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To meet the coverage requirement in the 5G cellular network, small cells are conceived as an emerging technology to increase coverage and satisfy the traffic demand. However, modeling and analysis coverage is the most important step in cell planning to explore the performance of system. Furthermore, with a large deployment of small cells in a Heterogeneous Network (Hetnet), the cross-tier interference management is a complex problem that needs to be studied. The main contribution of this paper is to analyze the downlink coverage performance for 5G Hetnet where the infrastructure is composed of Macro cell and Small cell. We model the received Signal to Interference plus Noise Ratio SINR at the user and we derive coverage probability according to Stochastic Geometry under different cognitive interference with and without coordination. Simulation result are provided to validate the proposed model.

In this paper, we are going to joint design of the continuous/discrete phase transmit waveform and receive space-time filter to maximize the Signal to Interference plus Noise Ratio (SINR) in collocated Multiple Input Multiple Output (MIMO) radar systems. The resulting problem is non-convex, so we devise an iterative algorithm based on alternating optimization that applies to two different sub-problems, which monotonically enhances the objective function. In each sub-problem, we benefit from an efficient procedure based on the coordinate descent (CD) framework, and iteratively tackle the non-convex constrained optimization problem.Also, Fast Fourier Transform (FFT) is used to reduce the computational complexity in designing set of discrete phase sequences. Numerical examples illustrate superior performance of the proposed algorithm in comparison with the state-of-the-art counterparts.

Two distributed power allocation schemes are proposed to improve the energy efficiency and throughput in cellular networks subject to outage probability limits. The effects of path loss, log normal shadowing, and Rayleigh fading are considered. Upper and lower bounds on the outage probability are derived based on the normalized signal to interference plus noise ratio (SINR). A power allocation problem for throughput maximization is presented and solved using the Lagrangian method. As this problem has high computational complexity, it is split into two subproblems. Then, a power allocation problem is proposed to improve the energy efficiency. This problem is in convex fractional programming form, so a parametric transformation is used to convert it into a subtractive optimization problem which can be solved iteratively. Results are presented which show that the proposed algorithms provide better performance than existing power allocation schemes.

In this paper, we develop a physical/medium-access-control cross layer design to improve system throughput with the consideration of fairness for IEEE 802.11 WLAN. From PHY layer perspective, when an access collision occurs, the access point can still decode the corresponding data successfully if the received signal to interference plus noise ratio is larger than the threshold. This phenomenon is referred to as the capture effect. To improve system throughput, this work proposes a Differential Reception-Power Power Control scheme to take advantage of the capture effect. However, the proposed power control scheme cannot provide a fair transmission environment even though it improves the system throughput. To resolve this problem, this work proposes two methods: the adjustment of contention window size and the modification of probability mass function for the selection of the backoff value. The simulation results demonstrate that the proposed schemes can not only remarkably improve system throughput, but also provide a fair transmission environment.

Heterogeneous networks are used to meet both capacity and coverage demands in a cellular network. As the frequencies are reused due to the limited spectrum availability, there exists co-channel interference (CCI) between the high power and low power nodes in such networks apart from the CCI between high power nodes. Inter cell interference coordination (ICIC) is a big challenge towards heterogeneous network deployments since users located at the cell range expansion (CRE) area are more vulnerable to stronger interference caused by the signals from the high power nodes. To enhance capacity, achieve good user experience and improve spectral efficiency interference management techniques like fractional frequency reuse (FFR) with enhanced scheduling strategies and ICIC using expectation maximization algorithm are proposed to mitigate the effects of the CCI. The resource allocation in FFR is done for the users in the cell center (full reuse) and CRE (partial reuse) regions based on the optimum post processing signal to interference plus noise ratio threshold with different schedulers in the two regions. It is shown that a particular combination shows the best throughput performance for the proposed enhanced FFR scheme.

