Distributed Optimization for Coordinated Beamforming in Multicell Multigroup Multicast Systems: Power Minimization and SINR Balancing

In previous works, MIMO beamforming in multiuser wireless systems is typically formulated in two ways: one is minimizing the total transmit power with individual signal-to-interference-plus-noise ratio (SINR) constraints for each user; and the other one is maximizing the minimum SINR among all the users with a total transmission power constraint. However, although the total transmit power is optimized, these beamforming algorithms might not be the optimum with respect to the individual energy effciency of each user. In this paper, we consider an energy-efficient multiuser MIMO beamforming algorithm that maximizes the minimum energy efficiency among all the users with individual SINR constraints. We solve the optimization problem by transforming it into a semidefinite program with relaxation that can be efficiently solved. We compare our multiuser beamforming algorithm with the traditional beamforming scheme considered in previous works, which minimizes the total transmission power with individual SINR constraints. Simulation results show the advantage of using the proposed energy-efficient beamforming algorithm.

Recently, the use of LTE in the unlicensed spectrum has gained a lot of attention to address bandwidth crunch. Due to restriction on the transmission power in the unlicensed spectrum, LTE-U/LAA cells will get deployed mostly inside residential and office buildings to provide high data rates for indoor User Equipments (UEs). The UEs with high Signal-to-Interference plus Noise Ratio (SINR) experience good throughput, but the SINR decreases significantly due to walls and other obstacles that are present in the communication path. The coverage difference of licensed and unlicensed spectrum leads to different SINRs so, efficient placement of LAA Base Stations (BSs) inside the buildings is very crucial for attaining desirable SINR for the indoor UEs. Our primary objective is to find the optimal number of LAA/LTE-U BSs with minimum SINR requirements in the unlicensed band, and the secondary objective is to maximize the minimum SINR inside the building in the licensed band with power control. To do this, we formulate an optimization model (MinLF) to find the minimum number of LAA/LTE-U BSs along with their positions in indoor scenarios which resulted in Mixed Integer Linear Programming (MILP) problem. Further, to maximize the minimum SINR in the licensed spectrum, we formulate MinLPower model to find the optimal transmission power of each LTE-U/LAA cell inside the building which resulted in Mixed Integer Non-Linear Programming (MINLP) problem. Our proposed models achieve optimal placement with a maximum energy saving of 88% compared to the maximum power scheme.

In this article, a linear precoding weight vector is designed to enhance the minimum signal-to-interference plus noise ratio (SINR) of a space-time line code (STLC)-based multicast users. To solve the intractable minimum SINR maximization problem, the optimal weight vector for each STLC user is derived, and then, the individual optimal weight vectors are linearly combined. The designed linear precoding vector improves the minimum and average SINR of the multicast users as verified by numerical results. Numerical results also verify that the STLC-based multicast is a promising scheme, especially, if a transmitter has a large number of transmit antennas and the additive noises are severe at the users.

A cooperative bidirectional relaying scheme based on distributed relay beamforming is proposed for an underlay cognitive radio network which consists of two secondary transceivers and K cognitive relay nodes and a primary network with a transmitter and receiver, all equipped with single antenna. For this network we assume that the second-order statistics of the channel coefficients between the relays and primary network is available. Also the perfect channel state information (CSI) is assumed for secondary network. Here, we propose a signal-to-interference plus noise-ratio (SINR) Balancing based on distributed relay beamforming. Our aim is to design the beamforming coefficients to maximize quality of service (QoS) for the secondary network while satisfying tolerable interference constraint for the primary network. Using semidefinite relaxation we turned this problem into convex feasibility problem which can be solved along with bisection search method. Our simulation results show that the uncertainty about the channel coefficients can be degrade the performance of the network considerably. Also as we increased the tolerable interference on primary receiver, the maximum achievable SINR is increased.

We consider a dynamic time division duplexing wireless network and propose a distributed coordinated beamforming algorithm based on Alternating Direction Method of Multipliers (ADMM) technique assuming the availability of perfect channel state information. Our design objective is to minimize the sum transmit power at the base stations subject to minimum signal-to-interference-plus-noise ratio (SINR) constraints for downlink mobile stations and a maximum interference power threshold for uplink mobile stations. First, we propose a centralized algorithm based on the relaxed Semidefinite Programming (SDP) technique. To obtain the beamforming solution in a distributed way, we further propose a distributed coordinated beamforming algorithm using the ADMM technique. Detailed simulation results are presented to examine the effectiveness of the proposed algorithms. It is shown that the proposed algorithm achieves better performance in terms of the design objective and converges faster than the reference algorithm based on primal decomposition.

