Random access sensor networks: Field reconstruction from incomplete data

Random access channel is incorporated in IEEE 802.16 WiMAX system to transport contention-based messages in the uplink, such as bandwidth requests generated by best effort applications, from mobile stations (MSs) to the base station(BS). Regarding the packet transmissions in the random access channel, delay, throughput and power consumption are usually considered as major performance metrics. We propose an enhanced power calibration protocol to optimize the system performance in terms of channel access delay, system throughput and MS transmit power consumption. Optimal selection of power levels is formulated in order to maximize the achievable throughput while being subject to power consumption constraint of mobile stations. Our scheme can substitute the random backoff mechanism in the current the WiMAX uplink random access channel, as it can accomplish a significantly improved access delay performance without an increment of design complexity. Simulations are conducted to validate our protocol and confirm its performance superiority as compared to the random channel access method used in the current WiMAX.

We perform a new analysis of the performance of the wideband code-division multiple access (W-CDMA) randomized slotted-offset random access channel (RAC) with Nakagami-m fading and compare it with that of a comparable randomized slotted-ALOHA-based RAC. Previously, it was shown that the W-CDMA RAC is fast, robust and simple to implement (see Esmailzadeh, R. and Gustafsson, M., Proc. 1997 IEEE ICUPC Conf, p.43-7, 1997). However, it was assumed that any random access packet arrival events involving multiple packets from cochannel mobile stations would result in lost packets. Closed-form equations are developed for the collision process of the arriving random access packets in slotted-offset and slotted-ALOHA RACs. An analysis is developed of the signal-to-interference-and-noise ratio of a packet involved in a multipacket DS-CDMA collision with a generalized Nakagami fading channel and diversity reception at the base station. A closed-form equation is developed for the bit error rate and packet throughput of the slotted-offset- and slotted-ALOHA-based RACs. The results of the analysis show that considerable improvement in the RAC performance can be achieved when multiple arrival collisions, on the same timeslot and with the same signature code, are partially resolved. The results also show the RAC's sensitivity to fading severity, packet E/sub b//N/sub 0/, spreading gain and number of base station receive selection diversity antennas. Compared to the randomized slotted-ALOHA designs, W-CDMA RAC performs as well in light fading conditions and slightly worse in severe fading conditions.

Massive Machine-Type Communications using LTE networks is the focus of this work aimed at realization of future Internet of Things (IoT) paradigm. Random Access Channel is the bottleneck in random access procedure which is designed for low-rate HTC connections. In MTC, when there are a large number of devices, congestion occurs in Random Access Channel. Access Class Barring (ACB) and preamble slicing are two main approaches proposed to control RACH congestion. These schemes have limited improvements over the base approach. In this paper, we propose a complementary approach that can be used in conjunction with these methods. Our approach is based on the concept of local relays and spatial preamble reuse. Assuming random selection of preambles by the devices, we developed a heuristic to select a set of local relays to act as an aggregator node for random access requests of the devices in its vicinity. The relays perform random access procedure on behalf of their members to eNodeB. The simulations show that using RACH relays reduces preamble collisions and hence is a promising technique to scale and move up the random access success rate.

To support a high density of mobile devices and its connections by means of rapid increase of mobile devices as well as small cells, various studies related to random access such as the random access load, better uplink resource utilization and interference among random access attempts have been developed for enhanced long-term evolution (LTE) system and 5G communication technology. In this paper, we discuss about the technical issues of random access resource configuration in time division duplex (TDD) mode and propose an improved method of it to make better uplink resource utilization on frequency domains and to minimize interference among random access attempts for physical random access channel (PRACH) resource allocation point of view, but it can also easily extend the LTE system. The proposed method is compared with LTE TDD PRACH configuration method through theoretical analysis. It shows that the proposed method provides better resource utilization for PRACH and physical uplink shared channel resources (PUSCH), allows flexible resource utilization in uplink scheduling, and is intuitive and effective in cell deployment with random access channel optimization in terms of random access resource configuration.

