Sum rate

This paper analyzes the performance of well-known precoding schemes for massive multiple-input multiple-output (MMIMO) systems. The investigations are based on extensive measurements made with a sounding system capable of capturing the dynamic channels towards users moving in many different outdoor scenarios. Assuming ideal channel state information (CSI), results show that the mean sum-rate of the maximum ratio transmission (MRT) precoder varies considerably with the scenario, e.g., from 6.5 to 14.5 bit/s/Hz (10%-and 90%-percentiles) for a 64 element uniform linear array (ULA) at the base station (BS), while the zero-forcing (ZF) and signal to leakage and noise ratio (SLNR) precoders are more robust and higher performing with variation from 13.4 to 16.3 bit/s/Hz in the same conditions. However, when the CSI is non-ideal the performance drops. With the CSI delayed corresponding to movement of about 1/5 of a wavelength, the ZF and SLNR mean sum-rate is 60-92% of that achieved with ideal CSI (10%-and 90%-percentiles). More statistics for different massive array sizes with both delay and frequency offset CSI are given in the paper. INDEX TERMS Cellular communications, channel sounding, massive MIMO, multi-user, precoding, radio propagation measurements, sum-rate, time-varying channel.

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This paper investigates the application of multicast non-orthogonal multiple access (MC-NOMA) schemes to the forward link of a satellite communication system. In multicast transmission each frame contains information of multiple users. To benefit from the theory developed in NOMA, the proposed scheme creates two groups of users within each beam. The analysis conducted in this work reveals that the user grouping has an impact on the performance. In the light of this observation, power allocation and user clustering techniques have been derived to either maximize the sum-rate or achieve maxmin fairness. The numerical simulation results show that MC-NOMA outperforms multicast orthogonal multiple access (MC-OMA) schemes, where different groups are served in orthogonal resources. Moreover, the gain of MC-NOMA over the MC-OMA becomes more prominent as number of users per group and the transmit power increases. The results show the minimum-rate and the sum-rate of MC-NOMA can be increased by a factor 2 and 1.45 with respect to MC-OMA, respectively.

Non-Orthogonal Multiple Access (NOMA) has been identified as essential in boosting system throughput to meet future wireless communication demands. Maximizing the system throughput in the NOMA network depends on distributing appropriate transmit power from the base station (BS) to users. In the NOMA network, the effective execution of power allocation (PA) at the transmitter and the successful interference cancellation (SIC) process at the receiver are inextricably connected. Therefore, our study presents an optimization problem for efficient PA for maximum sum rate in a downlink NOMA system considering the SIC. Specifically, we investigate an optimization problem to maximize the sum rate by achieving optimal PA with SIC and power budget constraints for downlink NOMA networks. The optimal PA is obtained by finding the common region between the upper bounds for the power budget and SIC constraints. A fast and low-complexity algorithm is proposed for real-world NOMA networks. Finally, simulation results are provided for the proposed method, and compare the results with the benchmark method.

This paper investigates the achievable sum-rate of massive multiple-input multiple-output (MIMO) systems in the presence of channel aging. For the uplink, by assuming that the base station (BS) deploys maximum ratio combining (MRC) or zero-forcing (ZF) receivers, we present tight closed-form lower bounds on the achievable sum-rate for both receivers with aged channel state information (CSI). In addition, the benefit of implementing channel prediction methods on the sum-rate is examined, and closed-form sum rate lower bounds are derived. Moreover, the impact of channel aging and channel prediction on the power scaling law is characterized. Extension to the downlink scenario and multi-cell scenario are also considered. It is found that, for a system with/without channel prediction, the transmit power of each user can be scaled down at most by 1/ √ M (where M is the number of BS antennas), which indicates that aged CSI does not degrade the power scaling law, and channel prediction does not enhance the power scaling law; instead, these phenomena affect the achievable sum-rate by degrading or enhancing the effective signal to interference and noise ratio, respectively.

Visible light communication, or VLC, networks emerged as a viable option for data access, particularly indoors. Their cost-effectiveness, protection to radio frequency (RF) intrusion, and extraordinarily high data speeds make them a desirable option for the upcoming generation of indoor networking technologies. In this paper, we propose the Exponential Gain Ratio Power Allocation (EGRPA), an effective and low-complex power splitting method, to increase the attainable sum amount in Multiple Input Multiple Output (MIMO) VLC downlink networks. Using numerical simulations, we assess the enactment of an indoor 2x2 MIMO VLC downlink model for several users. We also use Non-Orthogonal Multiple Access (NOMA) for enhancing spectrum efficacy. The usefulness and resilience of the suggested power splitting approach are established by the simulation outcomes, especially in scenarios with a high user count. In particular, the EGRPA power allocation algorithm shows a sum rate enhancement of more than 38.7%, 7.86%, and 7.04% for a system with three users when compared to the GRPA method, Normalized Gain Difference Power Allocation (NGDPA) method, and Logarithmic GRPA (NLGRPA) method, correspondingly.

