A Convergent Version of the Max SINR Algorithm for the MIMO Interference Channel

In closed-loop multiple input and multiple output (MIMO) systems, using a transmit power allocation scheme can increase capacity. However, the use of a space division multiplexing (SDM) scheme, which does not separate the MIMO channel into orthogonal channels, causes nonlinearity between the transmit power and the corresponding signal to interference plus noise ratio (SINR) of each data stream at the output of the detector (e.g. utilizing a MMSE detector with parallel interference canceller at the receiver). This makes it difficult to obtain the optimal power allocation value for each data stream. This paper proposes a novel power allocation scheme with an iterative algorithm for MIMO systems to solve the above problem. Furthermore, we incorporate transmit antenna selection into our proposed power allocation scheme in order to attain further capacity enhancement. Several computer simulation results are provided to show the effectiveness of our proposed techniques.

We propose an adaptive transmit and receive beam forming (TRBF) scheme for Time Division Duplex Multiple Input and Multiple Output (TDD-MIMO) system. Through analyzing the anti-jamming mechanism and deficiency from the point of subspace projection, we solve the optimization problem of designing TRBF and give an adaptive scheme. Firstly, the receiver determines receive beam former according to the legitimate channel matrix and interference null space. Secondly, the receiver uses the receive beam former as the transmit beam former to send training sequences to the transmitter for estimating the receive space. Finally, the transmitter determines the transmit beam former to correct the transmit power pointing to the receive space for avoiding power leakage. Since all of the transmit power reaches receiver and is collected, the receiver can get the maximum signal-to interference plus noise ratios (SINR). Simulation results show that the proposed method outperforms conventional beam forming significantly and has a similar performance to the theoretical value in the presence of repressive and deceptive interference.

In downlink multiple streams multiple-input multiple-output (MIMO) system, adaptive modulation and coding (AMC) is used to increase spectrum efficiency (SE) due to selecting the modulation and coding rate scheme (MCS) dynamically. However, there is a gap between UE's signal to interference plus noise ratio (SINR) and that required by the MCS. In this paper, we propose a novel power loading algorithm using the SINR gap. The algorithm converts the SINR gap into the transmit power gap among different streams. Thus BS adjusts transmit power allocation for different streams and selects higher MCS than that without adjusting power. The results demonstrate that this proposed algorithm contributes large gain of SE for single user (SU-) MIMO based on singular value decomposition (SVD) preceding.

Interference alignment (IA) with symbol extensions in the quasi-static flat-fading K-user multipleinput multiple-output (MIMO) interference channel (IC) is considered in this paper. In general, long symbol extensions are required to achieve the optimal fractional degrees of freedom (DOF). However, long symbol extensions over orthogonal dimensions produce structured (diagonal or block diagonal) channel matrices from transmitters to receivers. Most of existing approaches are limited in cases where the channels have some special structures, because they align the interference without preserving the dimensionality of the desired signal explicitly. To overcome this common drawback of most existing IA algorithms, two novel iterative algorithms for IA with symbol extensions are proposed. The first algorithm designs transceivers for IA based on the mean square error (MSE) criterion which minimizes the total MSE of the system while preserving the dimensionality of the desired signal. The novel IA algorithm is a constrained optimization problem which can be solved by Lagrangian method. Its convergence is proven as well. Utilizing the reciprocity of alignment, the second algorithm is proposed based on the maximization of the multidimensional case of the generalized Rayleigh Quotient. It maximizes each receiver’s signal to interference plus noise ratio (SINR) while preserving the dimensionality of the desired signal. In simulation results, we show the superiority of the proposed algorithms in terms of four aspects, i.e., average sum rate, the fraction of the interfering signal power in the desired signal subspace, bit error rate (BER) and the relative power of the weakest desired data stream.

In this paper, the performance of hybrid carrier (HC) systems based on weighted fractional Fourier transform (WFRFT) is investigated in an uplink non-orthogonal multiple access (NOMA) scenario. NOMA is a promising technology to improve the system capacity, in which two users (far-user and near-user relative to a base station) are allocated to use the same time-frequency resources, and the successive interference cancellation (SIC) technique is implemented to decode signals at the receiver. Considering the actual error decoding in the SIC process (i.e. imperfect SIC), NOMA cannot avoid the inter-user interference (IUI) and residual interference (or error propagation). Therefore, firstly IUI and residual interference are analysed, and signal to interference plus noise ratio (SINR) of the far-user is expressed mathematically considering the residual interference. Then, based on the analysis of IUI, considering different WFRFT orders, a near-user BER expression over additive white Gaussian noise (AWGN) channels is derived. Furthermore, the optimal WFRFT order selection to minimise the interference influence in the uplink is formulated and solved efficiently. Simulation results have verified the mathematical expression of SINR, the near-user theoretical BER expression, and the proposed optimal WFRFT order selection to obtain the maximum sum spectral efficiency.

