The Effect of Interference Cancellation on Spectrum-Sharing Transmission Capacity

This paper analyzes large-scale networks that share the spectrum with interference cancellation (IC). The efficiency of spectrum sharing is determined primarily by interference, which in turn depends on the spatial densities, the interference cancellation method, and the spectrum sharing method, i.e., underlay or overlay. By assuming the Poisson distribution for transmitters, equal transmission power in the same system, and an interference-limited environment, this paper finds the performance gain from IC in terms of spectrum-sharing transmission capacity (S-TC), defined as the number of successful transmissions per unit area while guaranteeing the target outage probabilities of all coexisting systems. The effectiveness of IC is characterized by the coefficient of cancellation (CoC), and specific CoC values are derived for two simple IC scenarios, the strong interferer and the close interferer cancellation, with the assumption of having perfect information for channel states of interfering links and interferer locations. The sum S-TC optimal spatial densities of the two systems are given. Finally, CoC conditions to determine the superiority of an underlay or overlay method are presented. We verify that the underlay method could be preferred depending on the CoCs of coexisting systems; that is starkly different from the case without IC, in which the overlay method is always better.

This paper proposes a new application of fuzzy inference mechanism to the interference cancellation in a direct-sequence code-division multiple-access (DS/CDMA) communication system over a non-perfect power control channel. Multistage parallel interference cancellation (PIC) is an effective method to cancel the multiple access interference (MAI) for equal-power channels; nevertheless, there is a significant degradation in performance for non-equal power ones. The effectiveness of interference cancellation is related to the reliability of the tentative decision involved in the interference estimates. We established a fuzzy logic system to adapt the weight of each interference cancellation path. According to the received signal's reliability, the weights of interfering users can be estimated by the fuzzy inference mechanism, so that the error propagation would be minimized. The simulation results show that the proposed adaptive fuzzy PIC scheme is robust to the interference and channel noise and is superior to the conventional PIC and constant weight PIC schemes under a severe near-far environment.

The multiuser detection is a signal processing tech- nique which enhances the performance and capacity in DS- CDMA technology. Since its complexity issue was too expensive to handle, there was focus on the suboptimal detectors. In this paper we propose a hybrid method called adaptive differential interference cancellation method (ADIC) which is a hybrid of the differential interference cancellation method and which is then combined in a adaptive way to determine a weight matrix which will map the outcome of the differential interference cancellation method to come out with a better performance. This paper also looks into the computational cost of different methods using the floating point operation (flops) which is a good estimation of the comparative computational cost if not the exact one. I. INTRODUCTION The conventional DS-CDMA match filter detector fails to combat these issues due three prominent drawbacks: unrealis- tic ucorrelated code, near-far problem (even with strict power control (1)), and tough multiple access interference (MAI). Many advanced signal processing approaches have been made to improve the performances of these kinds of detectors. In this paper we will study the different approaches that were made in this field and implement these methods to reach a conclusion about the detection methods. As the name of the topic suggests the focus of our work will be study and propose cost effective better performing multiuser detection method. We will explore Multiuser Detection Techniques in Synchronous CDMA environment. Multi-user detection deals with the development and ap- plication of joint demodulation and interference cancellation cancellation techniques for improved detection of a desired set of digital signals in the presence of multiple access interfer- ence, intersymbol interference and noise. Since veterbi forward dynamic algorithm (2) is used in case of Optimum multiuser detection (3) the complexity grows in with the increase in the number of users. Hence the complexity is immense which increases exponentially with the increase in the number of users. Looking ahead for lower complexity hence lesser cost of implementation, the paper proposes the use of sub-optimal linear detectors (4). The sub-optimal detector the paper next focuses on is Decorrelator type of Detector (5) which is optimal in least squares. This detector out performs the optimal detector in many respects. Then the Minimum Mean Square Error (MMSE) linear detector is proposed which tries to minimize the squared error from the required transformation. It is one of the most popular detectors in use due to its easiness to implement and its lower complexity. But then in the above detection methods the decisions made were based on certain linear transformation criterion and there are missing efforts to check the performance in between the detection process to improvise the transformation method better detection. So then the paper proposes Adaptive multiuser detection. Then the paper focuses on Interference cancellation methods which utilize the feedback to reduce Multiple Access Interference (MAI) in the detected bits. Under the Interference Cancellation umbrella the Successive Interference Cancellation (SIC) (6), (7) method is explored and simulated to observe the results. Then the next method which performs better than SIC and more commonly used in real life, called Parallel Interference Cancellation (PIC) (6), (8) is also implemented. Before going ahead to implement the final proposed detection method, this paper implements Differential Interference Cancellation (DIC) (9) method. And then this paper finally proposes an Inter- ference Cancellation method called the Adaptive Differential Interference Cancellation Multiuser Detection method which is cost effective in comparison to other Interference Cancellation methods as we will require lesser hardware (multipliers as in the SIC or Parallel Interference Cancellation (PIC)) for that matter. More ever since we are using adaptive method the desired BER can be further reduced. This proposed method will be discussed in detail in the following section.

