In this paper, we propose a novel user selection scheme based on jointly combining channel gain (CG) and signal to interference plus noise ratio (SINR) to improve the sum-rate as well as to reduce the computation complexity of multi-user massive multi-input multi-output (MU-massive MIMO) downlink transmission through a block diagonalization (BD) precoding technique. By jointly considering CG and SINR based user sets, sum-rate performance improvement can be achieved by selecting higher gain users with better SINR conditions as well as by eliminating the users who cause low sum-rate in the system. Through this approach, the number of possible outcomes for the user selection scheme can be reduced by counting the common users for every pair of user combinations in the selection process since the common users of CG-based and SINR-based sets possess both higher channel gains and better SINR conditions. The common users set offers not only sum-rate performance improvements but also computation complexity reduction in the proposed scheme. It is shown by means of computer simulation experiments that the proposed scheme can increase the sum-rate with lower computation complexity for various numbers of users as compared to conventional schemes requiring the same or less computational complexity.

In this letter, we study an interference scenario under a smart interferer which observes color channels and interferes with a visible light communication (VLC) network. We formulate the smart interference problem based on a Stackelberg game and propose an optimal response algorithm to overcome the interference by optimizing transmit power and sub-color channel allocation. The proposed optimization algorithm is composed with Lagrangian dual decomposition and non-linear fractional programming to have stability to get optimum points. Numerical results show that the utility by the proposed algorithm is increased over that of the algorithm based on the Nash game and the baseline schemes.

Intersymbol interference (ISI) is a significant source of degradation in many digital communication systems including our proposed non-far region communication system using large array antennas in the millimeter-wave band in which the main cause of ISI can be attributed to the path delay differences among the elements of an array antenna. This paper proposes a quantitative method to evaluate the ISI estimated from the measured near-field distribution of the array antenna. The influence of the uniformity in the aperture field distribution in ISI is discussed and compared with an ideally uniform excitation. The reliability of the proposed method is verified through a comparison with another method based on direct measurements of the transmission between the actual antennas. Finally, the signal to noise plus interference is evaluated based on the estimated ISI results and ISI is shown to be the dominant cause of the degradation in the reception zone of the system.

In this paper, we apply extended regularized channel inversion precoding to address the multiuser multiantenna downlink transmission problem. Different from conventional regularized channel inversion precoding, extended RCI precoding considers non-homogeneous channels, adjusts more regularization parameters, and exploits the information gained by inverting the covariance matrix of the channel. Two ways of determining the regularization parameters are investigated. First, the parameters can be determined by solving a max-min SINR problem. The constraints of the problem can be transformed to the second-order cone (SOC) constraints. The optimal solution of the problem can be obtained by iteratively solving a second-order cone programming (SOCP) problem. In order to reduce the computational complexity, a one-shot algorithm is proposed. Second, the sum-rate maximization problem is discussed. The simple gradient-based method is used to solve the problem and get the regularization parameters. The simulation results indicate that the proposed algorithms exhibit improved max-min SINR performance and sum-rate performance over RCI precoding.

This paper investigates an adaptive movable access point (AMAP) system and explores its feasibility in a static indoor classroom environment with an applied wireless local area network (WLAN) system. In the AMAP system, the positions of multiple access points (APs) are adaptively moved in accordance with clustered user groups, which ensures effective coverage for non-uniform user distributions over the target area. This enhances the signal to interference and noise power ratio (SINR) performance. In order to derive the appropriate AP positions, we utilize the k-means method in the AMAP system. To accurately estimate the position of each user within the target area for user clustering, we use the general methods of received signal strength indicator (RSSI) or time of arrival (ToA), measured by the WLAN systems. To clarify the basic effectiveness of the AMAP system, we first evaluate the SINR performance of the AMAP system and a conventional fixed-position AP system with equal intervals using computer simulations. Moreover, we demonstrate the quantitative improvement of the SINR performance by analyzing the ToA and RSSI data measured in an indoor classroom environment in order to clarify the feasibility of the AMAP system.

