The rapid proliferation of smart devices and Internet of Things (IoT) applications have brought significantly increased demands for concurrent sensing, localization and communication services. To achieve multiple functions concurrently, new unified wireless systems including integrated localization and communication (ILAC) and integrated sensing and communication (ISAC) are facing the fundamental challenge of integrative resource allocation among coexisting functions and services. In addressing this challenge, an ILAC system based on the efficient allocation of the common hardware and radio resource pool for localization and communication is proposed. A novel concept, termed Value of Service (VoS), is coined to maximize the unified performance of ILAC system for diverse service provisioning including localization accuracy and communication data rate. Furthermore, the bandwidth and temporal resource allocation problem is formulated for ILAC to maximize its VoS. Specifically, the problem is treated as a mixed-integer nonlinear problem solved by an iterative joint resource allocation (JRA) strategy. In each iteration, the resource allocation is decomposed into two steps. Firstly, the bandwidth resource is optimized with a Kelly mechanism-based continuous allocation method followed by discretization. Secondly, the temporal resource is assigned with the aid of an adaptive particle swarm optimization (PSO)-based approach. Simulation results demonstrate the significant superiority of our proposed VoS evaluation metric and JRA method in ILAC system under limited resources.

Guided scrambling (GS) is a constrained coding technique that can be used in digital communication systems to control the characteristics of the encoded sequence. In each encoding interval, a GS encoder constructs a quotient selection set with a number of codeword candidates and selects the "best" candidate to represent the source word. Relationships between candidates in the quotient selection set impact the quality of the transmitted sequence. In particular, in some applications it is desired that the quotient relationship patterns (QRPs) be periodic, and in other applications, periodic QRPs are to be avoided. QRPs are determined by the scrambling polynomial. In this correspondence, we derive the general form for scrambling polynomials that generate all periodic quotient relationship patterns.

Trellis-based error-control (EC) codes, such as convolutional or turbo codes, are integrated with guided scrambling (GS) multimode coding to generate DC-free GS-convolutional/turbo codes. On the basis of the generators of the convolutional/turbo code, we employ puncturing or flipping to ensure that the EC-coded sequences are DC-free. At the receiver, convolutional/turbo decoding is performed before GS decoding to circumvent the performance degradation that can occur when GS decoding is performed prior to EC decoding. Performance of the new DC-free GS-convolutional/turbo codes is evaluated in terms of both spectral suppression and bit error rate (BER). It is shown that the new codes can provide superior BER performance and approximately the same suppression of low frequencies as the conventional concatenation of convolutional/turbo codes and DC-free GS codes.

The complexity of conventional partial transmit sequence (PTS) increases largely with the number of subblocks. Conventional PTS requires generation of all partial transmit sequences through IFFT operations and optimization of the weighted partial transmit sequences. Previously published simplification methods only focus on simplifying this optimization process. In this paper, we propose additional techniques to reduce the complexity of PTS, including a new combining technique which we call sequence modification (SM). By use of SM, both the number of IFFT operations and the complexity of the optimization process can be significantly reduced. Our simulation results demonstrate that PTS using SM preserves the good PAPR performance of conventional PTS.

In this paper we integrate convolutional/turbo encoding with multimode encoding to generate dc-free convolutional/turbo codes. Based on the generators of error-control codes, we employ flipping or puncturing to ensure that the coded sequences are dc-balanced. At the receiver, the channel output is first decoded by a convolutional/turbo decoder (with consideration of detection when flipping is used during encoding), and then by a dc-free decoder. We show that good spectrum performance can be obtained at the cost of an increase in complexity in the encoder and that excellent bit error rate (BER) performance can be obtained particularly when source data logic values are not equiprobable.

DC-free codes and error-control (EC) codes are widely used in digital transmission and storage systems. To improve system performance in terms of code rate, bit-error rate (BER), and low-frequency suppression, and to provide a flexible tradeoff between these parameters, this paper introduces a new class of codes with both dc-control and EC capability. The new codes integrate dc-free encoding and EC encoding, and are decoded by first applying standard EC decoding techniques prior to dc-free decoding, thereby avoiding the drawbacks that arise when dc-free decoding precedes EC decoding. The dc-free code property is introduced into standard EC codes through multimode coding techniques, at the cost of minor loss in BER performance on the additive white Gaussian noise channel, and some increase in implementation complexity, particularly at the encoder. This paper demonstrates that a wide variety of EC block codes can be integrated into this dc-free coding structure, including binary cyclic codes, binary primitive BCH codes, Reed-Solomon codes, Reed-Muller codes, and some capacity-approaching EC block codes, such as low-density parity-check codes and product codes with iterative decoding. Performance of the new dc-free EC block codes is presented.

This paper investigate the extension of Golay complementary sequences to a larger family of sequences which we call multiple L-shift complementary sequences ( L 2 I ). It is well-known that the peak-to-average power ratio (PAPR) value of any Golay complementary sequence is less than or equal to 2. We show that the PAPR of each multiple L-shift complementary sequence is less than or equal to 2L. Other properties of multiple L-shift complementary sequences are also discussed.

A new class of codes with high-order spectral nulls at zero frequency is introduced. The codes, called high-order spectral-null multimode codes, are constructed through state-dependent encoding by use of the guided-scrambling coding technique, and result in efficiently coded sequences with good low-frequency characteristics.

Sum-variance is a well-known metric for assessing the performance of dc-free codes (first-order spectral-null codes), however, as we show in this paper, it is unsuitable for comparing the magnitude of spectral components of high-order spectral-null (HOSN) codes at low frequencies. In this paper, we introduce a new performance metric for evaluating the spectrum compression of arbitrarily HOSN codes around zero frequency; we call this metric the low-frequency spectrum weight (LFSW). We show that the asymptotic low-frequency spectral components of Kth-order spectral-null codes (K/spl ges/1) are exclusively determined by the order K and the LFSW, and that the LFSW equals the zero-frequency value in the spectrum of the corresponding sequence of Kth-order running digital sum values. We derive this result for symbol-by-symbol encoding, and then extend it to block HOSN codes. We then derive a closed-form expression for the LFSW of HOSN codes constructed through state-independent encoding. Closed-form expressions for LFSW of first-order zero-disparity codes and for the asymptotic LSFW of maxentropic dc-free sequences are also given.

Selective mapping (SLM) and partial transmit sequences (PTS) are two approaches that significantly improve the statistics of the peak-to-average power ratio of an orthogonal frequency-division multiplexing signal. Guided scrambling (GS) is a multimode coding technique that is used to constrain the characteristics of encoded sequences in digital transmission and recording systems. We demonstrate the similarity of these techniques, and integrate GS coding with SLM and PTS. Our proposed GS-SLM and GS-PTS techniques result in very good PAPR performance with little error extension, and do not require transmission of side information.

We introduce a new method for enumerating codewords that can be applied to DC/sup 2/-constrained channels. Based on this method, two efficient algorithms for evaluating the number of codewords with specified characteristics are developed. Computer calculation results show that these algorithms are significantly more computationally efficient than other techniques developed to date.