Due to the broad bandwidth nature of the direct sequence spread spectrum (DSSS) signal, the application of narrowband interference (NBI) cancelation algorithms based on the Nyquist‐Shannon sampling theory are limited by the high sampling rate. To solve the sampling and processing difficulty in the traditional DSSS communication interference cancelation method, we used the compressive sensing (CS) to reduce the sampling rate of the DSSS communication system, and further proposed a compressed domain NBI elimination method in this study. We proved that NBI with a certain bandwidth and DSSS signal are both sparse in specific dictionaries and proposed the corresponding sparse dictionary construction method. Detailed analysis of the compressed domain features of NBI and the DSSS signal demonstrated that it is possible to extract the strong NBI components from the compressed measurements. Two compressed domain NBI cancelation algorithms were proposed based on this idea. The extracted NBI components were filtered out from the compressed measurements directly in the first algorithm, and then we achieved the DSSS signal demodulation in compressed domain using the separated DSSS signal components with the orthogonal matching pursuit (OMP) algorithm. A proposed extraction filter block sparse Bayesian learning (EFBSBL) framework algorithm was utilized to estimate the NBI from the compressed measurements in the second algorithm. The estimated NBI was eliminated from the received signal, and then we recompressed the DSSS signal after NBI cancelation and realized the DSSS signal demodulation in compressed domain with the OMP algorithm. Simulation results support our theoretical analysis results and reveal that the two proposed algorithms are both effective for NBI cancelation and significant interference cancelation performance are achieved.

Radar serves as an essential sensor for detecting distant targets. However, under multiple mainlobe and sidelobe interferences, conventional interference suppression techniques often introduce significant distortion to the radar antenna's mainlobe, severely degrading critical performance metrics such as ranging and direction finding. An algorithm reused based interference cancellation with mainlobe maintenance method is proposed to solve this problem. First, a low-complexity method for estimating the direction of arrival (DOA) of interference is proposed. This method directly reuses the interference cancellation (IC) algorithm to compute the optimal weights, which are then used to synthesize the array pattern. The DOA of the interference is then estimated by identifying the null steering in this pattern. This approach eliminates the need for the computationally intensive eigenvalue decomposition, thereby significantly reducing the computational complexity. Second, based on the estimated interference DOA, a method for interference cancellation with mainlobe maintenance is introduced. By directly exploiting the estimated interference DOA information to construct a projection matrix, this method significantly reduces the computational complexity of the mainlobe maintenance. Additionally, through the projection of mainlobe interference energy onto the subspace associated with sidelobe interferences, it not only preserves the mainlobe integrity but also achieves improved suppression of sidelobe interferences. Finally, simulation and experimental results demonstrate the effectiveness of the proposed method.

For cellular networks, the increased cell density and decreased cell size will give rise to significant inter-cell interference. In this work, an adaptive antenna array and an iterative receiver are combined to facilitate inter-cell interference suppression and cancellation at the receiver end. Iterative receivers exchange soft information between different receiver modules, e.g., symbol detector and channel decoder. An adaptive antenna array is integrated within the iterative receiver, which performs interference suppression and successive interference cancellation. The beamforming weight vectors are updated in each iteration using interference rejection combing, which takes into account the soft information from the channel decoder and previously estimated interfering signals. The proposed algorithm can effectively suppress and cancel the interference signal with various signal-to-interference ratios under different channel models.