This letter considers the robust transceiver design for multiple-input multiple-output interference channels under channel state information mismatch. According to alternating schemes, an adaptive algorithm is proposed to solve the minimum SINR maximization problem. Simulation results show the convergence and the effectiveness of the proposed algorithm.

In this letter, we show the new signal power estimation method base on the subspace projection. This work mainly contributes to the SINR estimation problem because, in this research, the signal power estimation is implicitly or explicitly performed. The difference between our method and the conventional method related to this topic is the exploitation of the subspace character of the signals constructing the observed signal. As tools to perform subspace operation, we apply orthogonal projection and oblique projection which can extracts desired parameters. In the proposed scheme, the statistics of the projected observed signal by these projection are used to estimate the parameters.

In this paper, a self optimization beamforming null control (SOBNC) scheme is proposed. There is a need of maintaining signal to interference plus noise ratio (SINR) threshold to control modulation and coding schemes (MCS) in recent technologies like Wi-Fi, Long Term Evolution (LTE) and Long Term Evolution Advanced (LTE-A). Selection of MCS depends on the SINR threshold that allows maintaining key performance index (KPI) like block error rate (BLER), bit error rate (BER) and throughput at certain level. The SOBNC is used to control the antenna pattern for SINR estimation and improve the SINR performance of the wireless communication systems. The nulling comes with a price; if wider nulls are introduced, i.e. more number of nulls are used, the 3dB beam-width and peak side lobe level (SLL) in antenna pattern changes critically. This paper proposes a method which automatically controls the number of nulls in the antenna pattern as per the changing environment based on adaptive-network based fuzzy interference system (ANFIS) to maintain output SINR level higher or equal to the required threshold. Finally, simulation results show a performance superiority of the proposed SOBNC compared with minimum mean square error (MMSE) based adaptive nulling control algorithm and conventional fixed null scheme.

An ordered successive interference cancellation (OSIC) scheme based on combined post-processing signal-to-interference-plus-noise ratio (PSINR) is proposed for multiple-input multiple-output (MIMO) systems with retransmission. For the OSIC procedures at the current transmission round, instead of reusing the PSINRs and decision statistics calculated for the previous transmission rounds, the proposed OSIC scheme newly calculates the combined PSINRs and combined decision statistics from the available receive signal vectors and channel matrices at every retransmission. Therefore, the proposed OSIC scheme utilizes all receive signal vectors and channel matrices obtained up to the current transmission round during the OSIC procedures. A low-complexity version of the proposed OSIC scheme is also proposed, and the low-complexity version recalculates the combined PSINRs and combined decision statistics from part of the available receive signal vectors and channel matrices. Simulation results verify that the proposed schemes achieve significantly better error performance than existing OSIC schemes based on the detection and combining process for MIMO systems with retransmission.

Recently, many neural networks have been proposed for radar sea clutter suppression. However, they have poor performance under the condition of low signal to interference plus noise ratio (SINR). In this letter, we put forward a novel method to detect a small target embedded in sea clutter based on an optimal filter. The proposed method keeps the energy in the frequency cell under test (FCUT) invariant, at the same time, it minimizes other frequency signals. Finally, detect target by judging the output SINR of every frequency cell. Compared with the neural networks, the algorithm proposed can detect under lower SINR. Using real-life radar data, we show that our method can detect the target effectively when the SINR is higher than -39dB which is 23dB lower than that needed by the neural networks.

The pilot contamination is a serious problem which hinders the capacity increasing in the massive MIMO system. Similar to Fractional Frequency Reuse (FFR) in the OFDMA system, Fractional Pilot Reuse (FPR) is proposed for the massive MIMO system. The FPR can be further classified as the strict FPR and soft FPR. Meanwhile, the detailed FPR schemes with pilot assignment and the mathematical models are provided. With FPR, the capacity and the transmission quality can be improved with metrics such as the higher Signal to Interference and Noise Ratio (SINR) of the pilots, the higher coverage probability, and the higher system capacity.

