Intelligent reflecting surface (IRS)-aided wireless communication is attracting interest as a technology that can improve communication quality and coverage in high-frequency bands such as millimeter waves. The proper control of the IRS requires channel estimation for each element, which reduces communication efficiency owing to a channel estimation overhead. Furthermore, when an IRS is used in multiple-input multiple-output (MIMO) systems, the overhead becomes larger than that of single-input single-output (SISO) systems. To control the IRS according to the beamforming of the transmitter, the IRS must cooperate with the transmitter. This requires a channel estimation of the number of elements for each transmitter antenna. Therefore, a standalone IRS that does not require a connection or channel estimation for cooperation between the IRS and transmitter is required. Recently, standalone IRS control in SISO systems using camera images has been proposed. In this paper, we propose a method to adapt this concept to transmitter beamforming. Our method achieves a standalone IRS by predicting the channel based on the 3D position estimated by detecting the user in the camera image and then applying the reflection coefficients corresponding to the estimated beamforming vectors. Numerical experiments confirm that the proposed method can control the IRS with only a slight degradation in communication quality.

For wireless communication in the high-frequency band, Intelligent Reflecting Surface (IRS) has been developed to expand the coverage. To appropriately control the reflection pattern of each element in the IRS, deep learning (DL)-based spectral efficiency predictions have been proposed. The conventional method performs prediction from the partially estimated channel at a single point in time. However, since the movement of wireless terminals is spatially continuous, the accuracy can be improved using past estimated channels. Therefore, in this paper, we propose a prediction method that considers the movement of wireless terminals by treating the estimated channel as time-series data. Furthermore, we apply a long short-term memory network to capture the time-series nature efficiently. The numerical experiments show that the proposed method can achieve high spectral efficiency even with smaller training samples than the conventional method.

We construct linear codes over odd prime fields for correcting two-dimensional (2-D) Lee-errors on the hexagonal signal constellations. They are obtained by puncturing and enlarging either RS codes or BCH codes. We introduce 2-D Lee-weight on the hexagonal constellations in the same way as the method presented by the first author in ISIT’19, and propose an effective and efficient method for correcting Lee-errors of small weight. The concept of value-locator of an error, which was introduced implicitly by K. Nakamura in the late 1970s and early 1980s and inherited to the ISIT’19 paper, is a key for decoding Lee-error-correcting codes. Our method is based on the Buchberger algorithm for finding Gröbner bases of ideals in the multivariate polynomial ring. A result of simulations shows that our method works well for correcting Lee-errors of small weight.

The multipoint codes from algebraic curves are a broad class of algebraic geometry codes derived from algebraic functions, which have multiple poles/zeros on their defining curves. Each of them is defined as either a primal code or a dual code. The dual one-point codes which are viewed as a subclass can be decoded efficiently up to the Feng-Rao bound by using the Berlekamp-Massey-Sakata (BMS) algorithm with majority logic. Since a primal code is equivalent to a dual code, one can decode as either of them, while their decoding methods are different. Recently, we published a fast method for decoding primal multipoint codes from curves based on the vectorial BMS algorithm. But, that is neither for dual codes nor up to the Goppa bound dGoppa. Although we can guarantee theoretically that every error vector of weight only up to (1/2)(dGoppa- g) can be corrected, where the integer g is the genus of the defining curve, the simulation shows that the method can correct most error patterns of weight up to (1/2)dGoppa. In this paper we present a fast method for decoding dual multipoint codes from algebraic curves up to the Kirfel-Pellikaan bound, based on the vectorial BMS algorithm with majority logic, and show that algebraic geometry codes from generic algebraic curves can be decoded up to the Goppa bound efficiently. Similar to the case of one-point codes, the computational complexity of decoding is O(a1n2), where the integer a1 is the minimum nonzero pole order of algebraic functions on the defining curve and the integer n is the code length, and in particular, O(n(7/3)) for Hermitian codes. This complexity is less than the complexity O(a1gn2) of Lee's method for decoding dual multipoint codes as a unique alternative.

Multipoint codes are a broad class of algebraic geometry codes derived from algebraic functions, which have multiple poles and/or zeros on an algebraic curve. Thus, they are more general than one-point codes, which are an important class of algebraic geometry codes in the sense that they can be decoded efficiently using the Berlekamp-Massey-Sakata algorithm. We present a fast method for decoding multipoint codes from a plane curve, particularly a Hermitian curve. Our method with some adaptation can be applied to decode multipoint codes from a general algebraic curve embedded in the N-dimensional affine space FqNover a finite field Fq, so that those algebraic geometry codes can be decoded efficiently if the dimension N of the affine space, including the defining curve is small.

Multipoint codes are a broad class of algebraic geometry codes derived from algebraic functions which have multiple poles on their defining curves. Thus, they are more general than one-point codes which are an important class of algebraic codes in the sense that they can be decoded efficiently by using the BMS algorithm. In this paper we present a fast decoding method of multipoint codes from algebraic curves. Since algebraic geometry codes from algebraic curves are essentially the same as multipoint codes, this means that almost all algebraic geometry codes can be decoded efficiently.

In this paper, we propose a class of regular LDPC codes from a cyclic difference family, which is a kind of combinatorial design. These LDPC codes have no 4-cycles, i.e., cycles of length 4. We clarify the conditions on which these codes with column weight 3 have no 6-cycles and discuss their minimum distance. Finally, we show the performance of the proposed codes with high rates and moderate lengths