Subcarrier Multiplexing OFDM-based Radar Communication Integration

This paper derives the performance of the joint radar and communication system (JRCS). Firstly, for the radar application of the JRCS, we derive the mutual information (MI) between target and received signal in additive Gaussian noise. For communication, we derive the communication data rate that the JRCS can achieve. Then, under partial coexistence between radar and communication bands, the MI and communication data rate for the JRCS are derived. In terms of the overlap between the received radar and communication signals, the successive interference cancellation (SIC) scheme is adopted. Finally, the provided numerical results demonstrate the performances for the JRCS.

Application of LFM-CPM signal into a DFRC system based on circulating code array

Theoretical performance analysis is presented for an optical transmission system with RF subcarriers multiplexing (SCM) for radio on fiber technology considering the effect of PM-IM conversion due to Mach-zehnder modulator (MZM) and optical beat interference (OBI) generated during photodetection process. The computed bit error rate (BER) performance results show that there is significant deterioration in system BER due to OBI and PM-IM conversion and the system suffers significant power penalty at a given BER. The penalty is found to be approximately 5.8 dB, 11.0 dB, 13.5 dB, 15.0 dB, 17.0 dB for PM-IM conversion factor of -1, -2, -3, -4, -5 and 18.0 dB, 18.5 dB, 20.5 dB, 21.5 dB, 22.0 dB for number of subcarriers of 2, 4, 8, 16, 32 respectively.

This paper proposes a method to maximize the rate of reliable communication for polar codes operating on channels with memory. The channel is learned implicitly from data by optimizing a neural polar decoder (NPD). This approach enables simultaneous optimization of the code rate over the input distribution and the design of a practical coding scheme within the framework of polar codes. The proposed approach applies to scenarios where the channel model is unknown and treated as a black-box that produces output samples from input samples. We use NPDs to estimate the mutual information (MI) between the channel inputs and outputs, and optimize a parametric model of the input distribution. The methodology involves a two-phase process: a training phase and an inference phase. In the training phase, two steps are repeated iteratively. The first step optimizes the NPD to estimate the MI of the channel inputs and outputs. The second step improves the input distribution parameters by maximizing the MI estimate obtained with the NPD. In the inference phase, the optimized model is used to construct polar codes. This approach uses the Honda-Yamamoto (HY) scheme, which implements polar codes with optimized input distributions, together with list decoding. Experimental results on memoryless and finite state channels (FSCs) demonstrate the effectiveness of this approach, particularly in cases where the channel’s capacity-achieving input distribution is non-uniform. For these cases, significant improvements in MI and bit error rates (BERs) are shown over those achieved by uniform and independent and identically distributed (i.i.d.) input distributions, validating our method for block lengths up to 1024. This data-driven approach can be utilized in real-world communication systems, bridging theoretical capacity estimation and practical coding performance.

Publication in the conference proceedings of EUSIPCO, Lausanne, Switzerland, 2008

Orthogonal frequency division multiplexing (OFDM) has been widely used as radar, communication, and jamming shared waveform. To improve the power utilization and efficiency of radar, communication, and jamming integrated system, we propose an adaptive OFDM shared waveform design method. Considering the problem of jamming path propagation loss and sensitivity of frequency response error of radar and communication channels, we propose a robust OFDM shared waveform design method. Firstly, the suppressed jamming entropy model, the detection probability (Pd) of the stationary point target model, the data information rate (DIR) model with a given bit error rate (BER) are formulated. With the constraints on total power and BER, the adaptive and the robust OFDM optimization problems are formulated. Then we derive the Karush-Kuhn-Tucker (KKT) conditions of the two optimization problems and an improved greedy algorithm is proposed to solve the optimization problems, and the optimal power and bit allocation schemes for the two problems are obtained. Finally, we present several numerical results to demonstrate the effectiveness of the proposed method.

The role of the Royal Navy has changed dramatically since the end of the Cold War. Ships and personnel are now expected to fulfil a wider range of possible missions in theatres all over the world. Consequently ship's radar systems are now expected to give a high level of performance in regions that include the Middle East and the Eastern Mediterranean, despite being originally designed to operate predominately in the North Atlantic. The problem is that the local scenario and environmental conditions can dramatically affect radar system performance in two important ways. Firstly the environment can change the way that energy propagates outwards from the radar leading to large variations in target and clutter strength between different locations. Secondly these variations are often hidden by automatic threshold changes that reduce sensitivity to prevent the radar picture from becoming cluttered. This can give the false impression that the radar is operating optimally and could prevent ship's personnel from adapting their tactics to fit to the local situation. This paper outlines an updated model that is compared to real data in ducting conditions. The model is used to examine radar performance in littoral scenarios and to estimate sea state and duct strength from real radar data. The ultimate aim is to combine information collected by the ship's surveillance radar with modelling to allow ship's personnel to monitor the effect of the local environment on radar performance.

The radar system designer is constrained by limited budgets for resources such as cost, weight, prime power, and volume. Under these constraints, the designer attempts to maximize the radar system performance. After selecting the operating frequency band and the basic design approach, the primary way to improve radar performance is to increase the average radiated power (P) and the antenna aperture area (A). Search radar performance scales with the power-aperture product PA, track radar performance scales in proportion to PA/sup 2/, and fire control radar performance scales as PA/sup 3/ of PA/sup 4/. After allocating resources to all other sub-systems (e.g. computers and signal processors), the system designer must determine how to balance resource allocation between P and A. This analysis determines the optimal allocation of the critical resource that is exhausted before others. If the resource cost of P and A are linear and independent, the analysis shows that for a search radar the critical resource should be divided equally between P and A. For a track radar, one-third of the critical resource should be allocated to P and two-thirds to A. For a fire control radar, one-fourth or one-fifth of the critical resource should be allocated to P, with the remainder allocated to A. The analysis also provides results to optimally balance P and A in the case where the resource costs are non-linear functions. The appendix reviews the relationship between P, A, and radar performance.

