Positioning and sensing have long been an important area of research. Recently, this field has attracted more attention due to the rapid deployment of emerging applications and next-generation communication networks. On the one hand, emerging applications like extended reality (XR) and autonomous vehicle systems need to precisely “see” the physical world, thus greatly increasing the demands on positioning and sensing technologies. Moreover, these applications also require data rate communication links, and thus technologies like cellular networks and WiFi are excellent for supporting these applications. On the other hand, with the evolution of wireless networks, positioning, and sensing have also been considered important functions of future wireless networks that can further enhance communication performance. Although existing wireless communication has achieved significant success in the past several decades, achieving satisfying positioning and sensing performance for these emerging applications remains a challenge due to the complexity of the wireless environment and the stringent performance requirements.

Positioning has recently received considerable attention as a key enabler in emerging applications such as extended reality, unmanned aerial vehicles, and smart environments. These applications require both data communication and high-precision positioning, and thus they are particularly well-suited to be offered in wireless networks (WNs). The purpose of this paper is to provide a comprehensive overview of existing works and new trends in the field of positioning techniques from both academic and standard perspectives. The paper provides a comprehensive overview of indoor positioning in WNs, covering the background, applications, measurements, state-of-the-art technologies, and future challenges. The paper outlines the applications of positioning from the perspectives of public facilities, enterprises, and individual users. We investigate the key performance indicators and measurements of positioning systems, followed by the review of the key enabler techniques such as artificial intelligence/large models and adaptive systems. Next, we discuss a number of typical wireless positioning technologies. We extend our overview beyond the academic progress, to include the standardization efforts, and finally, we provide insight into the challenges that remain. The comprehensive overview of existing efforts and new trends in the field of indoor positioning from both academic and standardization perspectives would be a useful reference to researchers in the field.

This is Part II of the double-part Special Issue (SI) on Positioning and Sensing Over Wireless Networks. The two-part SI aims to bring cutting-edge and novel contributions on positioning and sensing over wireless networks for future and emerging applications. The accepted 51 papers are arranged into eight groups: 1) fundamental performance analysis and optimization; 2) positioning and sensing with cellular networks; 3) positioning and sensing with WiFi networks; 4) positioning and sensing with emerging communication technologies; 5) positioning and sensing applications; 6) cooperative positioning and sensing; 7) reconfigurable intelligent surfaces (RIS)-assisted positioning and sensing; and 8) privacy and security. The contributions made by the papers in Part II are summarized as follows, which correspond to the last four paper groups.

We introduce algebraic machine reasoning, a new reasoning framework that is well-suited for abstract reasoning. Effectively, algebraic machine reasoning reduces the difficult process of novel problem-solving to routine algebraic computation. The fundamental algebraic objects of interest are the ideals of some suitably initialized polynomial ring. We shall explain how solving Raven's Progressive Matrices (RPMs) can be realized as computational problems in algebra, which combine various well-known algebraic subroutines that include: Computing the Gröbner basis of an ideal, checking for ideal containment, etc. Crucially, the additional algebraic structure satisfied by ideals allows for more operations on ideals beyond set-theoretic operations. Our algebraic machine reasoning framework is not only able to select the correct answer from a given answer set, but also able to generate the correct answer with only the question matrix given. Experiments on the I-RAVEN dataset yield an overall 93.2% accuracy, which significantly out-performs the current state-of-the-art accuracy of77.0% and exceeds human performance at 84.4% accuracy.

For 5G New Radio services with the requirement of high reliability and low latency, the HARQ loop can only afford one or a couple of retransmissions within the latency bound, or none at all, depending on the system configuration. In response to such stringent demand on the link adaptation algorithm, improved algorithms for predicting or estimating downlink channel conditions are desired. This paper describes the problem and proposes a solution where channel state statistics are reported by user equipment to aid the base station for more accurate downlink scheduling. Simulation results are provided to demonstrate the benefit of the new approach.