Multicell coordinated beamforming (CB) can mitigate intercell interference (ICI). However, existing work on CB focuses on systems that maximize overall throughput. This paper considers CB for systems with multiple receive antennas and further extends the CB to multiuser and multistream transmission. We consider fairness and pay close attention to cell-edge users. CB that maximizes the harmonic sum of signal-to-interference-plus-noise ratio (SINR) can be derived into a low-complexity algorithm that favors cell-edge users. Two iterative algorithms are developed. From the simulation results, the proposed algorithms can provide a better fifth-percentile user throughput compared with the CB algorithms minimizing mean square error, maximizing uplink SINR, and maximizing weighted sum rate. Furthermore, the computational complexity of the proposed algorithms is significantly lower than that maximizing the minimum SINR of users.

Device-to-device (D2D) communication plays an important role in the next generation of communication systems. Enabling D2D communication decreases latency and expands the coverage of a cell in cellular networks. In addition, D2D underlaying cellular users benefit from high spectral efficiency. However, it creates interference to cellular communications. In this paper, we propose a genetic algorithm-based method to minimize the interference and maximize the spectral efficiency. One of the advantages of genetic algorithm is that it escapes from local maximums and evolves toward global maximum by searching different parts of search space simultaneously. Since D2D underlay cellular network degrades the signal-to-interference plus noise ratio (SINR), a minimum SINR is considered for cellular users. Numerical evaluations demonstrate the superior performance of the proposed technique in terms of spectral efficiency and interference mitigation.

In this paper, intercell interference (ICI) produced by adjacent / neighboring cells in a user who moves through a mining tunnel is studied. For this, a visible light communication (VLC) system is modeled that uses Time Division Multiplexing access(TDMA) and two possible topologies of LED distribution are presented within a mining tunnel to be analysed. The interference of an optical cell in its neighboring cells is analysed and compared in detail, as well as the signal to interference plus noise ratio (SINR) for different paths within the tunnel.

In a conventional cellular network, a terminal receives signals not only from the base station of that cell, but also from other cell base stations. This inter-cell interference has more impact on the cell-edge users, in multi cell environment. The inter-cell interference degrades the performance of wireless systems. Using Base Station Cooperation, the ability of a mobile station to receive signals from multiple base stations can be utilized as an opportunity to improve the spectral efficiency and to get higher data rates for cell edge users. In multi cell environment using base station cooperation overall interference can be minimized marginally, whereas the interference within the cooperation region is largely reduced. This leads to a question whether it is worth doing cooperation all the time. However increase in terms of throughput may not always be enough to increase the throughput of each of the user .Hence for such a scenario the distinct cooperation scheme is used. The distinct cooperation is a joint transmission scheme in which the selection criterion is based on user’s signal to interference plus noise ratio (SINR) is proposed and the capacity achieved through cooperation is shared equally among the cell-edge users. Here we will analyze the normal operation, full cooperation and distinct cooperation scheme in the downlink environment for cell edge users in cellular network and we will compare and see which method improves the user capacity and data rate.KeywordsCooperative transmissionfull cooperationDistinct cooperationsignal to interference plus noise ratio (SINR)

In this paper, we investigate the problem of robust beamforming for multiple-input multiple-output (MIMO) dual-function radar-communication (DFRC) system, when there exist radar look direction mismatch and communication channel state information (CSI) error. To address these system imperfections, a region-of-interest (ROI) rather than a specific angle is considered for radar sensing, and the communication CSI is assumed to be available with a bounded unknown error. With these considerations, we design a robust dual-function beamformer through optimizing the radar sensing performance in terms of the energy radiated towards the ROI, while guaranteeing the communication quality-of-service (QoS) measured by the per-user signal-to-interference-plus-noise ratio (SINR) as required. For this robust design, a max-min optimization problem is formulated and a semidefinite programming (SDP) reformulation based on the S-procedure is presented. The popular semidefinite relaxation (SDR) technique is employed to solve the resulting non-convex problem, and the tightness of SDR is discussed. Further, we propose to incorporate an extra constraint of main beam control into the problem to achieve a flat magnitude response of the beampattern over the ROI. In addition, it is shown that the proposed approach is straightforwardly applicable to the scenario of multiple targets. Numerical examples are carried out to show the tightness, and demonstrate the effectiveness and robustness of the proposed MIMO-DFRC beamforming approach.