Successive interference cancellation (SIC) for code division multiple access (CDMA) systems, together with a suitable power control, is an attractive technique to reduce multiuser access interference in uplink transmissions. In this paper we propose a receiver design which minimizes the system transmit power while ensuring a constant signal to noise plus interference ratio (SNIR) at each user detection point by using a suitable order of user detection. Indeed, the problem is a joint optimization of power control and ordering of user detection and its optimum solution is NP-hard. Hence, we derive both a suboptimal greedy algorithm and a randomized search which explores many solutions. All these approaches are evaluated in an uplink multiuser scenario for the UMTS-TDD standard in terms of bit error rate and power consumption.

We consider the problem of waveform design for Multiple-Input Multiple-Output (MIMO) radar in the presence of signal-dependent interference embedded in white Gaussian disturbance. We present two sequential optimization procedures to maximize the Signal to Interference plus Noise Ratio (SINR), accounting for a constant modulus constraint as well as a similarity constraint involving a known radar waveform with some desired properties (e.g., in terms of pulse compression and ambiguity). The presented sequential optimization algorithms, based on a relaxation method, yield solutions with good accuracy. Their computational complexity is linear in the number of iterations and trials in the randomized procedure and polynomial in the receive filter length. Finally, we evaluate the proposed techniques, by considering their SINR performance, beam pattern as well as pulse compression property, via numerical simulations.

Signal to interference plus noise ratio (SINR) based call admission control (CAC) scheme admits incoming calls as long as the measured SINR is higher than threshold value (SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> ). If a high value of SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> is chosen, the signal quality will improve but this will increase the blocking probability (p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> ), and as a result, will decrease the network utilization. On the other hand, a low value of SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> will reduce p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> , however degrades the signal quality and increases outage probability (p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">out</sub> ). Hence, how to choose appropriate SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> is very important. In this paper, we focus on the following aspects. Firstly, an accurate upper bound of SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> is derived. Secondly, based on the upper bound of SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> and a lower bound from other literature, we design a fuzzy logic controller (FLC), which can adaptively adjust SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> according to the number of active users (AUs) in a cell and average arriving traffic intensity (AATI) in Erlang per cell. Finally, network performance based on FLC is compared with that based on optimal fixed SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> . Numerical results show that the proposed scheme based on FLC has better performance than the optimal fixed threshold CAC scheme.

In this paper, we propose a novel opportunistic scheduling algorithm, joint useful and interference channel based scheduling (JUICS), in coordinated multi-point (CoMP) transmission scenario. Our scheme jointly considers the useful channel condition of the scheduled user from its serving cell and the orthogonality between that and the corresponding interference channels to concurrently scheduled users in neighboring CoMP cells, thus to exploit multi-user diversity (MUD) and mitigate inter-cell interference (ICI) simultaneously. The performance of the proposed algorithm is evaluated through simulation in terms of the cumulative distribution performance of the received signal to interference plus noise ratio (SINR) and that of the scheduled times of all CoMP users. Results show that, with limited complexity and overhead, our scheme can significantly enhance the received SINR with relatively better fairness guarantee, thus to achieve the largest throughput and utility comparing to several well-known scheduling algorithms.

Wireless Powered Communication Networks (WPCNs) represent a transformative approach to address the energy demands of mobile and Internet of Things (IoT) devices. By integrating Nonorthogonal Multiple Access (NOMA) and Intelligent Reflecting Surfaces (IRS), we can significantly enhance system performance, extend coverage, and elevate the sum rate. NOMA efficiently utilizes the entire bandwidth by employing a power allocation strategy, whereas IRS, serving as an alternative to traditional relay amplification, further bolsters the sum rate. Despite these advancements, optimizing the sum rate introduces a nonconvex optimization challenge, primarily owing to the signal‐to‐interference‐plus‐noise ratio (SINR) complexities introduced by NOMA's Successive Interference Cancellation (SIC). Traditional convex optimization solvers, such as the CVX, struggle to address nonconvexity directly. Consequently, they were unable to produce the desired outcome. Moreover, the combination of multiple technologies to improve the sum rate complicates the optimization framework, necessitating a multitude of constraints that not only heightens the mathematical complexity but also induces errors through the requisite approximations for convexity conversion. To circumvent these hurdles, we advocate the application of a minimum constrained nonlinear multivariable function (Fmincon). This approach enables us to tackle the nonconvex problem head‐on, maintaining consistent simulation parameters while limiting constraints to two pivotal factors: joint optimization of the transmit power ( ) and transmit time ( ). This strategic simplification mitigates complexity and minimizes errors. Our numerical analyses confirmed the efficacy of the proposed model and optimization technique. By co‐optimizing the transmission power and time, we achieved a notable sum rate. Comparative evaluations with extant models underscored the superior performance of our proposed framework, marking a significant stride in WPCN advancement.