In this paper, we derive the packet error probability of cognitive radio networks. Our analysis is valid when the powers of secondary source and relays are adaptive. The secondary source and relays can adapt their transmitting power so that interference to primary receiver is below a given threshold T. The analysis takes into account interference from primary transmitter. Different relay selection techniques are investigated such as opportunistic amplify and forward (AF) relaying, partial and reactive relay selection. In opportunistic AF relaying, the selected relay offers the highest end-to-end signal to interference plus noise ratio (SINR). Partial relay selection activates the relay with the largest SINR of first hop. Reactive relay selection activates the relay with the largest SINR of second hop.

This paper is concerned with joint beamforming and power control for downlink multi-cell massive multiple-input and multiple-output system. The finite system analysis and large system analysis are successively made for two different system configurations. When base station (BS) antenna number and user number per cell are not large, the finite system analysis of single cell is extended to the multi-cell case after problem reformulation. With the Perron–Frobenius theory and alternative optimization, the dual uplink power and beamformers can be calculated iteratively. Based on the iteration result and the uplink-downlink duality, the final solution is obtained. However, when BS antenna number and user number are large, the large system analysis is employed. In order to reduce computation complexity, the dual uplink power is approximated by its asymptotic equivalent. First, the asymptotic expression of signal to interference plus noise ratio is derived via random matrix theory. Next, the power control problem is reformulated in the asymptotic regime to obtain the asymptotic dual uplink power. As the asymptotic dual uplink power only depends on the second order statistic, it does not require updating along with the channel state information instantaneously. As a result, the computation complexity is drastically reduced.

An relay station (RS) is a low-cost alternative to upgrading a conventional communication infrastructure. It can cope with ever-increasing wireless traffic demand and eliminate shadow areas efficiently. Accordingly, relay-based networking is a key technology for the next generation wireless communication infrastructure. In a relay-based network, the signal to interference plus noise ratio (SINR) and the throughput of the mobile stations (MSs), especially those located at cell edges, heavily depend on the location of the RSs. Hence, it is important to determine the optimal RS locations. In this paper, we address an anomaly which causes a serious fairness problem among MSs when the RS locations are determined only by throughput maximization. Moreover, RS locations were considered for a non-uniform geographical user distribution environment, because in the real world users are not uniformly distributed. We propose a utility optimal RS placement scheme based on a genetic algorithm (GA), which considers both the fairness problem and the non-uniform user distribution. An extensive simulation study verified that the proposed scheme extends cell coverage and maximizes utility while guaranteeing fairness among MSs.

Energy and spectrum optimization for massive multiple input multiple output (MIMO) cognitive femtocell based fifth generation (5G) mobile network is developed using auction game. In 5G massive MIMO, multiple numbers of antennas are used to transmit the signal with same time frequency to maximize the number of users, who can communicate with less number of channels. Cognitive radio network (CRN) also increases spectrum efficiency by sharing primary users channel to transmit data for secondary users. In this article, cognitive femtocell base stations are treated as secondary base stations to win a channel by using auction game with utility function. Femtocell base stations bid for a channel with pricing value to the MIMO base station spectrum manager and the spectrum manager allocates spectrum to the femtocell base station based on maximum pricing value. Opportunistic spectrum access by femtocell using cognitive approach decreases number of active antennas in massive MIMO based network which reduces energy consumption. Simulation results show that the proposed network reduces ~ 70% power consumptions than the existing CRN and only MIMO CRN based strategies. Simulation results also presents that the massive MIMO cognitive femtocell network increases signal to interference plus noise ratio and spectral efficiency ~ 13% and ~ 20% respectively than the existing CRN and only MIMO CRN based approaches.

Femtocells are the solution to improve cellular system capacity in indoor coverage. In two-tier networks, co-channel interference is a serious problem. In this paper, an efficient spectrum allocation scheme is proposed to improve signal to interference plus noise ratio (SINR) and the throughput for femtocell users. The proposed spectrum allocation scheme is based on reducing the cross-tier interference by allocating the best group of the available resource blocks (RBs) that achieve minimum interference level for femtocell users. The soft frequency reuse scheme is considered for long term evolution cellular system due to its ability to decrease the inter-cell interference and enhances the throughput for macrocells. Simulation results show that the proposed spectrum allocation scheme efficiently increases the SINR for femtocell users and enhances both the femtocell throughput and the total cell throughput compared to the conventional random allocation scheme. In addition, it is shown that the best performance of proposed scheme in terms of highest SINR and highest throughput is achieved by allocating only one-third of the available RBs for femtocell.