In this contribution, we investigate a coarsely quantized MultiUser (MU)-Multiple Input Single Output (MISO) downlink communication system, where we assume 1-Bit Digitalto-Analog Converters (DACs) at the Base Station (BS) antennas. First, we analyze the achievable sum rate lower-bound using the Bussgang decomposition. In the presence of the non-linear quantization, our analysis indicates the potential merit of reconsidering traditional signal processing techniques in coarsely quantized systems, i.e., reconsidering transmit covariance matrices whose rank is equal to the rank of the channel. Furthermore, in the second part of this paper, we propose a linear precoder design which achieves the predicted increase in performance compared with a state of the art linear precoder design. Moreover, our linear signal processing algorithm allows for higher-order modulation schemes to be employed.

In this work we consider the optimization of the power assigned to the user streams in a coordinated base station downlink environment with Orthogonal Frequency Division Modulation (OFDM). In this scenario the base stations perform distributed cooperative processing with a block diagonalization scheme to remove interference among users. Two schemes based on the waterfilling technique are proposed and compared to the optimal solution, which can be obtained numerically, by using convex optimization. We show that the proposed schemes achieve a performance, in terms of weighted sum rate, very close to the optimal, without the heavy computational complexity required by the numerical solution. These sum rates are compared in a simplified scenario consisting of two-user and two-cell. Other more realistic multicell scenario and some examples of achievable rates are presented too.

In this paper, the spatial interference alignment (IA) is investigated in the downlink (DL) of a relay-assisted multi-cell multiuser network. The transmission from the base station (BS) to the mobile station (MS) takes place in two phases with the help of the selected relay station (RS). The closed-form IA algorithms are employed in both the BS to RS and RS to MS links. The performance of this cooperative scheme is analyzed in terms of the sum rate and the sum degrees of freedom (DoF) for the amplify-and-forward (AF) and decode-and-forward (DF) relaying schemes. The simulation results of the sum rate show that the DF scheme significantly outperforms the noncooperative minleakage and max-SINR iterative algorithms over the entire range of SNR, and the AF scheme performs very close to the min-leakage algorithm. Moreover, the DF scheme outperforms the noncooperative closed-form IA algorithm in the low and medium-SNR regimes.

Non-orthogonal multiple access (NOMA) is an essential enabler technology that is expected to help satisfy the key requirements of increased system throughput in future wireless networks. However, another equally important aspect that should go hand-in-hand with system throughput is user fairness for any network. But, to the best of our knowledge, even though there have been works that look at system throughput or user fairness maximization for NOMA-based networks, they looked at these as a single objective optimization problem, where one is the objective and the other is one of the constraints. However, quite often, joint optimization of both system throughput and user fairness is required to make optimized decisions in the face of trade-offs between these two equally important but conflicting objectives. In this regard, this paper formulates a multi-objective optimization problem to jointly maximize the sum rate and user fairness in a downlink transmission NOMA system, through optimize power allocation (PA), under system-imposed constraints. A weighted sum approach is used to turn the multi-objective optimization problem into a single-objective optimization problem to make it analytically tractable. The optimized PA is then obtained using Lagrange dual decomposition method and Karush–Kuhn–Tucker (KKT) conditions. Using our derived expressions, we propose an iterative PA algorithm that converges fast enough to be employed in practical NOMA networks. We also present simulation results to highlight the effectiveness of the proposed solution. Further, the performance of the proposed method is compared with that of the benchmark methods.

In a multicarrier NOMA system, the subchannel allocation (SA) and power allocation (PA) are intricately linked and essential for improving system throughput. Also, for the successful execution of successive interference cancellations (SIC) at the receiver, a minimum power gap is required among users. As a result, this research comes up with optimization of the SA and PA to maximize the sum rate of the NOMA system while sticking to the minimum power gap constraint in addition to minimum user rate, maximum number of users in a subchannel and power budget constraints for downlink transmission in multicarrier NOMA networks. To ensure that the formulated problem can be solved in polynomial time, we propose solving it in two stages; SA followed by PA. To obtain SA, we investigate four algorithms: Greedy, WSA, WCA, and WCF. For PA, we propose a low-complexity algorithm. We compare the performance of the proposed method with benchmark method that does not consider the minimum power gap constraint. We conclude that employing WCF algorithm with the PA algorithm gives the best sum rate performance.

