we present a novel discrete-time analysis of OFDM-based OTFS transceiver with a concise and vectorized input-output relationship that clearly characterizes the contribution of each underlying signal processing block in such systems. When adopting cyclic prefix in the time domain, our analysis reveals that the proposed MIMO OTFS and OFDM systems have the same ergodic capacity despite the well-known fact that the former has great advantages in low-complexity receiver design for high Doppler channels. The proposed discrete-time vectorized formulation is applicable to general fast fading channels with arbitrary window functions. It also enables practical low-complexity receiver design for which such a concise formulation of the input-output relationship is of great benefits.

In this paper, we explore the idea that 5G will permit the use of multiple waveforms, with each service employing a waveform that is best suited for it. We look at a 5G machine-type communication (MTC) scenario consisting of clustered user equipment employing device-to-device (D2D) communication, such as a smart factory with intercommunicating machinery. The overhead associated with synchronizing a large number of machine-type D2D user equipment (DUE) comes at a cost that may render synchronous communication infeasible or undesirable. Based on this motivation, we consider multiple possible combinations of prominent 5G waveform candidates for cellular users and DUEs, examining the asynchronous performance of all waveforms under consideration and using the performance of synchronous orthogonal frequency division multiplexing (OFDM) as a baseline for comparison. Specifically, we focus on the coexistence of waveforms in which the ordinary cellular users employ OFDM for synchronous communication, as in LTE, and the machine-type DUEs, operating asynchronously, employ a different waveform. When DUEs employ filter bank multicarrier with offset-QAM, the average achieved rate is marginally greater than the synchronous OFDM baseline case, and approximately 43% greater than the asynchronous OFDM case. This result is encouraging, as the benefits of asynchronous D2D communication could be enjoyed in MTC scenarios without suffering any performance reduction compared to the synchronous OFDM scenario. We then investigate how the relative performance of different waveform choices depends on the scenario by varying key parameters. Notably, for asynchronous communication, increasing the transmit power of DUEs results in diminishing benefits unless the DUEs employ a waveform that mitigates interdevice leakage interference.

We perform an asymptotic study on the performance of filter bank multicarrier (FBMC) in the context of massive multi-input multi-output (MIMO). We show that the signal-to-interference-plus-noise ratio (SINR) cannot grow unboundedly by increasing the number of base station (BS) antennas, and is upper bounded by a certain deterministic value. This is a result of the correlation between the multi-antenna combining tap values and the channel impulse responses between the terminals and the BS antennas. To solve this problem, we introduce a simple FBMC prototype filter design method that removes this correlation, enabling us to achieve arbitrarily large SINR values by increasing the number of BS antennas.

We study the possibility of removing the cyclic prefix (CP) overhead from orthogonal frequency division multiplexing (OFDM) in massive multiple-input multiple-output (MIMO) systems. We consider the uplink transmission, while our results are applicable to the downlink as well. The absence of CP increases the spectral efficiency in expense of intersymbol interference and intercarrier interference. It is known that in massive MIMO, the effects of uncorrelated noise and multiuser interference vanish as the number of base station antennas tends to infinity. To investigate if the channel distortions in the absence of CP fade away, we study the performance of the standard maximum ratio combining receiver. Our analysis reveals that in this receiver, there always remains some residual interference leading to saturation of signal-to-interference-plus-noise ratio. To resolve this problem, we propose using the time reversal (TR) technique. Moreover, in order to further reduce the multiuser interference, we propose a zero-forcing equalization to be deployed after the TR combining. We compare the achievable rate of the proposed system with that of the conventional CP-OFDM. We show that in realistic channels, a higher spectral efficiency is achieved by removing the CP from OFDM, while reducing the computational complexity.

This paper analyses a scenario where a Device-To-Device (D2D) pair coexists with an Orthogonal Frequency Division Multiplexing (OFDM) based incumbent network. D2D transmitter communicates in parts of spectrum left free by cellular users, while respecting a given spectral mask. The D2D pair is misaligned in time and frequency with the cellular users. Furthermore, the D2D pair utilizes alternative waveforms to OFDM proposed for 5G. In this study, we show that it is not worth synchronising the D2D pair in time with respect to the cellular users. Indeed, the interference injected into the incumbent network has small variations with respect to time misalignment. We provide interference tables that encompass both time and frequency misalignment. We use them to analyse the maximum rate achievable by the D2D pair when it uses different waveforms. Then, we present numerical results showing what waveform should be utilized by the D2D pair according to the time-frequency resources that are not used by the incumbent network. Our results show that the delay induced by linearly convolved waveforms make them hardly applicable to short time windows, but that they dominate OFDM for long transmissions, mainly in the case where cellular users are very sensitive to interference.