This paper proposes a new superimposed training (ST) scheme for uplink multi-user multi-cell system, where each base station, equipped with a large number of antennas (M), communicates to single antenna users. In uplink training phase, large number of users within limited coherence time introduces the pilot contamination, which causes two types of interferences in data estimation. The first type, which is referred as self interference, arises due to the dependence between channel estimate and estimation error of the same user, while the second type, known as cross interference, occurs because of the correlation between ST vectors of different users. In this paper, an ST scheme with variable data length is proposed for Rician fading channels. For simplicity of analysis, a single cell model is considered first to derive mean squared error and signal to interference plus noise ratio. The analysis is further extended to multi-cell system. Various limiting cases are investigated, and the design parameters viz., power allocation factor and length of data vector, are optimized. Simulation results verify that the proposed ST scheme reduces self interference, and yields sum rate improvement over conventional ST scheme.

Optimized cooperative scheduling (OCS) increases the network capacity of the wireless ad hoc network by optimizing relay node selection. This increases the capacity by dividing the long link into too many hops locally and avoids the node failure. OCS decides the best node for the transfer of the file by evaluating its objective function and forming the interference set of the relay node. Random scheduling generalizes the randomization framework to the Signal to Interference plus noise ratio rate-based interference model by dealing with the power allocation problem. It develops a distributed gossip comparison mechanism with the power allocation to maximize the throughput. The comparison of wireless scheduling schemes is done in terms of transmission rate, throughput, jitter, time to schedule packets, latency, end-to-end delay and bandwidth. The performance analysis proves that OCS has high transmission rate, low latency and uses less bandwidth. Random scheduling has high throughput, less time for scheduling of packets, low jitter and smaller at the end to end delay.

In this information age, high data rates and good reliability features are becoming the dominant factors for a successful deployment of commercial networks. Increasing capacity with finite power requirement in wireless networks is one of the main challenges for high speed communications. A new method of power allocation in wireless communication using beamforming vector based sectored relay planning for capacity enhancement has been proposed. It has been observed that any number of terminals (receive antennas) in the downlink can be incorporated without the requirement of additional link budget. Moreover, it has also been observed in the proposed technique that required power is also independent of coverage area i.e., the channel losses at cell borders. This optimal power allocation has been observed using beamforming vector. The beamforming vector becomes independent of transmitter diversity and is the function of receive antennas on both wireless backhaul and access link (sampled impulse response). The target signal-to-interference-noise-ratio (SINR) in the proposed technique can be achieved at small and finite power; therefore any capacity can be achieved at the target SINR. This is in contradiction to the major outcomes of the Shannon’s theorem. The simulations have been carried out in Matlab and the results given in the form of various plots and graphs.

In this paper we consider joint waveform and filter design in multi-input multi-output (MIMO) radars in the presence of signal dependent interference to improve signal-to-interference-plus-noise ratio (SINR) of received signals. We have proposed two new iterative methods for this in which instead of direct design of waveforms, the coefficients of orthogonal waveform combinations are designed. In the first method, coefficients of combinations are calculated by solving a convex optimization problem. By extending the first method, we have proposed a method for multi-target case in presence of signal dependent interference. However, the computational complexity of the first method is high and therefore we have proposed the second method, which is more suitable for real time applications. In the second method, in each step, waveform combination coefficients and received filter coefficients are designed in closed form. Simulation results show that the proposed methods can achieve higher SINR in comparison to other methods which are used in MIMO and phased array radars.