Factory automation is one of the most challenging use cases for 5G-and-beyond mobile networks due to strict latency, availability and reliability constraints. In this work, an indoor factory scenario is considered, and distributed multiple- input multiple-output (MIMO) schemes are investigated in order to enable reliable communication to the actuators (ACs) active in the factory. Different levels of coordination among the access points serving the ACs and several beamforming schemes are considered and analyzed. To enforce system reliability, a max-min power allocation (MPA) algorithm is proposed, aimed at improving the signal to interference plus noise ratio (SINR) of the ACs with the worst channel conditions. Extensive system simulations are performed in a realistic scenario, which includes a new path-loss model based on recent measurements in factory scenarios, and, also, the presence of non-Gaussian impulsive noise. Numerical results show that distributed MIMO schemes with zero-forcing (ZF) beamforming and MPA have the potential of providing SINR gains in the order of tens of dB with respect to a centralized MIMO deployment, as well as that the impulsive noise can strongly degrade the system performance and thus requires specific detection and mitigation techniques.

The previously proposed first-order perturbation-based algorithm and linear constrained least mean square (LMS) based algorithm for channel matrix singular value decomposition (SVD) in multiple - input multiple - output (MIMO) orthogonal frequency division multiplexing (OFDM) systems are evaluated and compared in this paper from orthogonality, signal to noise plus interference ratio (SINR) and bit error rate (BER) view points. Due to approximations made in the perturbation-based algorithm to reduce its complexity, studies show that the estimates of the right and left singular matrices do not become unitary in this algorithm. This phenomenon causes more spatial interference and therefore the perturbation-based algorithm has less performance in comparison with the LMS-based algorithm at high SNRs.

This paper presents a theoretical analysis of subband adaptive array combining the cyclic prefix transmission scheme (SBAA-CP) in a multipath fading environment. The exact expressions for optimal weights, array outputs and the output signal to interference plus noise ratio (SINR) are derived. The analysis shows that use of the cyclic prefix data transmission scheme can significantly improve the performance of subband adaptive array (SBAA). We also show that if the output SINR is plotted versus the delay of the delay path then the output SINR of SBAA-CP is in effect the SINR of SBAA shifted by C samples to the right.

This paper considers the design problem of Multiple-Input Multiple-Output (MIMO) radar space-time transmit code (STTC) and space-time receive filter (STRF) for a moving point-like target in the presence of signal-dependent interference. An iterative procedure, whose convergence is analytically proved, is devised to maximize the Signal to Interference plus Noise Ratio (SINR) accounting for both a similarity constraint and constant modulus requirements on the probing waveform. Each iteration of the algorithm, involves the solution of hidden convex problems. Specifically, both a convex problem (whose solution is provided in closed form) and a set of fractional programming problem, that can be globally solved in polynomial time via the Dinkelback's procedure, are solved. The computational complexity is linear in the number of iterations and polynomial with the sizes of the STTC and the STRF. Finally, numerical results are provided to assess the quality of the devised procedure.

Transmission of the multimedia video streaming has been an important topic in wireless communications. As a metric of video quality at the application layer, peak signal-to-noise ratio (PSNR) is affected by the capacity at the physical layer which can be improved by power controlling and precoding. This paper investigates an optimal power allocation scheme which can maximize the sum PSNR of all users in an SLNR-precoding-based multiuser multiple input single output (MISO) system. The power allocation problem can be transformed into a convex optimization problem when the system works in the high signal to interference plus noise ratio (SINR) region. Performance of the proposed power allocation scheme is evaluated through computer simulation. Results show that, when the system works in the high SINR region, performance improvement in terms of sum PSNR through power allocation is neglectable while the effects of different precoding schemes on the sum PSNR performance are obvious.