Computer Science

The millimeter wave (mmWave) communication has drawn intensive attention with abundant band resources. In this paper, we consider the popular content distribution (PCD) problem in the mmWave vehicular network. In order to offload the communication burden of base stations (BSs), vehicle-to-vehicle (V2V) communication is introduced into the PCD problem to transmit contents between on-board units (OBUs) and improve the transmission efficiency. We propose a full-duplex (FD) cooperative scheme based on coalition formation game, and the utility function is provided based on the maximization of the number of received contents. The contribution of each member in the coalition can be transferable to its individual profit. While maximizing the number of received contents in the fixed time, the cooperative scheme also ensures the individual profit of each OBU in the coalition. We evaluate the proposed scheme by extensive simulations in mmWave vehicular networks. Compared with other existing schemes, the proposed scheme has superior performances on the number of possessed contents and system fairness. Besides, the low complexity of the proposed algorithm is demonstrated by the switch operation number and CPU time.

Distributed computation is a framework used to break down a complex computational task into smaller tasks and distributing them among computational nodes. Erasure correction codes have recently been introduced and have become a popular workaround to the well known "straggling nodes" problem, in particular, by matching linear coding for linear computation tasks. We observe that decoding tends to amplify the computation "noise", i.e., the numerical errors at the computation nodes. We use noise amplification as a performance measure to compare various erasure-correction codes, and in particular polynomial codes (which Reed-Solomon codes and other popular codes are a subset of). We show that noise amplification can be significantly reduced by a clever selection of the sampling points and powers of the polynomial code.

We consider codes for channels with extreme noise that emerge in various low-power applications. Simple LDPC-type codes with parity checks of weight 3 are first studied for any dimension m?��?. These codes form modulation schemes: they improve the original channel output for any SNR> ?? dB (per information bit) and gain 3 dB over uncoded modulation as SNR grows. However, they also have a floor on the output bit error rate (BER) irrespective of their length. Tight lower and upper bounds, which are virtually identical to simulation results, are then obtained for BER at any SNR. We also study a combined scheme that splits m information bits into b blocks and protects each with some polar code. Decoding moves back and forth between polar and LDPC codes, every time using a polar code of a higher rate. For a sufficiently large constant b and m?��? , this design yields a vanishing BER at any SNR that is arbitrarily close to the Shannon limit of -1.59 dB. Unlike other existing designs, this scheme has polynomial complexity of order mlnm per information bit.

In this paper, combinatorial quantitative group testing (QGT) with noisy measurements is studied. The goal of QGT is to detect defective items from a data set of size n with counting measurements, each of which counts the number of defects in a selected pool of items. While most literatures consider either probabilistic QGT with random noise or combinatorial QGT with noiseless measurements, our focus is on the combinatorial QGT with noisy measurements that might be adversarially perturbed by additive bounded noises. Since perfect detection is impossible, a partial detection criterion is adopted. With the adversarial noise being bounded by d n =?( n δ ) and the detection criterion being to ensure no more than k n =?( n κ ) errors can be made, our goal is to characterize the fundamental limit on the number of measurement, termed \emph{pooling complexity}, as well as provide explicit construction of measurement plans with optimal pooling complexity and efficient decoding algorithms. We first show that the fundamental limit is 1 1??δ n logn to within a constant factor not depending on (n,κ,δ) for the non-adaptive setting when 0<2δ?��?1 , sharpening the previous result by Chen and Wang [1]. We also provide an explicit construction of a non-adaptive deterministic measurement plan with 1 1??δ n log 2 n pooling complexity up to a constant factor, matching the fundamental limit, with decoding complexity being o( n 1+? ) for all ?>0 , nearly linear in n , the size of the data set.

This paper analyzes the problem of common randomness (CR) generation from correlated discrete sources aided by unidirectional communication over Single-Input Single-Output (SISO) slow fading channels with additive white Gaussian noise (AWGN) and arbitrary state distribution. Slow fading channels are practically relevant for wireless communications. We completely solve the SISO slow fading case by establishing its corresponding outage CR capacity using our characterization of its channel outage capacity. The generated CR could be exploited to improve the performance gain in the identification scheme. The latter is known to be more efficient than the classical transmission scheme in many new applications, which demand ultra-reliable low latency communication.

Inspired by compressive sensing principles, we propose novel error control coding techniques for communication systems. The information bits are encoded in the support and the non-zero entries of a sparse signal. By selecting a dictionary matrix with suitable dimensions, the codeword for transmission is obtained by multiplying the dictionary matrix with the sparse signal. Specifically, the codewords are obtained from the sparse linear combinations of the columns of the dictionary matrix. At the decoder, we employ variations of greedy sparse signal recovery algorithms. Using Gold code sequences and mutually unbiased bases from quantum information theory as dictionary matrices, we study the block error rate (BLER) performance of the proposed scheme in the AWGN channel. Our results show that the proposed scheme has a comparable and competitive performance with respect to the several widely used linear codes, for very small to moderate block lengths. In addition, our coding scheme extends straightforwardly to multi-user scenarios such as multiple access channel, broadcast channel, and interference channel. In these multi-user channels, if the users are grouped such that they have similar channel gains and noise levels, the overall BLER performance of our proposed scheme will coincide with an equivalent single-user scenario.