Frequency diverse array (FDA) radar has been proposed in last decade for joint range and angle beamforming of a target. Multiple input multiple output-frequency diverse array (MIMO-FDA) radar has also been presented recently in literature to steer multiple beams by creating subarrays in transmit array. These beams help to localize the target in range as well as angle dimension. Due to same subarray size, all the beams have same beamwidth and thus exhibit same response for a given target. In this paper, we have proposed an unequal size subarrays structure for the FDA radar (US-MIMO-FDA), which allow us more focusing of the target in range and angle dimension by using beams of variable width. As a result the echoes received at the receiver help in better estimation of target parameters. The effectiveness of proposed scheme has been shown by comparing transmit and received beam patterns of proposed scheme with MIMO-FDA with equal subarrays Performance analysis of proposed scheme has also been done in terms of output signal to interference plus noise ratio, detection probability and cramer-rao lower bound. Simulation and results have verified better focusing of target by proposed design as compared to existing subarrays schemes for MIMO-FDA.

Energy efficiency power control for dynamical cognitive radio networks is a challenging problem. In this paper, our objective is to minimize total transmit power of multiuser cognitive system while keeping the time-varying target signal-to-interference-noise-ratio (SINR) requirements constraints satisfied. In order to compensate the perturbations from new coming users, a SINR strengthen factor is introduced to keep minimum acceptable SINR for SUs. A robust energy aware distributed power control scheme with SINR-flexible requirements is proposed in which a tradeoff between power consumption and received SINR is considered. Simulation results show that our proposed scheme provides better SINR protection and robustness than the existing work which does not consider the entry of new users and the perturbation of channel gains.

Machine to machine (M2M) communications refer to the technology that enables huge number of devices to be wired or wireless communication with each other’s. Neither the contention based medium access control (MAC) protocols nor the reservation based MAC protocols can provide a flexible, scalable solution for M2M networks. That is because of the huge number of communicating devices. In this paper, an efficient proposed MAC protocol for M2M networks is suggested. It is divided into three periods, namely the notification, the contention and the transmission periods. During the contention period, the contention is occurred with equal probabilities between the devices which have traffic to be sent. The non-persistent carrier sense multiple access protocol is selected for the contention strategy. In the notification period, the devices get information about the contention state. Furthermore, the transmission time slots location for the succeeded ones are announced. Finally, in the transmission period, the packets from each successful contended device are sent. This is done using time division multiple access (TDMA) strategy in the reserved time slot. Moreover, more than one device can transmit in one TDMA slot as long as the signal to interference plus noise ratio condition is not violated. In addition, the analytical analysis of the proposed MAC protocol is produced. Furthermore, extensive simulation programs are executed using MATLAB to measure the system performance. The system throughput, average delay time, and packet collision ratio are our performance metrics. Further, our MAC protocol outperforms other traditional ones.

Path loss minimization in next generation mobile network is a challenging research area. The signal transmitted by a base station degrades due to various obstacles in the environment. The received signal level at the mobile station is less than the transmitted signal level of the base station. This loss in the signal level is referred as path loss in mobile network. In this paper different path loss models are discussed for indoor environment covered by femtocell. It is assumed that the mobile users in that region exclusively access the services of femtocell. As only indoor area is considered, non-line of sight propagation is examined. Signal-to-interference-plus-noise-ratio for a femtocell base station is calculated. The performance of the path loss models are analyzed using vector signal generator and vector signal analyzer. A comparative analysis is carried out between the models. Based on the comparative analysis, a case study is performed to demonstrate how an appropriate path loss model will be selected depending on the frequency range, building type, walls and floors.

We study the effective signal to interference-plus-noise ratio (SINR) of the MIMO detector (or decoder) for the MIMO system with decorrelation based receive transformation (MIMO-DRT), in which the decorrelation based transformation is employed on the received signal of the MIMO receiver. By performing eigendecomposition on the inverse of the covariance matrix for interference plus noise, we express the effective SINR of MIMO-DRT in terms of the eigenvalues of the covariance matrix for interference plus noise and derive the SINR gain (relative to the MIMO system without receive transformation) provided by MIMO-DRT. We prove that the SINR gain provided by MIMO-DRT is larger than or equal to one. Furthermore, we show by both the analytical results and the simulation results that the SINR gain provided by MIMO-DRT increases with the interference to noise ratio and converges to one as the number of cochannel users gets large.