Heterogeneous networks (HetNets) have an increased data rate, improve quality-of-service (QoS), lower latency, and use less power for future wireless networks. Despite the benefits, there are various problems in HetNets, with interference being one of the most prominent. Densification in HetNets increases interference while decreasing rate and outage probability. As a result, non-orthogonal multiple access (NOMA) based HetNets may be employed to minimize cross-tier interference. Thus, decreasing outage probability and increasing the system sum rate in order to fulfill future wireless communication needs. Power allocation (PA) is critical for increasing system throughput and reducing outages in a NOMA network. Hence, this study comes up with an optimal PA for downlink transmission NOMA-based HetNets in order to optimize the system’s sum rate and outage probability while adhering to the minimal user rate constraint. We derived a generalized optimum PA coefficient equation for small cell users of NOMA-based HetNets. Then, utilizing the PA coefficient equation, we presented an algorithm to optimize the sum rate and minimize the outage probability. To apply our algorithm in real-world wireless networks, we ensure that our algorithm is both fast and minimal in complexity. Finally, we illustrate simulation outcomes for the proposed method and compare them to OMA systems.

This paper investigates the application of multicast non-orthogonal multiple access (MC-NOMA) schemes to the forward link of a satellite communication system. In multicast transmission each frame contains information of multiple users. To benefit from the theory developed in NOMA, the proposed scheme creates two groups of users within each beam. The analysis conducted in this work reveals that the user grouping has an impact on the performance. In the light of this observation, power allocation and user clustering techniques have been derived to either maximize the sum-rate or achieve maxmin fairness. The numerical simulation results show that MC-NOMA outperforms multicast orthogonal multiple access (MC-OMA) schemes, where different groups are served in orthogonal resources. Moreover, the gain of MC-NOMA over the MC-OMA becomes more prominent as number of users per group and the transmit power increases. The results show the minimum-rate and the sum-rate of MC-NOMA can be increased by a factor 2 and 1.45 with respect to MC-OMA, respectively.

In a multicarrier NOMA system, the subchannel allocation (SA) and power allocation (PA) are intricately
linked and essential for improving system throughput. Also, for the successful execution of successive
interference cancellations (SIC) at the receiver, a minimum power gap is required among users. As
a result, this research comes up with optimization of the SA and PA to maximize the sum rate of
the NOMA system while sticking to the minimum power gap constraint in addition to minimum
user rate, maximum number of users in a subchannel and power budget constraints for downlink
transmission in multicarrier NOMA networks. To ensure that the formulated problem can be solved in
polynomial time, we propose solving it in two stages; SA followed by PA. To obtain SA, we investigate
four algorithms: Greedy, WSA, WCA, and WCF. For PA, we propose a low-complexity algorithm. We
compare the performance of the proposed method with benchmark method that does not consider the
minimum power gap constraint. We conclude that employing WCF algorithm with the PA algorithm
gives the best sum rate performance.

This work addresses the sum-rate maximization for a downlink non-orthogonal multiple access (NOMA) system in the presence of imperfect successive interference cancellation (SIC). We assume that the NOMA users adopt improper Gaussian signalling (IGS), and hence, derive new expressions of their rates under residual interference from imperfect SIC. We optimize the circularity coefficient of the IGS-based NOMA system to maximize its sum-rate subject to quality-of-service (QoS) requirements. Compared to the NOMA with proper Gaussian signaling (PGS), simulation results show that the IGS-based NOMA system demonstrates considerable sum-rate performance gain under imperfect SIC.

This work addresses the sum-rate maximization for a downlink non-orthogonal multiple access (NOMA) system in the presence of imperfect successive interference cancellation (SIC). We assume that the NOMA users adopt improper Gaussian signalling (IGS), and hence, derive new expressions of their rates under residual interference from imperfect SIC. We optimize the circularity coefficient of the IGS-based NOMA system to maximize its sum-rate subject to quality-of-service (QoS) requirements. Compared to the NOMA with proper Gaussian signaling (PGS), simulation results show that the IGS-based NOMA system demonstrates considerable sum-rate performance gain under imperfect SIC.

This paper analyzes the performance of well-known precoding schemes for massive multiple-input multiple-output (MMIMO) systems. The investigations are based on extensive measurements made with a sounding system capable of capturing the dynamic channels towards users moving in many different outdoor scenarios. Assuming ideal channel state information (CSI), results show that the mean sum-rate of the maximum ratio transmission (MRT) precoder varies considerably with the scenario, e.g., from 6.5 to 14.5 bit/s/Hz (10%-and 90%-percentiles) for a 64 element uniform linear array (ULA) at the base station (BS), while the zero-forcing (ZF) and signal to leakage and noise ratio (SLNR) precoders are more robust and higher performing with variation from 13.4 to 16.3 bit/s/Hz in the same conditions. However, when the CSI is non-ideal the performance drops. With the CSI delayed corresponding to movement of about 1/5 of a wavelength, the ZF and SLNR mean sum-rate is 60-92% of that achieved with ideal CSI (10%-and 90%-percentiles). More statistics for different massive array sizes with both delay and frequency offset CSI are given in the paper. INDEX TERMS Cellular communications, channel sounding, massive MIMO, multiuser , precoding, radio propagation measurements, sum-rate, time-varying channel.