While Doppler resilient complementary waveforms have previously been considered to suppress range sidelobes within a Doppler interval of interest in radar systems, their capability of Doppler resilience has not been fully utilized. In this paper, a new construction of Doppler resilient complementary waveforms based on a null space is proposed. With this new construction, one can flexibly include a specified Doppler interval of interest or even an overall Doppler interval into a term which results in range sidelobes. We can force this term to zero, which can be solved to obtain a null space. From the null space, the characteristic vector to control the transmission of basic Golay waveforms, and the coefficients of the receiver filter for Golay complementary waveform can be extracted. Besides, based on the derived null space, two challenging non-convex optimization problems are formulated and solved for maximizing the signal-to-noise ratio (SNR). Moreover, the coefficients of the receiver filter and the characteristic vector can be applied to fully polarimetric radar systems to achieve nearly perfect Doppler resilient performance, and hence fully suppress the inter-antenna interferences.

This paper proposes a beamforming method under a per-antenna power constraint (PAPC). Although many beamformer designs with the PAPC need to solve complex optimization problems, the proposed complete power reallocation (CPR) method can generate beamformers with excellent performance only with linear operations. CPR is designed to have a simple structure, making it highly flexible and practical. In this paper, three CPR variations considering algorithm convergence speed, sum-rate maximization, and robustness to channel uncertainty are developed. Simulation results verify that CPR and its variations satisfy their design criteria, and, hence, CPR can be readily utilized for various purposes.

The problem of solving explicitly the equation P a (X):= X q+1 +X+a=0 over the finite field $\GF{Q}$, where Q= p n , q= p k and p is a prime, arises in many different contexts including finite geometry, the inverse Galois problem \cite{ACZ2000}, the construction of difference sets with Singer parameters \cite{DD2004}, determining cross-correlation between m -sequences \cite{DOBBERTIN2006} and to construct error correcting codes \cite{Bracken2009}, cryptographic APN functions \cite{BTT2014,Budaghyan-Carlet_2006}, designs \cite{Tang_2019}, as well as to speed up the index calculus method for computing discrete logarithms on finite fields \cite{GGGZ2013,GGGZ2013+} and on algebraic curves \cite{M2014}. Subsequently, in \cite{Bluher2004,HK2008,HK2010,BTT2014,Bluher2016,KM2019,CMPZ2019,MS2019,KCM19}, the $\GF{Q}$-zeros of P a (X) have been studied. In \cite{Bluher2004}, it was shown that the possible values of the number of the zeros that P a (X) has in $\GF{Q}$ is 0 , 1 , 2 or p gcd(n,k) +1 . Some criteria for the number of the $\GF{Q}$-zeros of P a (x) were found in \cite{HK2008,HK2010,BTT2014,KM2019,MS2019}. However, while the ultimate goal is to explicit all the $\GF{Q}$-zeros, even in the case p=2 , it was solved only under the condition gcd(n,k)=1 \cite{KM2019}. In this article, we discuss this equation without any restriction on p and gcd(n,k) . In \cite{KCM19}, for the cases of one or two $\GF{Q}$-zeros, explicit expressions for these rational zeros in terms of a were provided, but for the case of p gcd(n,k) +1 $\GF{Q}-$ zeros it was remained open to explicitly compute the zeros. This paper solves the remained problem, thus now the equation X p k +1 +X+a=0 over $\GF{p^n}$ is completely solved for any prime p , any integers n and k .

Dual-functional radar-communication (DFRC) is a promising new solution to simultaneously probe the radar target and transmit information in wireless networks. In this paper, we study the joint optimization of transmit and receive beamforming for the DFRC system. Specifically, the signal to interference plus noise ratio (SINR) of the radar is maximized under the SINR constraints of the communication user (CU), which characterizes the optimal tradeoff between radar and communication. In addition to simply using the communication signal for target probing, we further consider to exploit dedicated probing signals to enhance the radar sensing performance. We commence by studying the single-CU scenario, where a closed-form solution to the beamforming design problem is provided. It is then proved that a dedicated radar probing signal is not needed. As a further step, we consider a more complicated multi-CU scenario, where the beamforming design is formulated as a non-convex quadratically constrained quadratic programming. The optimal solutions are obtained by applying semidefinite relaxation with guaranteed rank-1 property. It is shown that under the multi-CU scenario, the dedicated probing signal should be employed to improve the radar performance at the cost of implementing an additional interference cancellation at the CU. Finally, the numerical simulations are provided to verify the effectiveness of the proposed algorithm.