The vehicular small cell (VSC) is a new paradigm that has been recently proposed to be a potential technology for 5G cellular systems. Briefly, VSC concept lies in using the small cell technology inside vehicles such as buses and private cars to provide better coverage and good internet experience while on the move where the wireless backhaul link is inevitable. However, in order to increase the spectral efficiency, co-channel deployment of VSCs on the wireless backhaul link is preferred. Thus, managing the variable interference on the wireless backhaul and its power allocation requirement seem to be serious challenges in implementing the VSCs. Motivated by the simplicity and practically of the power allocation based on pilot power and received signal strength index (RSSI) information, this paper proposes an evolutionary approach and robust to the interference fluctuations in which, taking the limited dynamic range of transmitted power using linear mapping into account, the signal to interference plus noise ratio (SINR) balancing of the vehicular small base stations in their home macro base station and maximum capacity on the backhaul link are achieved at the cost of exchanging some power level information among both macro and small base stations. Finally, simulation results prove aforementioned potential advantages attained from the presented schemes.

The focus in Mobile communication networks has been addressed to high data rate networks that offer high quality of service. Long Term Evolution Advanced (LTE-A) technology has been the first to completely fulfill 4G requirements. However, performance gains remain limited due to severe interference levels. For this reason, the Inter-Cell Interference (ICI) problem is one of the main challenges in LTE-A systems. In order to deal with this ICI problem, in this paper we propose a novel framework to analyze the fairness of several scheduling techniques when Fractional Frequency Reuse (FFR) schemes are used. We evaluate the system performance of a typical FFR-based LTE-A scenario. Performance results show the optimum values of the Signal to Interference plus Noise Ratio and partition bandwidth for frequency reuse that maximizes the spectral efficiency. Fairness evaluation has been done in terms of the Gini index, showing a trade-off between spectral efficiency and fairness among users. In that sense, the proposed Truncated-Equal Transmission Rate scheduling policy is able to adjust this trade-off by means of a parameter $$\varepsilon$$ .

In this paper, the joint uplink and downlink signal to interference plus noise ratio distribution have been analyzed in a two-tier heterogeneous cellular network. We assume that macro and pico base stations and user equipments are uniformly distributed in the network. User could be paired to its nearest base station or to the BS from which the average received power in the downlink is maximum. Uplink in both cases is coupled to downlink. For symmetric services both up and down links should be able to carry the information flow. Correlation between uplink and downlink coverage could be guessed even under independent Rayleigh fading. The symmetric spectral efficiency gathers both uplink and downlink capacities while forcing them to happen simultaneously. We used realistic spectral efficiencies as signaled by channel quality indicators in LTE. Fractional power control has also been included in the analysis. The results of coverage and spectral efficiency for marginal uplink, marginal downlink, and joint uplink/downlink has been obtained. The assumption of independence between both links is analyzed for the complex trade off of the parameters for network design to obtain the best symmetric efficiency.

The data rates for indoor users can be boosted using low power consuming nodes like Femtos base stations (FBSs) in long term evolution networks. The manner in which Femtos are deployed inside a building environment, with large number of users, can significantly affect the throughput and number of handovers among Femtos. In our system model, we take into account the following parameters: co-channel interference between FBS and macro BSs, wall attenuation factor and user density in the enterprise building environment. In this work, we formulate two mixed integer linear programming (MILP) optimization models: optimal constant threshold signal to interference plus noise ratio (OptCTSINR) which guarantees a certain minimum SINR and also minimizes the number of Femtos needed for the coverage of enterprise buildings and optimal handover (OptHO) which reduces the number of handovers when the user passes through a certain portion (i.e., within a room or corridor) of the building. We solve these MILP models by utilizing branch and cut framework of CPLEX solver using General Algebraic Modeling System (GAMS) tool. When compared to K-means clustering based placement scheme, for a given number of Femtos, proposed OptCTSINR scheme results in an average SINR improvement of 28 %. Similarly, our proposed OptHO scheme reduces 30 % of the unnecessary handovers when compared to OptCTSINR scheme.