This paper presents a new method for indicating contiguous resources in the frequency domain where the granularity of frequency resource can vary depending on the size of the actual allocation. The outcome is flexible frequency domain resource allocation (FDRA) where the resource can be finely scheduled when the actual allocation is small or coarsely scheduled when the actual allocation is large. It provides a better tradeoff between scheduling flexibility and overhead reduction as compared to existing approaches. The method reduces the number of bits required to indicate the FDRA in the downlink control information (DCI) and can be applicable for future releases of 5G NR and any future generations of wireless access technologies.

A method of distributing CRC bits from a single CRC polynomial over a block of information bits for Polar codes via an interleaver to facilitate early termination and enhanced error correction is proposed and investigated. The interleaver is designed such that each CRC bit is placed in a decoding position as early as possible while keeping all the information bits that the CRC bit depends on in front of it in the successive decoding order. This allows the CRC bits to be used as dynamic frozen bits to assist surviving path selection during SC/SCL decoding to improve error performance. Furthermore, it allows the distributed CRC bits to be used for early error detection in the list decoding process and thus reduces the average decoding latency. Simulation results show that interleaved CRC can provide moderate benefits in improving error correction and reducing decoding latency through early error detection.

The Internet of Things (IoT) has emerged as one of the focal points in the evolution of cellular networks, and has motivated the introduction of several features that facilitate Machine-Type Communications (MTC) in LTE networks. These features serve the MTC goals of reduced User Equipment (UE) modem cost and complexity, Coverage Enhancement (CE) to support UEs in remote radio locations, and an improved battery lifetime. In this paper, we discuss the features specified in LTE Release 12 and Release 13 for reducing the UE modem cost up to 81% compared to the least expensive broadband LTE UE modem. Further, we describe the techniques specified in Release 13 for the CE of physical channels that carry data or control information. We provide link-level simulation results for the CE performance over various physical channels in terms of their error rates and per-user throughput.

LTE Release 13 has introduced coverage enhancement (CE) mode "CE Mode B" to support MTC deployments that require medium-to-large CE, compared to the baseline LTE coverage for voice communications. In this paper, we describe the operation of CE Mode B for the supported physical data and control channels, and study the dimensioning of this mode for each of these channels. We provide link-level simulation results for CE Mode B, which illustrate the possibility of MTC operation at a coupling loss up to 160 dB. Further, we study the achievable uplink capacity in terms of the blocking probability of new scheduling requests. Finally for a few representative scenarios, we show that the existing LTE configurations can provide sufficient uplink capacity.

This paper considers the problem of simultaneously communicating two messages, a high-security message and a low-security message, to a legitimate receiver, referred to as the security embedding problem. An information-theoretic formulation of the problem is presented. A coding scheme that combines rate splitting, superposition coding, nested binning, and channel prefixing is considered and is shown to achieve the secrecy capacity region of the channel in several scenarios. Specifying these results to both scalar and independent parallel Gaussian channels (under an average individual per-subchannel power constraint), it is shown that the high-security message can be embedded into the low-security message at full rate (as if the low-security message does not exist) without incurring any loss on the overall rate of communication (as if both messages are low-security messages). Extensions to the wiretap channel II setting of Ozarow and Wyner are also considered, where it is shown that "perfect" security embedding can be achieved by an encoder that uses a two-level coset code.

This paper considers the problem of simultaneously communicating high-security and low-security messages, referred to as the security embedding problem. An information-theoretic model is presented. A coding scheme that combines superposition coding and random binning is proposed and is shown to achieve the capacity region in several communication scenarios. As an application, it is shown that a simple scheme that combines security embedding codes and secure network coding can achieve the secrecy capacity of a parallel multi-eavesdropper wiretap channel with two reversely degraded components.

This paper discusses circular buffer rate matching (CBRM) algorithms for the turbo code in the long term evolution (LTE) of the WCDMA-based air interface. To enhance performance at high code rates, systematic bit puncturing is incorporated in conjunction with the CBRM. The RM algorithm is further optimized based on the algebraic properties of the QPP interleavers and the 8-state recursive systematic convolutional code of the LTE turbo code.