This paper analyses the impact of inter-user distance and angular separation on the channel correlation and achievable sum-rate for a massive multiple-input multiple-output system in non line of sight conditions. The investigation is based on outdoor measurements on a channel sounding system capturing the dynamic channel of two user arrays. The paper analyses correlation and sum-rate with varying inter-user distance and angular separation of dominant beams towards the users. A large span of correlation and sum-rate values are found across the range of distances and angular separation. The investigation shows a moderate link between inter-user distance and correlation, but a strong impact on correlation is found only for low angular separation of the users. The results of this non line of sight (NLOS) scenario suggest that a distance based criteria alone is not sufficient to accurately model shared clusters and correlation.

Fully-synchronous measurements of a massive multiuser multiple-input multiple-output (MU-MIMO) radio propagation channel are presented. We evaluate the ability of a massive MIMO system to spatially separate users located close to each other in line-of-sight (LOS) propagation conditions. The system consists of a base-station (BS) antenna array equipped with 64 dual-polarized antenna elements (128 ports) arranged in a cylindrical configuration, and eight single-antenna users. The users are confined to a five-meter diameter circle and move randomly at pedestrian speeds. The BS antenna array is located on top of a 20 m tall building and has LOS to the users. We examine user separability by studying singular value spread of the MU-MIMO channel matrix for several subsets of BS antenna array ports, along with sum-rate capacity and achievable sum-rates with both zero-forcing and matched-filtering linear precoders. We also analyze the performance of the user with the lowest rate. Finally, a comparison between the performance offered by the massive MIMO system and that of a conventional MU-MIMO system is provided. To the best of our knowledge, this is the first report of fully-synchronous dynamic measurements of a massive MIMO system. Our investigation shows that even users located close to each other in LOS propagation conditions can be spatially separated in a massive MIMO system.

In this work we consider the optimization of the power assigned to the user streams in a coordinated base station downlink environment with Orthogonal Frequency Division Modulation (OFDM). In this scenario the base stations perform distributed cooperative processing with a block diagonalization scheme to remove interference among users. Two schemes based on the waterfilling technique are proposed and compared to the optimal solution, which can be obtained numerically, by using convex optimization. We show that the proposed schemes achieve a performance, in terms of weighted sum rate, very close to the optimal, without the heavy computational complexity required by the numerical solution. These sum rates are compared in a simplified scenario consisting of two-user and two-cell. Other more realistic multicell scenario and some examples of achievable rates are presented too.

Successive zero-forcing dirty paper coding (SZF-DPC) is a simplified alternative to DPC for MIMO broadcast channels (MIMO BCs). In the SZF-DPC scheme, the noncausallyknown interference is canceled by DPC, while the residual interference is suppressed by the ZF technique. Due to the ZF constraints, the precoders are constrained to lie in the null space of a matrix. For the sum rate maximization problem under a sum power constraint, the existing precoder designs naturally rely on the singular value decomposition (SVD). The SVD-based design is optimal but needs high computational complexity. Herein, we propose two low-complexity optimal precoder designs for SZF-DPC, all based on the QR decomposition (QRD), which requires lower complexity than SVD. The first design method is an iterative algorithm to find an orthonormal basis of the null space of a matrix that has a recursive structure. The second proposed method, which will be shown to require the lowest complexity, results from applying a single QRD to the matrix comprising all users' channel matrices. We analytically and numerically show that the two proposed precoder designs are optimal.

In this paper, the spatial interference alignment (IA) is investigated in the downlink (DL) of a relay-assisted
multi-cell multi-user network. The transmission from the base station (BS) to the mobile station (MS) takes place in
two phases with the help of the selected relay station (RS). The closed-form IA algorithms are employed in both the
BS to RS and RS to MS links. The performance of this cooperative scheme is analyzed in terms of the sum rate and
the sum degrees of freedom (DoF) for the amplify-and-forward (AF) and decode-and-forward (DF) relaying schemes.
The simulation results of the sum rate show that the DF scheme significantly outperforms the noncooperative minleakage
and max-SINR iterative algorithms over the entire range of SNR, and the AF scheme performs very close to
the min-leakage algorithm. Moreover, the DF scheme outperforms the noncooperative closed-form IA algorithm in
the low and medium-SNR regimes.