The number of Wi-Fi devices and their requirements for bandwidth keep on increasing, along with their hunger for spectrum. This fact is mostly noticeable in dense urban scenarios where neighbors fight for bandwidth and their networks struggle to deliver the requested information. While the inherent limitations of Wi-Fi technologies cannot be overcome, they can be mitigated through configuration. Optimally selecting a wireless channel is a critical aspect of access point (AP) configuration, and a challenging task due to a broad range of factors affecting the wireless connection performance. This paper addresses the channel selection problem by relying on a time-varying dynamic approach capable of modeling its surrounding wireless networks with respect to their usage patterns, channel utilization and adjacent channel interference. This contextual data is used in a channel selection model, which combines utilization patterns and statistics with a probabilistic mathematical model to accurately estimate the impact of adjacent channel interference on the signal to interference plus noise ratio, hence effectively selecting a wireless channel whose optimal performance is exhibited when the users' need it. The experimental results demonstrate that the proposed approach outperforms competing methods while closely tracking the simulation models, thus paving the way for smarter APs.

Coordinated multipoint (CoMP) networks cooperatively process user equipment (UE) to eliminate inter-cell interference. CoMP networks convert the interfering signals into useful information by controlling the interference among adjacent cells. This is important for UE at the cell edge. This paper examines deployment of CoMP networks and investigates how CoMP communications can enhance the signal-to-interference and noise ratio (SINR) in practical inter-site and intra-site networks. In addition, we propose weighted clustering according to the average number of active users in the sector. Priority in forming clusters is given to sectors with more users. This reduces the error caused by the uniform UEs distribution assumption used by many researchers. We consider real city topography, terrain data, and UEs distribution to evaluate the received power and estimate the SINR improvement in real CoMP networks.

For direct-conversion transceiver, IQ imbalance is significant at both transmitter (TX) and receiver (RX), which brings in image interference and degrades the transmission quality. In order to handle this problem, the maximum-likelihood algorithm is employed to jointly estimate TX and RX IQ imbalance, and the corresponding Cramer---Rao lower bounds (CRLBs) are calculated. Furthermore, a compensation mechanism is proposed to combat IQ imbalance, which is derived from the criterion of maximum signal-to-interference-plus-noise ratio (MSINR). In addition, comprehensive simulations indicate that the mean square errors of the proposed estimation coincide with the CRLBs. Also, the proposed MSINR compensation achieves competitive performance, in terms of both SINR and bit error rate.

Capacity analysis is a hotspot in the research of wireless networks, playing an important role in the network construction. This paper analyzed the connectivity of the network to form the hops-distribution probability formula between the source node and the destination node; then developed the closed-form expressions of the upper bound and lower bound of the multi-hop capacity based on the Gupta physics model; finally first-order energy model was built for computing the bounds of the lifetime of the networks. This paper defined capacity as the amount of traffic in the lifetime of the networks. The numerical simulation shows: multi-hop network capacity with the node number showed a trend of first increasing and then decreasing; with the increasing of nodes, multi-hop have the high probability in transmission and larger range of capacity than that of one-hop network.

This work proposes a formulation to calculate the transmitter power needed to cover cells of different sizes whilst maintaining the average signal to interference-plus-noise ratio (SINR) constant, and near the maximum, for two long-term evolution (LTE) systems operating over non-contiguous frequency bands, 800 MHz and 2 GHz, with an integrated common radio resource management (iCRRM) entity, in the context of spectrum aggregation in an LTE-Advanced scenario. The iCRRM entity is able to switch users between the two LTE systems. We address a formulation based on the computation of the average received power and average co-channel interference in cellular topologies with frequency reuse pattern K=3, keeping the presence of coverage holes insignificant, whilst considering the COST-231 Hata path loss model. We have verified how the normalized power increases as the cell radius increases. The objective of applying this formulation in the dimensioning process is to save power for shorter coverage distances.