This letter deals with a new cell clustering problem subject to signal-to-interference-plus-noise-ratio (SINR) constraints in uplink network MIMO systems, where multiple base stations (BSs) cooperate for joint processing as forming a cluster. We first prove that the SINRs of users in a certain cluster always increase monotonically as the cluster size increases when the receiver filter that maximizes the SINR is used. Using this result, we propose an efficient clustering algorithm to minimize the maximum number of cooperative BSs in a cluster. Simulation results show that the maximum number of cooperative BSs minimized by the proposed method is close to that minimized by the exhaustive search and the proposed scheme outperforms the conventional one in terms of the outage probability.

In the literature, many resource allocation schemes have been proposed for multi-hop networks. However, the analyses provided focus mainly on the single cell case. Inter-cell interference severely degrades the performance of a wireless mobile network. Therefore, incorporating the analysis of inter-cell interference into the study of a scheme is required to more fully understand the performance of that scheme. The authors of this paper have proposed a parallel relaying scheme for a 2-hop OFDMA virtual cellular network (VCN). The purpose of this paper is to study a new version of that scheme which considers a multi-cell environment and evaluate the performance of the VCN. The ergodic channel capacity and outage capacity of the VCN in the presence of inter-cell interference are evaluated, and the results are compared to those of the single hop network (SHN). Furthermore, the effect of the location and number of wireless ports in the VCN on the channel capacity of the VCN is investigated, and the degree of fairness of the VCN relative to that of the SHN is compared. Using computer simulations, it is found that in the presence of inter-cell interference, a) the VCN outperforms the SHN even in the interference dominant transmission power region (when a single cell is considered, the VCN is better than the SHN only in the noise dominant transmission power region), b) the channel capacity of the VCN remains greater than that of the SHN even if the VCN is fully loaded, c) an optimal distance ratio for the location of the wireless ports can be found in the interval 0.2∼0.4, d) increasing the number of wireless ports from 3 to 6 can increase the channel capacity of the VCN, and e) the VCN can achieve better outage capacity than the SHN.

In the next generation mobile network, the demand for high data rate transmission will require an increase in the transmission power if the current mobile cellular network architecture is used. Multihop networks are considered to be a key solution to this problem. However, a new resource allocation algorithm is also required for the new network architecture. In this paper, we propose a resource allocation scheme for a parallel relay 2-hop OFDMA virtual cellular network (VCN) which can be applied in a multiuser environment. We evaluate, by computer simulation, the ergodic channel capacity of the VCN using the proposed algorithm, and compare the results with those of the conventional single hop network (SHN). In addition, we analyze the effect of the location of the relay wireless ports on the ergodic channel capacity of the VCN. We also study the degree of fairness of the VCN, using the proposed scheme, compared with that of the SHN. For low transmission power, the simulation results show: a) the VCN can provide a better ergodic channel capacity and a better degree of fairness than the SHN, b) the distance ratio for which the ergodic channel capacity of the VCN is maximal can be found in the interval 0.20.3, c) the ergodic channel capacity of the VCN remains better than that of the SHN as the number of users increases, and d) as the distance between the relay WPs and the base station increases, the channel capacity of VCN approaches that of the SHN.