The interference suppression performance of the traditional adaptive beamforming method is affected by the collected interference samples. In this work, we proposed a method for interference cancellation in array radar. The problem of interference suppression is transformed into finding a weight vector to minimize the mean square error between the array output signal and the desired signal. According to the time-delay relationship between the target reflection echo and the radar transmitted signal, an auxiliary vector with constant modulus constraint is introduced to construct the desired signal expression. The alternative projection method is used to solve the non-convex optimization problem and obtain the optimal weight. The introduction of prior information on transmitted waveform avoids the interference sample selection and improves cancellation performance. Numerical results demonstrate the effectiveness of the proposed method.

In mobile WiMAX, geo-location is possible at the PSS (personal subscriber station) by using the preamble signals broadcasted by all the RAS (Radio Access Station) simultaneously. Using relative arrival times of signals, user location can be obtained by TDoA (Time Difference of Arrival) positioning. However, sufficient number of RAS should be detected to obtain the location in this method. Since mobile WiMAX system employs cellular network structure, the number of RAS that PSS can detect is limited due to low SNR and CCI (co-channel interference) by neighboring RAS. To detect sufficient number of RAS at the PSS, hearability should be enhanced by increasing SNR (signal to noise ratio) and SIR (signal to interference ratio), which can be achieved using long integration and interference cancellation. In multipath environment, however, interference cancellation does not remove the CCI completely. Therefore, multipath mitigation and interference cancellation method should be merged and solved together. In this paper, detection performance after interference cancellation is analyzed using mobile WiMAX geo-location system. Simulation results show that trilateration is possible in most area of the cell coverage after interference cancellation in multipath environment, except at the vicinity of the RAS.

This paper presents a new and simple decoding algorithm for layered space time block codes such as the two independent Alamouti's codes which are also called the double space-time transmit diversity (DSTTD) system. By using group interference suppression and successive interference cancellation, we can treat DSTTD as two independent space-time block codes (STBC). We can then decode both of these STBC's through a simple maximum likelihood (ML) detector with null space-based interference cancellation. We also compare the proposed interference cancellation (IC) scheme with the conventional MMSE IC scheme. The performance of the proposed IC scheme is comparable to that of the MMSE IC scheme while the complexity of the proposed scheme is lower than that of the MMSE IC scheme.

Device‐to‐device (D2D) communication underlaying cellular networks is a promising technology to improve network resource utilization. In D2D‐enabled cellular networks, interference among spectrum‐sharing links is severer than that in traditional cellular networks, which motivates the adoption of interference cancelation (IC) techniques at the receivers. However, to date, how IC can affect the performance of D2D‐enabled cellular networks is still unknown. In this paper, we present an analytical framework for studying the performance of two IC methods, that is, unconditional IC and successive IC, in large‐scale D2D‐enabled cellular networks using the tools from stochastic geometry. To facilitate the interference analysis, we propose an approach of stochastic equivalence of the interference, which converts the two‐tier interference (interference from the cellular tier and D2D tier) to an equivalent single‐tier interference. Based on the proposed stochastic equivalence models, we derive the general expressions for the successful transmission probabilities of both cellular uplinks and D2D links in the networks where unconditional IC and successive IC are respectively applied. We demonstrate how these IC methods affect the network performance using both analytical and numerical results. Copyright © 2016 John Wiley & Sons, Ltd.

Non-orthogonal multiple access (NOMA) has become the key technology in 5G communication. NOMA can achieve multi-user multiplexing in transmit power domain by allocating different power, which can effectively improve the spectral efficiency, but also causes the multiple access interference of the receiver signal. The parallel interference cancellation (PIC) technology is applied to NOMA system in order to solve the problem of high-delay and error propagation in the successive interference cancellation (SIC) algorithm. PIC can effectively compensate for the deficiency of SIC algorithm but it has high complexity. Combined with the advantages of SIC and PIC, a joint interference cancellation (JIC) method is proposed. The performance and complexity of the three algorithms are simulated and analyzed. The results show that JIC can effectively reduce the delay and improve the error propagation problem in the case of low complexity.