Random access channel (RACH) procedures in modern wireless communications are generally based on multi-channel slotted-ALOHA, which can be optimized by flexibly organizing devices' transmission and retransmission. However, due to the lack of information about the traffic generation statistics and the occurrence of random collision, optimizing RACH in an exact manner is generally challenging. In this article, we first summarize the general structure of optimization for different RACH schemes, and then review existing RACH optimization methods based on machine learning (ML) and non-ML techniques. We demonstrate that the ML-based methods can better optimize RACH schemes compared to non-ML-based methods due to their capability in solving high-complexity long-term optimization problems. To further improve the RACH performance, we introduce a decoupled learning strategy (DLS) for access control optimization, which individually executes two sub-tasks: traffic prediction and access control configuration. In detail, the traffic prediction relies on an online supervised learning method adopting recurrent neural networks that can accurately capture traffic statistics over consecutive frames, while the access control configuration uses either a non-ML-based controller or a cooperatively trained deep reinforcement learning (DRL)-based controller selected depending on the complexity of different random access schemes. Numerical results show that the DLS optimizer considerably outperforms conventional DRL optimizers in terms of higher training efficiency and better access performance.

Random access channels (RACHs) in cellular networks are normally designed for Poisson-distributed arrivals with a constant rate. Unexpected bursty arrivals may result in severely collisions in RACHs and thus, degrade users' service qualities. This paper presents an analytical model to investigate the transient behavior of the RACHs with bursty arrivals generated in a specific time interval in OFDMA wireless networks. The proposed model considers the effect of new arrivals and the real-world implementation constraints of the OFDMA random access procedure such as periodic access characteristic, uniform random backoff policy, and power-ramping effect. The average number of contending and success mobile stations (MSs) in each random-access slot are then derived using the proposed model. The accuracy of the proposed model was verified through computer simulations and the results show the accuracy of the analysis.

The emergence of networks of many devices in the context of cyber-physical systems motivates novel solutions for communication over random access channels. Currently deployed random access protocols attempt to avoid collisions, and target the performance of a scheduled multiple access system (a strategy known to be only suboptimal from the information-theoretic perspective). In contrast, in this paper, we allow collisions among the transmissions of different users. We consider code design for random access channels with erasures in which the number of users in each frame is unknown at the transmitters but known at the receiver, and we present a two-layer coding architecture for joint contention resolution and erasure correction. For random LDPC codes based on this scheme, the density evolution is asymptotically analyzed, which enables optimized code design for maximized throughput with constrained outage. The results demonstrate that the proposed low-complexity scheme approaches the outage capacity of the random access channel with erasures when the average number of active users is small.

In the high performance radio access networks, the number of random access channels can be used for mobile stations to transmit their bandwidth requests in contention mode via multiple random access. In this paper a collision reduced random access scheme based on m-art split algorithm in the centralized medium access control protocol is presented. In this method the splitting algorithm is used in two fold. On one hand the whole random access channels are exclusively separated into two parts; one is for initial contention where only initial access mobile stations can be served and the other is for retransmit contention where the mobile stations whose initial random access was not successful can join for their retransmission. On the other hand the m-ary split algorithm applied in the retransmit contention area to resolve the collisions. By doing so the proposed scheme achieves considerably greater performance in terms of maximum throughput, mean access delay, and delay jitter, which is one of the important criteria for real-time traffic. Through numerical examples and computer simulations the effect of the various parameters of the algorithm, initial number of random access report(s) and the split size m, on the system performance is examined.

Orthogonal frequency-division multiple access (OFDMA) systems are considered promising candidates for implementing next-generation wireless communication systems. They provide multiple channels that can be accessed via random access schemes. However, traditional random access schemes could result in an excessive amount of access delay. To address this issue, we develop a fast retrial scheme that is based on slotted Aloha and exploits the structure of OFDMA. A salient feature of this scheme is that when collisions occur instead of retrials occuring randomly in time, they occur randomly in frequency, i.e., the scheme randomly selects the subchannels for retrial. To further achieve fast access, retrials are designed to follow the 1-persistent type, i.e., no exponential backoff. To achieve the maximum throughput, we limit the maximum number of allowed retrials according to the load condition. We also consider the issue of designing for an appropriate reuse factor for random access channels in order to overcome the intercell interference problem in OFDMA multicell environments. Our finding is that full sharing, i.e., a reuse factor of one, performs best for given random access channels. Through analysis and simulation, we confirm that our fast retrial algorithm has the advantage of high throughput and low access delay, and the full sharing policy for random access channels shows high throughput as well as low collision.

This paper addresses self-optimization of the random access channel (RACH) in the Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE). Ensuring satisfactory random access (RA) performance in terms of access delay (AD) is crucial for reducing the delays associated with initial access and handovers. The feasibility of self-optimization is investigated by means of simulations, where the coupling between several parameters and the RACH performance in terms of AD is provided. We present two candidate feedback control algorithms that automatically adjust key RACH parameters to meet specified AD targets.