Long term evolution-advanced has developed the heterogeneous network (HetNet) that consists of a mix of macrocells and low-power nodes, such as picocells, to improve the system performance. Also, to encourage data offloading in HetNet, cell range expansion has been introduced. In this paper, we propose a cell selection scheme based on signal to interference plus noise ratio for optimal offloading effect. Also, we manage interference for the user located cell range expanded region using almost blank subframe (ABS) with flexible ABS ratio, to improve the spectrum efficiency in the time domain. Simulation results show that the proposed scheme can improve the spectrum efficiency of the macrocell and picocell user. Eventually, the proposed scheme can improve overall user performance.

Efficient radio spectrum utilization can be improved using cognitive radio technology. In this work, we consider a spectrum underlay cognitive radio system operating in a fading environment. We propose an efficient power control scheme that maximizes the effective capacity of the secondary user, provisioning quality of service while on the same time the communication of the primary user is guaranteed through interference constraints. The specific power allocation scheme uses a policy in which the outage events of the primary user are exploited leading to a significant increase of the secondary user's effective capacity. Moreover, the interference of the primary link to the secondary is taken into account so as to study a more realistic scenario. In order to safeguard primary user's communication, two types of restrictions are considered: the traditional interference power constraint and the proposed inverse signal to interference plus noise ratio constraint. Different scenarios depending on the nature of the constraints (peak/average) are studied and their impact on the performance of the primary and secondary users is investigated. The superiority of the proposed schemes is demonstrated through their comparison with two reference power control schemes. Finally, numerical calculations, validated with simulation results, confirm the theoretical analysis and evaluate the performance of the proposed scheme for all the different scenarios.

To meet the requirements of users for quality of data services, techniques which can support a high data rate to users located within the cell edge as well as the cell center would be indispensible. Accordingly, the need for efficient methods to control the interference between transfer points is increasing. In current standards and academic issues the way of how to control the interference from point-to-point transmission naming coordinated multi-point (CoMP) was selected as the work items for 3rd Generation Partnership Project (3GPP) long term evolution-advanced (LTE-A) Release 11. This paper proposes a combined system of CoMP with Scheduling and Precoding, which solves the problem of conventional cellular system and improves the spectral efficiency of overall system. We design and analyze the performance of the Coordinated Beamforming technique, which is one major category of CoMP. The parameters are included in order to fulfill the requirements of the 3GPP LTE-A Standard. Finally, we make a performance analysis of the proposed system through the system level simulation in Homogeneous Network and Heterogeneous Network. We confirm the performance through a graph of the cumulative distribution function about signal to interference plus noise ratio.

To achieve high capacity in cellular networks, frequency reuse factor of unity is used. However, it suffers from heavy co-channel interference at cell edge regions. This leads to poor Signal to Interference plus Noise Ratio (SINR) and hence poor performance. fractional frequency reuse (FFR) is one of the methods being considered to improve cell edge performance. In this work we present the impact of SINR threshold and bandwidth partitioning on the successful deployment of FFR scheme. We have considered both real time (RT) and best effort (BE) traffic. In FFR, the total frequency resource is divided logically into cell center and cell edge user bands. However, while frequency resource is partitioned into two segments, the amount of bandwidth required by cell center and cell edge users is quite different and influences the system performance. We developed the semi analytical approach to evaluate the average bandwidth required by cell center and edge band users. From the analysis and simulation results it is seen that while grade of service (GoS) fair based method of choosing bandwidth partitioning ratio is best for RT traffic, while the only feasible method for BE traffic is dividing the bandwidth based on probability of a user to be in a given band which we termed as `Probability' method.

This paper proposes a narrowband interference (NBI) suppression algorithm for Direct Sequence-Code Division Multiple Access systems. The NBI is considered from heterogeneous networks, and predicted based on its cyclostationary characteristic using a nonlinear feed-forward neural network predictor which eliminates the nonlinearity of the spread spectrum (SS) signal in the NBI prediction. To further improve the suppression performance, this paper exploits the structure of the spreading code, and proposes an iterative code-aided algorithm to jointly estimate the NBI and the SS signal. Simulation results reveal that the proposed algorithm largely outperforms the conventional linear prediction filtering and linear-conjugate linear polyperiodically time-varying filtering methods in both the signal to interference plus noise ratio improvement and the bit error rates, when it operates in NBI-contaminated environments.

