Spectrum-Sharing Transmission Capacity with Interference Cancellation

The efficiency of spectrum sharing can be improved by interference suppression and/or cancellation. This paper analyzes the performance of spectrum sharing networks with interference cancellation (IC) based on the spectrum-sharing transmission capacity (S-TC), defined as the number of successful transmissions per unit area while guaranteeing all target outage probabilities of spectrum-sharing systems. The effectiveness of IC can be characterized by the coefficient of cancellation (CoC) and a specific CoC for strong interferer cancellation (S-IC) method is derived. It is verified that the performance of S-IC is affected solely by system parameters of its own system and the S-TC region can increase in various forms depending on CoCs, which should be considered in analysis of spectrum-sharing efficiency.

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.

In this paper a method for interference detection and cancellation for automotive radar systems is proposed. With the growing amount of vehicles equipped with radar sensors, interference mitigation techniques are getting more and more important to maintain good interoperability. Based on the time domain signal of a 76 GHz chirp sequence radar the interfering signals of FMCW radar sensors are identified. This is performed by image processing methods applied to the time-frequency-image. With the maximally stable extremal regions algorithm the interference pattern in the signal is identified. Once the disturbed samples are known they are zeroed. To avoid any ringing effects in the processed radar image the neighborhood of affected samples is smoothed using a raised cosine window. The effectiveness of the proposed method is demonstrated on real world measurements. The method reveals weak scattering centers of the vehicle, which are occluded by interference otherwise.

Nonlinear interference cancellation multiuser detection algorithms have less BER and are less complex than linear multiuser detection methods. We present a hybrid switched mode detector that uses existing interference cancellation methods i.e. Parallel Interference Cancellation (PIC) and Successive Interference cancellation (SIC) based on channel conditions. This proposed detector takes decisions based on number of users on the channel and switches either to SIC method or PIC method. The switching mechanism is exploited by performance complexity tradeoff between matched filter detector and nonlinear interference cancellation methods.

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.

The wide application of digital radio communication systems in recent years has resulted in increasing demands for allocated frequencies and, due to the overcrowded spectrum, interference has become a crucial problem. In many cases, such interference appears in the upper sideband or in the lower sideband of the useful signal. In the present paper a binary PSK communication system with interference in either the upper or the lower sideband is considered and a method of interference cancellation is proposed for the Costas loop widely used in PSK receivers. Experiments are conducted to demonstrate the efficiency of this method. The results show that the maximum cancellation with a simple circuit added to the Costas loop is 23 dB if Af (the difference between the frequencies of the PSK carrier and the interfering signal) is above 0.3 fβ (fβ the data bit rate). At the same time, the bit error rate in the digital signal is greatly improved. Also, with respect to the impairment due to jitter caused by interference, the performance of the Costas loop is practically unchanged within the specification range of an ordinary Costas loop. The advantages of the present method are that the circuit is simple, it is stable because there is no feedback in the interference cancellation part and the cancellation is effective even for interfering signals of unknown δf.

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.

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.

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.

A method of interference cancellation using adaptive antenna arrays is investigated. A proposal for an adaptive antenna array is presented where the number of antenna sensors is minimized. The performance of both the proposed scheme and the ordinary one are compared through computer simulations. The effects of the number of array elements and interference to signal ratio (ISR) on the performance of the adaptive interference canceller is evaluated. It is found that the proposed scheme of the adaptive antenna array exhibits a better performance than the ordinary adaptive antenna array.

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.

In this work, a successive four-stage interference cancellation model to unwrap and remove two co-channel interference signals is introduced and successfully tested. This model utilizes the second order statistics of the cochannel interference signals in an interference limited communication environment for interference cancellation. In this model, interferers and the signal of interest (SOI) are considered as multiple inputs of a multiple-input multiple output (MIMO) system. Therefore, MIMO equalizers and blind MIMO channel estimator are employed for the corresponding tasks. At any stage of equalization in this model, a single signal is equalized and recovered. Later, a replica of the captured signal is cancelled from the received signal mixture. The remaining signal is fed to the next stage for equalization. The benefit of using this scheme is mainly improving the quality of the SOI by re-equalizing after interferers are completely removed. In the results section, 16 dB interference cancellation gain is shown where interferers are as strong as signal (SIR=O) and SNR is 30 dB. A Rayleigh fading (iid) channel is used for simulation.

One of the candidate methods for new generation communication systems is orthogonal frequency division multiplexing with offset quadrature amplitude modulation (OFDM/OQAM). Because of its unique feature "intrinsic interference", new channel estimation methods have been developed for OFDM/OQAM. One of these is the interference cancellation method (ICM) which aims to eliminate the intrinsic interference. In the first studies related with ICM in the literature, "isotropic orthogonal transformation algorithm" (IOTA) was used as the waveform. However, these methods are valid only for isotropic waveforms. In this study, a new ICM preamble which suitable for both isotropic and anisotropic waveforms is proposed and the relation between isotropy of waveforms and ICM is discussed. The performance of the method against noise and peak to average power ratio (PAPR) of the method are examined via the simulations.

In Single Frequency Networks, the effect of intersymbol interference (ISI) and inter-carrier interference (ICI) is great due to the delay spread of wireless channels is much longer than a cyclic prefix (CP). The performance of OFDM systems is degenerating seriously. This paper discusses a receiver design based on the implementation of a Decision Feed-back Equalizer (DFE). The proposed DFE receiver incorporates a Parallel Interference Canceller (PIC) as its feed-forward filter. The result shows that in long time delay or more serious fading multi-path, the proposed receiver has better performance for canceling ICI and ISI compared with the conventional OFDM receiver.

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.