Random access channel (RACH) is usually used for initial channel access, bandwidth request, etc. In this paper, we analyze the throughput and access delay performance of the RACH in an orthogonal frequency division multiple access (OFDMA) system. A closed-form expression of the RACH throughput is presented and its mean access delays under both binary exponential and uniform backoff policies have also been derived. Moreover, to further improve the utilization of RACH in an OFDMA system, we propose a novel message transmission scheme in a shared RACH. The message in the proposed scheme can be sent implicitly in the cyclic-shifted preambles which make the transmission much more reliable in a contention based RACH. Meanwhile, performance of the preamble detection has also been improved by the redundant information conveyed in messages. Finally, simulation results will demonstrate performance gains of the proposed scheme.

NarrowBand-Internet of Things (NB-IoT) is a new 3GPP radio access technology designed to provide better coverage for Low Power Wide Area (LPWA) networks. To provide reliable connections with extended coverage, a repetition transmission scheme and up to three Coverage Enhancement (CE) groups are introduced into NB-IoT during both Random Access CHannel (RACH) procedure and data transmission procedure, where each CE group is configured with different repetition values and transmission resources. To characterize the RACH performance of the NB-IoT network with three CE groups, this paper develops a novel traffic-aware spatio-temporal model to analyze the RACH success probability, where both the preamble transmission outage and the collision events of each CE group jointly determine the traffic evolution and the RACH success probability. Based on this analytical model, we derive the analytical expression for the RACH success probability of a randomly chosen IoT device in each CE group over multiple time slots with different RACH schemes, including baseline, back-off (BO), access class barring (ACB), and hybrid ACB and BO schemes (ACB&BO). Our results have shown that the RACH success probabilities of the devices in three CE groups outperform that of a single CE group network but not for all the groups, which is affected by the choice of the categorizing parameters.This mathematical model and analytical framework can be applied to evaluate the performance of multiple group users of other networks with spatial separations.

In this paper, the problem of random access contention between machine type devices (MTDs) in the uplink of a wireless cellular network is studied. In particular, the possibility of forming cooperative groups to coordinate the MTDs’ requests for the random access channel (RACH) is analyzed. The problem is formulated as a stochastic coalition formation game in which the MTDs are the players that seek to form cooperative coalitions to optimize a utility function that captures each MTD’s energy consumption and time-varying queue length. Within each coalition, an MTD acts as a coalition head that sends the access requests of the coalition members over the RACH. One key feature of this game is its ability to cope with stochastic environments in which the arrival requests of MTDs and the packet success rate over RACH are dynamically time-varying. The proposed stochastic coalitional game is composed of multiple stages, each of which corresponds to a coalitional game in stochastic characteristic form that is played by the MTDs at each time step. To solve this game, a novel distributed coalition formation algorithm is proposed and shown to converge to a stable MTD partition. Simulation results show that, on the average, the proposed stochastic coalition formation algorithm can reduce the average fail ratio and energy consumption of up to 36% and 31% for a cluster-based distribution of MTDs, respectively, compared with a noncooperative case. Moreover, when the MTDs are more sensitive to the energy consumption (queue length), the coalitions’ size will increase (decrease).

A packet aggregation method is proposed in this paper to lower the packet collision rate when the random access channel is used for machine type communications (MTC) uplink channel access in LTE. With the proposed packet aggregation method, a UE triggers random access when the aggregated packets in the buffer reaches the given threshold. However, this method reduces the packet collision rate at the expense of an extra latency which is used to aggregate certain amount of packets. Therefore, the tradeoff should carefully be selected between packet loss rate reduction and extra channel access latency. In this paper, we derive the packet loss rate and channel access latency as functions of amount of aggregated packets using a Semi-Markov chain model. With the derived results, the optimal amount of aggregated packets which satisfies the packet loss requirement and keeps the latency as small as possible can be found, which is verified through simulations.

Random access channels (RACHs) in cellular networks are normally designed for Poisson-distributed arrivals with a constant rate. Unexpected bursty arrivals may result in severe collisions in RACHs and thus degrade users' service qualities. This paper presents an analytical model for investigating the transient behavior of the RACHs with bursty arrivals generated in a specific time interval for orthogonal frequency-division multiple access (OFDMA) wireless networks. The proposed model has considered the implementation details of the OFDMA random access procedure (such as periodic access characteristic, uniform random backoff policy, and power-ramping effect) and the effect of new arrivals. The performance metrics of collision probability, success probability, and average access delay and the cumulative distribution function of the number of preamble transmissions and access delay for the successfully accessed mobile station are then derived based on the analytical model. The accuracy of the proposed analytical model was verified through computer simulations, and the results show the effectiveness of the proposed model.