Multicode operation in space-time block coded (STBC) multiple input multiple output (MIMO) systems can provide additional degrees of freedom in code domain to achieve high data rates. In such multicode STBC systems, the receiver experiences code domain interference (CDI) in frequency selective fading. In this paper, we propose a linear parallel interference cancellation (LPIC) approach to cancel the CDI in multicode STBC signals in frequency selective fading. The proposed detector first performs LPIC followed by STBC decoding. We present an SINK for the proposed detector. We evaluate the bit error rate (BER) performance of the system, and show that the proposed detector effectively cancels the CDI and achieves improved error performance. Our BER results further illustrate how the combined effect of interference cancellation, transmit diversity, and RAKE diversity affects the performance of the system.

In this paper, the authors propose a widely-linear (WL) receiver structure for multiple access interference (MAI) and jamming signal (JS) suppression in direct-sequence code-division multiple-access systems. A vector space projection (VSP) scheme is also considered to cancel the JS before detecting the desired signals. They develop a novel multiple-candidate successive interference cancellation (MC-SIC) scheme which processes two consecutive user symbols at one time to process the unreliable estimates and a number of selected points serve as the feedback candidates for interference cancellation, which is effective for alleviating the effect of error propagation in the successive interference cancellation (SIC) algorithm. WL signal processing is then used to enhance the performance of the receiver in non-circular modulation scheme. By bringing together the techniques mentioned above, a novel interference suppression scheme is proposed which combines the WL MC-SIC minimum-mean-squared error (MMSE) algorithm with the VSP scheme to suppress MAI and JS simultaneously. Simulations for binary phase shift keying modulation scenarios show that the proposed structure achieves a better MAI suppression performance compared with previously reported SIC MMSE receivers at lower complexity and a superior JS suppression performance.

This paper proposes co-channel interference cancellation / equalization methods for downlink block transmission with cyclic prefix in multi-cell environments using multiple receiving antennas and iterative least-square (LS) interference cancellation. Due to circulant structure of channel matrices in block transmission schemes with cyclic prefix, pseudo inverse matrices, which is required in the iterative LS method, can be obtained with low computational complexity and is multiplied to the received signal in an efficient manner. Computer simulation results show that the proposed iterative LS interference cancellation and equalization method can achieve almost the same bit error rate (BER) performance as an minimum mean-square-error (MMSE) approach with lower computational complexity and without noise variance estimation.

FBMC is a pivotal system in 5G, serving as a cornerstone for efficient use of available bandwidth while simultaneously meeting stringent requirements for high spectral efficiency. Notably, FBMC harnesses the power of multicarrier modulation (MC), a good alternative to orthogonal frequency division multiplexing (OFDM) technology that supports fourth-generation (4G) systems. The wireless communications field is full of challenges, the most important of which are channel estimation and interference cancellation, both of which deserve comprehensive study to increase the efficiency of data transmission. In this paper, our investigation takes a deliberate step towards the convergence of two prominent modulation models: OFDM and FBMC. We specifically contrast these modulation techniques with the intricate field of joint channel estimation and interference cancellation (JCEIC). In this research study, we take advantage of recurrent neural networks' (RNNs') efficiency as a vehicular channel to perform precise channel estimation and recovery of uncorrupted transmitted signals, thereby lowering the bit error rate (BER). Our channel estimation for a dual selective channel is based on the thoughtful placement of pilots scattered over the temporal and frequency dimensions, and is further improved by the interference cancellation method of low complexity that was selected. Our JCEIC proposal aims to integrate RNNs carefully, using the output sequences of JCEIC algorithms as useful inputs to this neural architecture. By clearly demonstrating a decrease in BER as compared to traditional approaches, it is evident that the performance of the novel approach is near to that of a perfect channel. Additionally, a comparison of the performance of FBMC and OFDM systems at various signal-to-noise ratios reveals a clear performance divide that favors the former in terms of system efficiency. The BER is restricted by FBMC to a commendable threshold of less than 0.1 at a modest 5 dB, continuing the higher trend started by its improved RNN-based channel estimate. The accuracy of channel estimation is clearly improved by this paradigm shift, and the computing complexity typical of 5G networks is also clearly reduced.