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.

The Internet of Things (IoT) is a significant branch of the ongoing advances in the Internet and mobile communications. Yet, the use of a large number of IoT devices can severely worsen the spectrum scarcity problem. The usable spectrum resources are almost entirely occupied, and thus, the increasing demands of radio access from IoT devices cannot be met. To tackle this problem, the Cognitive Internet of Things (CIoT) has been proposed. In a CIoT network, secondary users, i.e., sensors and actuators, can access the licensed spectrum bands provided by licensed primary users (such as cellular telephones). Security is a major concern in CIoT networks. However, the traditional encryption method at upper layers (such as symmetric and asymmetric ciphers) may not be suitable for CIoT networks since these networks are composed of low-profile devices. In this paper, we address the security issues in spectrum-leasing-based CIoT networks using physical layer methods. Considering that the CIoT networks are cooperative in nature, we propose to employ cooperative jamming to achieve secure transmission. In our proposed cooperative jamming scheme, a certain secondary user is employed as the helper to harvest energy transmitted by the source and then uses the harvested energy to generate an artificial noise that jams the eavesdropper without interfering with the legitimate receivers. The goal is to minimize the Signal to Interference plus Noise Ratio (SINR) at the eavesdropper subject to the Quality of Service (QoS) constraints of the primary traffic and the secondary traffic. We formulate the minimization problem into a two-stage robust optimization problem based on the worst-case Channel State Information of the Eavesdropper (ECSI). By using Semi-Definite Programming (SDP), the optimal solutions of the transmit covariance matrices can be obtained. Moreover, in order to build an incentive mechanism for the secondary users, we propose an auction framework based on the cooperative jamming scheme. The proposed auction framework jointly formulates the helper selection and the corresponding energy allocation problems under the constraint of the eavesdropper's SINR. By adopting the Vickrey auction, truthfulness and individual rationality can be achieved. Simulation results demonstrate the effective performance of the cooperative jamming scheme and the auction framework.

This paper focuses on the problem of reconfigurable intelligent surface (RIS) aided co-design for multiple-input-multiple-output (MIMO) radar and MIMO communication systems with shared spectrum resources. The purpose is to maximize the radar output signal-to-interference-plus-noise-ratio (SINR) while ensuring the communication functionalities, where there is no line-of-sight (NLOS) propagation between the radar and the target. To achieve the goal, we develop a cyclic framework based on semi-definite programming (SDP), semi-definite relaxation (SDR), and alternating direction method of multiplier (ADMM) to jointly optimize the radar transmit waveforms, the receive filters, the communication codebook, and the RIS coefficients. Numerical experiments are conducted to evaluate the effectiveness of the proposed algorithm.

In this work, a signal-to-interference-plus-noise ratio (SINR)-based robust distributed beamforming scheme is proposed for one-way amplify-and-forward (AF) relay systems with multiple user pairs. The proposed scheme obtains its optimal beam vectors by utilizing convex semi-definite programming (SDP) optimization with newly derived bounds for signal and interference powers. Compared with existing works, the proposed scheme has much higher probability of obtaining the optimal solution than schemes applying approximate bounds exploiting Cauchy-Swartz (CS) inequality. In addition, in terms of transmit power consumption, the proposed scheme requires less transmit power than existing works while still satisfying the SINR constraints. Simulation results also demonstrate that the proposed SDP-based method outperforms the existing SDP-based methods.

In this paper, recent results in game theory and stochastic approximation are brought together to mitigate the problem of femto-to-macrocell cross-tier interference. The main result of this paper is an algorithm which reduces the impact of interference of femtocells over the existing macrocells. Such algorithm relies on the observations of the signal to interference plus noise ratio (SINR) of all active communications in both macro and femtocells when they are fed back to the corresponding base stations. Based on such observations, femto base stations learn the probability distributions over the feasible transmit configurations (frequency band and power levels) such that a minimum time-average SINR can be guaranteed in the macrocells, at the equilibrium. In this paper, we introduce the concept of logit equilibrium (LE) and present its interpretation in terms of the trade-off faced by femtocells when experimenting several actions to discover the network, and taking the action to maximize their instantaneous performance. Finally, numerical results are given to validate our theoretical findings.