This paper studies the behavior of the sum-rate of outdoor multi-user multiple input multiple output systems, where a uniform linear array is utilized at the base station (BS), as the number of BS antennas and the number of users increase. Two schemes are studied for the downlink, the zero-forcing and the maximum ratio transmission (MRT). To begin with, the channel matrix is described deterministically using direct scattering theory. Its matrix elements are the Fourier coefficients of functions that have a physical significance, being connected to the geometry of the environment. For the case when the energy is not arriving at the BS from every spatial direction, we prove for the ZF scheme that the achievable sum-rate behavior is sublinear in the number of antennas at the BS. For the MRT scheme, we prove that there is a link between the sum-rate and the distribution of the users in the city. To numerically evaluate the sum-rate for a given city, schematically described by its streets and its buildings, we introduce a model for the Fourier coefficients of the aforementioned functions, which mixes geometrical and statistical ingredients. We randomly distribute high buildings that will act as strong scatterers and look at the influence of their number on the sum-rate. With the ZF scheme, we perform the calculations for the case where the number of BS antennas, MT, is equal to the number of users, MR, and for the case where MTis larger than MR. We observe that the sum-rate first increases linearly with the number of BS antennas, and becomes sublinear after MTreaches a certain value. The threshold depends on the number of high buildings. With the MRT scheme, the calculations confirm the theoretical predictions, and the sum-rate is greater if the users are spread over all of the city.

Generalized frequency division multiplexing (GFDM) and circular filter bank multicarrier (C-FBMC) are two contender waveforms with circular pulse-shaping that are recently proposed for the physical layer of the fifth generation of wireless communication networks (5G). This paper puts these waveforms under the microscope and conducts an analysis on their practical feasibility and performance. In addition, we present a transmitter structure for both GFDM and C-FBMC and show that this structure has the same complexity for both systems. In this paper, GFDM receiver with successive interference cancellation (SIC) is considered as it can get a performance close to that of OFDM (orthogonal frequency division multiplexing). Our bit error rate (BER) performance analysis reveals that GFDM has limitations in terms of the total number of symbols per data packet. When the number of symbols in a packet has an even value, GFDM suffers from a high error floor in BER. For the small constellation sizes, GFDM and C-FBMC reach the same BER performance as that of OFDM. As the constellation size increases, a gap between the BER curve of GFDM and OFDM starts to appear while C-FBMC keeps the same performance as OFDM. Finally, our computational complexity analysis reveals that C-FBMC receiver is simpler than GFDM.

GFDM (Generalized Frequency Division Multiplexing) is a multicarrier modulation technique that is being proposed as a potential candidate for the fifth generation of wireless communication systems (5G). Due to the fact that GFDM uses only one cyclic prefix (CP) for a group of symbols rather than a CP per symbol and it has a well contained spectral properties, it is more bandwidth efficient than the widely used OFDM modulation. In this paper, we propose novel receiver designs for GFDM by taking advantage of the particular structure in the modulation matrix. A unified receiver structure for matched filter (MF), zero forcing (ZF) and minimum mean square error (MMSE) receivers is derived. Our proposed MF receiver is based on sparsification of the modulation matrix using block discrete Fourier transform (DFT) matrix. The proposed ZF and MMSE receiver algorithms in this paper harness the special block circulant property of the matrices involved in the demodulation stage to reduce the computational cost of the system implementation. In addition, our algorithms do not incur any performance loss as no approximation is involved. The computational costs of our proposed techniques are analyzed in detail and are compared with the existing solutions that are known to have the lowest complexity. It should be highlighted that a substantial computational complexity reduction can be achieved by adopting our techniques.

This paper introduces filter bank multicarrier (FBMC) as a potential candidate in the application of massive MIMO communication. It also points out the advantages of FBMC over OFDM (orthogonal frequency division multiplexing) in the application of massive MIMO. The absence of cyclic prefix in FBMC increases the bandwidth efficiency. In addition, FBMC allows carrier aggregation straightforwardly. Self-equalization, a property of FBMC in massive MIMO that is introduced in this paper, has the impact of reducing (i) complexity; (ii) sensitivity to carrier frequency offset (CFO); (iii) peak-to-average power ratio (PAPR); (iv) system latency; and (v) increasing bandwidth efficiency. The numerical results that corroborate these claims are presented.

Multiple carrier frequency offsets (CFOs) present in the uplink of orthogonal frequency division multiple access (OFDMA) systems adversely affect subcarrier orthogonality and impose a serious performance loss. In this paper, we propose the application of time domain receiver windowing to concentrate the leakage caused by CFOs to a few adjacent subcarriers with almost no additional computational complexity. This allows us to approximate the interference matrix with a quasi-banded matrix by neglecting small elements outside a certain band which enables robust and computationally efficient signal detection. The proposed CFO compensation technique is applicable to all types of subcarrier assignment techniques. Simulation results show that the quasi-banded approximation of the interference matrix is accurate enough to provide almost the same bit error rate performance as that of the optimal solution. The excellent performance of our proposed method is also proven through running an experiment using our FPGA-based system setup.

Orthogonal frequency division multiple access (OFDMA), where different subcarriers are allocated to different users, has been adopted for the uplink of several standards and has attracted a great deal of attention as a result. However, OFDMA is highly sensitive to carrier frequency offset (CFO) between the transmitter and receiver. In the uplink, different carrier frequency offsets due to different users can adversely affect subcarrier orthogonality. We propose a low complexity CFO compensation approach that addresses this problem while maintaining optimal performance. This approach is based on the least squares and minimum mean square error criteria applicable to interleaved and block interleaved carrier assignment schemes. The proposed algorithms use the special block circulant property of the interference matrix. In contrast to existing CFO compensation techniques, our algorithms do not rely on iterations or approximations. We present our approach in this paper and describe how a considerable reduction in computational complexity can be achieved by adopting it.