In order to solve the problems of low utilization of transmit power and low efficiency of OFDM radar communication jamming shared signal waveform, an adaptive shared waveform optimization method is proposed. Firstly, the suppression interference entropy model, signal-to-noise ratio (SNR) and data information rate (SIR) models of shared signals are derived. Then, an adaptive OFDM shared signal waveform optimization model is established with the maximum entropy, signal-to-noise ratio and data information rate as the optimization criteria. Then, the KKT condition of the adaptive waveform is derived, and the optimal adaptive waveform is obtained by convex optimization toolkit Power distribution scheme. The results show that the designed waveform has the best jamming performance of radar communication.

Error performance of OFDM-QAM signals is analyzed for subcarrier multiplexed (SCM) fiber-optic video transmission, particularly for hybrid AM/OFDM systems. In comparison with conventional M-QAM signals, it is shown that the OFDM system provides significant performance improvements in terms of bit-error rate (BER), channel capacity, and operating range of the optical modulation depth, in the lightwave SCM environment where both the clipping impulse noise and Gaussian noise are present. As a result, the OFDM signals will introduce less interference effects on the nominal AM channels than the M-QAM signals under the same operating conditions.

The Modern Society is becoming more and more dependable on technological inventions and gadgets which are increasing on very fast rate, hence user demands for wireless communication are increasing but existing networks are not able to fulfil the high data rate requirement for such services. As high data rate wireless access can be supported by more bandwidth but due to spectral limitations, it is very expensive to increase. Hence the available bandwidth is needed to be used efficiently. Orthogonal Frequency Division Multiplexing (OFDM) has been explored as a promising interface technology to utilize the bandwidth effectively. In order to serve multiple user demands, one of the most sophisticated techniques, resource allocation technique can be integrated into the OFDMA system. For achieving higher spectral efficiency and better Quality of Service (QoS) such as capacity and Bit Error Rate (BER) a combination of MIMO and OFDMA can be used. The present paper aims at developing a MIMO-OFDMA system for downlink transmission within one single cell. As an optimization method, subcarrier allocation is used for resource allocation. Eigen Value Decomposition (EVD) is used to decompose the MIMO channel into parallel single channels. On the basis of priority of user, subcarrier selection is done by using dominant eigen channels. By comparing the static allocation method (equal subcarrier allocation with equal power) and adaptive allocation methods (adaptive subcarrier allocation with equal power) the performance of the system is evaluated.

The integration of sensing and communication (ISAC) based on optical fibers has been a key enabling technique to achieve high-speed communication while ubiquitous sensing. In this paper, to ensure the coexistence of communication signal and sensing signal in low-cost optical access networks i.e., intensity modulation/direct detection (IM/DD) based short-reach optical transmission systems, a common bias-digital subcarrier multiplexing (CB-DSCM) scheme is proposed for ISAC signal generation. To assure distributed fiber acoustic sensing (DAS) signal having high spatial resolution and longer detection distance, linear frequency modulation (LFM) pulse compression technique, biased at the null point of the modulator, is used for sensing signal generation at the transmitter, and coherent detection is employed at the receiver. Then, due to the bias voltage at null point, asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) signal is utilized to carry communication signal in the IM/DD system. Therefore, both signals can be simultaneously transmitted using the already deployed modulator, enabling integrated sensing and communication in short-reach optical transmission systems. Experimental results demonstrate that, the proposed CB-DSCM scheme can achieve a net bit rate of 3.01 Gb/s with a bit error rate (BER) as low as 6 × 10-4 over a 19.8 km fiber-optic transmission link, while it can successfully reconstruct various vibration signals with a spatial resolution of 1 m in short-reach optical transmission systems.

In this paper subcarrier and power allocation to each user at base-station maximizes the user data rates, subject to constraints on total power and bit error rate. First, each subchannel is assigned to the user with best channel-to-noise ratio for the channel, with random power distributed by water filling algorithm. The Gao's (2006) subcarrier allocation algorithm was used to calculate the power for each population in of genetic algorithm model. With the goal of minimize the overall transmit power while ensuring the fulfillment of each user's data rate and bit error rate (BER), the needed allocation is proposed through genetic search. The proposed genetic search helps fast convergence and can handle large allocations of subcarriers to users without performance degradation. The simulation results show that genetic algorithm approach will be used where complex computations are involved and near optimal solution are acceptable for optimum resource allocation

Performance improvement of hybrid subcarrier multiplexing optical spectrum code division multiplexing system using spectral direct decoding detection technique

This paper reviews the remote sensing of waves and turbulence in statically stable atmospheric layers, utilizing sodar and microwave radar echoes from the small-scale inhomogeneities in gaseous refractive index caused by localized fluctuations in temperature, humidity, and velocity. Scattering theory and sounding methodology are reviewed briefly, and the relative performance of typical radar and sodar systems compared. The main section of the paper takes the form of a summary and discussion of experimental progress since 1969, showing how the echo patterns obtained may be applied to the interpretation of multiple layering, gravity waves, internal fronts and the details of dynamic instability and the genesis of turbulence in stably stratified shear layers. In addition, methods for the measurement of the intensity of the small-scale (∼ λ/2) variability of wind, temperature and water vapor from the observed radar or sodar echo intensities, and the use of Doppler techniques for the measurement of mean velocity and turbulence are discussed.