The throughput enhancement of Space-Time Spreading (STS)-based Code Division Multiple Access (CDMA) system is investigated in this paper. Adaptive Modulation is utilized to improve the data throughput of the system in multipath Rayleigh fading channel. In this contribution, an analytical approach is proposed to compute a new expression for the Bit Error Rate (BER) performance and the output Signal-to-Interference-and-Noise Ratio (SINR) of the RAKE receiver-assisted STS-based CDMA system for QAM data, considering multipath and multiuser interferences. The other contribution of the paper is deriving a new closed form expression for computing the throughput enhancement and the BER performance of the adaptive modulated STS-based CDMA system over multipath fading channel. Simulation and analytical results demonstrate that using adaptive modulation method in this system improves the average throughput by keeping the BER performance at a target level. The novel expressions presented in this paper bring out the facility of evaluation of the proposed system with no need to more calculations and simulations.

We propose in this paper an efficient method to derive the optimal feasible power and weight for joint diversity and power control. Instead of solving a constrained optimization problem where both the variables of power and the variables of weight are involved, this method simply solves a set of equations where only the variables of power are involved. It is proven that the power and weight obtained from the proposed method can minimize the power consumption. To reduce the computational complexity, we further propose another method where the number of equations can be reduced from the number of users to the number of base stations.

We present an analytic derivation of downlink dimensioning for a wireless network employing the "high speed downlink packet access" (HSDPA) standard, currently being developed by the 3/sup rd/ Generation Partnership Project (3GPP) as part of the next stage in the evolution of the WCDMA standard (see Frenger, P. et al., "Performance Comparison of HARQ with Chase Combining and Incremental Redundancy for HSDPA", http://www.3gpp.org; Moulsley, T. J., 3G Mobile Commun. Technologies, IEE Conf. Publication No. 477, 2001). We determine the maximum possible cell radius such that the probability of outage, P/sub out/, at the cell's "worst" location does not exceed a preset value under full load conditions. The results are presented in the form of curves obtained by numerical integration of integral expressions. The results can be used, for instance, to find the increase in cell radius achievable by a certain reduction in the value of the signal-to-interference-plus-noise ratio (SINR) threshold used to define outage.

The need to combat the severe effects of fading and interference in the rapidly increasing number of communication systems providing wireless services has motivated the study of diversity in the presence of interference. Hence the analysis of wireless systems with both transmit and receive diversity and subject to cochannel interference is an important tool for system design. We consider here a K-transmit dual-receive diversity communication system employing K antennas for transmission and two antennas for reception. The desired signal is corrupted by N interfering sources apart from additive white Gaussian noise. The channel is Rayleigh fading. As a result, the channel matrix for the desired signal and the propagation vectors of the interferers have zero-mean complex Gaussian entries; the entries are assumed to be independent and identically distributed. The complex receive weight vector used for combining the received signals is chosen so as to maximize the output signal-to-interference-plus-noise ratio (SINR). From the statistics of the channel matrix and the propagation vectors of the interferers, we derive a closed-form expression for the probability density function (p.d.f.) of the maximum output SINR. This p.d.f. can be used to obtain the symbol error probability for different digital modulation schemes.

This paper analyzes the application of macrodiversity in Code Division Multiple Access (CDMA) asynchronous systems with decorrelating detection in the reverse link. It is shown that decorrelating detectors allow predetection combining and, utilizing this property, several combining strategies are studied. We obtain the set of combining factors which minimize the bit error probability, and based on these results, we propose the Simplified Minimum Error Criterion (SMEC), which has little impact on the overall complexity of the system and outperforms the Maximal Signal to Interference plus Noise Ratio Combiner (MSINRC). Using this technique, it is possible to perform a distributed detection in the area influenced by the mobile, allowing the coexistence of heterogeneous cells and the effective use of microcells.