With the emergence of packet-based wireless broadband systems, work has begun on long term evolution (LTE) of the UMTS Terrestrial Radio Access and Radio Access Network aimed for commercial deployment in 2010. Goals for the evolved system include support for improved system capacity and coverage, high peak data rates, low latency, reduced operating costs, multi-antenna support, flexible bandwidth operations and seamless integration with existing systems. To reach these goals, a new design for the air interface including control channel is envisioned. This paper provides a preliminary look at an efficient downlink control channel design to reduce the overhead required to support data transmission. Initial performance results show that close to optimal system performance can be achieved with downlink control overhead of less than 14%.

The Long Term Evolution (LTE) of the WCDMA standard requires turbo decoding throughputs of up to 100 Mbps. Unfortunately, the existing WCDMA turbo interleaver does not permit an efficient high throughput implementation. The almost regular permutation (ARP) and quadratic polynomial permutation (QPP) interleavers were proposed to rectify this situation with QPP selected for LTE. In this paper, the interleavers are compared and a full suite of LTE designs and performance results for both are presented.

This work describes a family of low feedback, high performance link adaptation algorithms for multi-carrier systems. The methods include the use of the exponential effective SNR mapping (EESM) method as part of the modulation/coding selection process. The drawbacks of current link adaptation algorithms are reviewed, and means of combating the effect of Doppler and fading gain variation are proposed. In addition, a method enabling conventional SNR feedback reports to be converted to the effective SNR domain is described. This allows the effect of variable power allocation on coded BER to be more accurately estimated. Simulation results show that the proposed methods are effective.

This paper presents a high-speed "turbo-like" decoding algorithm for certain structured LDPC codes such as those adopted in IEEE 802.16e and in the draft 802.11n standards. It is shown that after a key modification, such LDPC codes may be processed as generalized repeat accumulate codes, codes which are known to support "turbo-like" decoding. A GRA-like encoder of structured LDPC codes is derived, which in turn leads to the decoding algorithm. It is also shown that the "structured" properties result in an inherent parallelism, leading to an efficient high speed decoder implementation

OFDM system-level simulations require a performance estimate for each link, but it is typically infeasible to conduct simultaneous link-level simulations for multiple users within a reasonable amount of time. Therefore, it is critical to have a simple link error probability predictor that accurately models coded OFDM performance. The exponential ESM (EESM) method was shown to be a very good link error prediction method for multi-carrier systems in the case of single transmission. Here, the EESM method is extended to cover hybrid ARQ (HARQ) techniques: Chase combining, incremental redundancy (IR) or an arbitrary combination of both. Further simplifications are introduced to greatly reduce the amount of memory necessary to utilize EESM for modeling OFDM-HARQ transmissions

The introduction of adaptive multi-rate (AMR) speech coders in wireless standards, such as GSM, imposes new challenges for forward error correction (FEC) design. Traditional FEC techniques of providing unequal error protection (UEP) may not maximize performance for a given set of design requirements, such as complexity limits. This paper introduces a new FEC technique that improves error correction performance while satisfying complexity constraints. This technique is applied to the new wideband AMR standard for a performance and complexity comparison.

This letter studies the numerical properties of log-MAP-based soft-input soft-output decoding. The ranges of the differences between the path metrics, the soft output, and the complete information are derived. Since the log-MAP algorithm is functionally dependent only upon the differences between path metrics, not their magnitudes, a module normalization technique that is automatically implemented in two's complement arithmetic can be used to accommodate overflow of the path metrics. An expression for the minimum internal data width of a soft-input soft-output decoder that employs the module normalization technique is derived. As an application, the minimum internal data width of a decoder for the turbo code used in third-generation mobile communication systems is determined.

We propose a new type-II code-combining hybrid automatic repeat request (ARQ) strategy that uses both parallel and serial concatenated convolutional codes (PCCCs and SCCCs). The ARQ technique is based on the observation that a PCCC can be represented by an equivalent punctured SCCC. The initial transmission is the PCCC. When a retransmission is requested, the system only transmits the additional parity bits that, together with the previously transmitted PCCC bits, constitute the related SCCC. Simulation results show remarkable power efficiency and throughput efficiency when using the proposed system.