MIMO two-way multi-hop networks are considered in which the radio resource is fully reused in all multi-hop links to increase spectrum efficiency while the adjacent interference signals are cancelled by MIMO processing. In addition, the nodes in the multi-hop network optimize their transmit powers to mitigate the remaining overreach interference. Our main contribution in this paper is to investigate an efficient relay placement method with power allocation in such networks. We present two formulations, namely QoS-constrained optimization and SINR balancing, and solve them using a sequential geometric programming method. The proposed algorithm takes advantage of convex optimization to find an efficient configuration. Simulation results show that relay placement has an important impact on the effectiveness of power allocation to mitigate the interference. Particularly, we found that an uniform relay location is optimal only in power-limited scenarios. With optimal relay locations, significant end-to-end rate gain and power consumption reduction are achieved by SINR balancing and QoS-constrained optimization, respectively. Furthermore, the optimal number of hops is investigated in power or interference-limited scenarios.

In this letter, signal to interference plus noise ratio (SINR) performance is analyzed for orthogonal frequency division multiplexing (OFDM) based amplify-and-forward (AF) relay systems in the presence of carrier frequency offset (CFO) for fading channels. The SINR expression is derived under the one-relay-node scenario, and is further extended to the multiple-relay-node scenario. Analytical results show that the SINR is quite sensitive to CFO and the sensitivity of the SINR to CFO is mainly determined by the gain factor and the different power of the direct link channel and relay link channel.

In this paper, a distributed cooperative multicell beamforming algorithm is proposed, and a detail analysis and solving method for instantaneous and statistical channel state information (CSI) are presented. Firstly, an improved distributed iterative beamforming algorithm is proposed for the multiple-input single-output interference channel (MISO IC) scenario which chooses virtual signal-to-interference-and-noise (SINR) as decision criterion to initialize and then iteratively solves the constrained optimization problem of maximizing the virtual SINR for a given level of generated interference to other users. Then, the algorithm is generalized to the multicell date sharing scenario with a heuristics power allocation scheme based on a viewpoint of the layered channel. Finally, the performance is illustrated through numerical simulations.

In time division multiple access (TDMA)-based wireless mesh networks, interference relationships should be considered when time slots are assigned to links. In graph theory-based time slot assignment algorithms, the protocol interference model is widely used to determine radio interference information, although it is an inaccurate model of actual radio interference. On the other hand, the signal-to-interference-plus-noise-ratio model (SINR model) gives more accurate interference relationships but is difficult to apply to time slot assignment algorithms since the radio interference information cannot be determined before time slot assignment. In this paper, we investigate the effect of the parameters of the protocol interference model on the accuracy of the interference relationships determined using this model. Specifically, after assigning time slots to links based on the protocol interference model with various interference ratios, which is the major parameter of the protocol interference model, we compare the interference relationship among links in the protocol interference and SINR models. Through simulation experiments, we show that accuracy of the protocol interference model is improved by up to 15% by adjusting the interference ratios of the protocol interference model.

In this letter, we study the power control of a cognitive radio (CR) network, where the secondary user (SU) is allowed to share the spectrum with the primary user (PU) only if the signal to interference plus noise ratio (SINR) at the PU is higher than a predetermined level. Both PU fixed power control and PU adaptive power control are considered. Specifically, for the PU adaptive power control, the PU will cooperate with the SU by transmitting with adaptive power. The optimal power control schemes for the SU to maximize the SU throughput under the PU SINR constraint are derived. It is shown that the SU throughput achieved by the optimal power control with the PU adaptive power control is a significant improvement over the optimal power control with the PU fixed power control, especially under high power constraint and low SINR constraint.

In this letter, we address a strategy to enhance the signal-to-interference plus noise ratio (SINR) of the worst-case user by using cooperative transmission from a set of geographically separated antennas. Unlike previously reported schemes which are based on either the power control of individual antennas or cooperative orthogonal transmission, the presented strategy utilizes the minimum-mean-squared error (MMSE) filter structure for beamforming, which provides increased robustness to the external interference as well as the background noise at the receiver. By iteratively updating the cooperative transmission beamforming vector and power control (PC), the balanced SINR is obtained for all users, while the transmission power from each antenna also converges to within the constrained value. It is demonstrated that proposed MMSE beamforming significantly outperforms other existing schemes in terms of the achievable minimum SINR.