SAI: safety application identifier algorithm at MAC layer for vehicular safety message dissemination over LTE VANET networks

Vehicular safety applications have much significance in preventing road accidents and fatalities. Among others, cellular networks have been under investigation for the procurement of these applications subject to stringent requirements for latency, transmission parameters, and successful delivery of messages. Earlier contributions have studied utilization of Long-Term Evolution (LTE) under single cell, Friis radio, or simplified higher layer. In this paper, we study the utilization of LTE under multicell and multipath fading environment and introduce the use of adaptive awareness range. Then, we propose an algorithm that uses the concept of quality of service (QoS) class identifiers (QCIs) along with dynamic adaptive awareness range. Furthermore, we investigate the impact of background traffic on the proposed algorithm. Finally, we utilize medium access control (MAC) layer elements in order to fulfill vehicular application requirements through extensive system-level simulations. The results show that, by using an awareness range of up to 250 m, the LTE system is capable of fulfilling the safety application requirements for up to 10 beacons/s with 150 vehicles in an area of 2 × 2 km2. The urban vehicular radio environment has a significant impact and decreases the probability for end-to-end delay to be ≤100 ms from 93%–97% to 76%–78% compared to the Friis radio environment. The proposed algorithm reduces the amount of vehicular application traffic from 21 Mbps to 13 Mbps, while improving the probability of end-to-end delay being ≤100 ms by 20%. Lastly, use of MAC layer control elements brings the processing of messages towards the edge of network increasing capacity of the system by about 50%

Random Access in Massive MIMO by Exploiting Timing Offsets and Excess Antennas

Massive MIMO systems, where base stations are equipped with hundreds of antennas, are an attractive way to handle the rapid growth of data traffic. As the number of user equipments (UEs) increases, the initial access and handover in contemporary networks will be flooded by user collisions. In this paper, a random access protocol is proposed that resolves collisions and performs timing estimation by simply utilizing the large number of antennas envisioned in Massive MIMO networks. UEs entering the network perform spreading in both time and frequency domains, and their timing offsets are estimated at the base station in closed-form using a subspace decomposition approach. This information is used to compute channel estimates that are subsequently employed by the base station to communicate with the detected UEs. The favorable propagation conditions of Massive MIMO suppress interference among UEs whereas the inherent timing misalignments improve the detection capabilities of the protocol. Numerical results are used to validate the performance of the proposed procedure in cellular networks under uncorrelated and correlated fading channels. With $2.5\times10^3$ UEs that may simultaneously become active with probability 1\% and a total of $16$ frequency-time codes (in a given random access block), it turns out that, with $100$ antennas, the proposed procedure successfully detects a given UE with probability 75\% while providing reliable timing estimates.Comment: 30 pages, 6 figures, 1 table, submitted to Transactions on Communication

Adaptive Bit Partitioning for Multicell Intercell Interference Nulling with Delayed Limited Feedback

Base station cooperation can exploit knowledge of the users' channel state information (CSI) at the transmitters to manage co-channel interference. Users have to feedback CSI of the desired and interfering channels using finite-bandwidth backhaul links. Existing codebook designs for single-cell limited feedback can be used for multicell cooperation by partitioning the available feedback resources between the multiple channels. In this paper, a new feedback-bit allocation strategy is proposed, as a function of the delays in the communication links and received signal strengths in the downlink. Channel temporal correlation is modeled as a function of delay using the Gauss-Markov model. Closed-form expressions for bit partitions are derived to allocate more bits to quantize the stronger channels with smaller delays and fewer bits to weaker channels with larger delays, assuming random vector quantization. Cellular network simulations are used to show that the proposed algorithm yields higher sum-rates than an equal-bit allocation technique.Comment: Submitted to IEEE Transactions on Signal Processing, July 201

Theoretical and simulation results with uplink OFDM code division multiplexing in multicellular scenario

International audienceIn this paper, we investigate the robustness of the spread spectrum multi-carrier multiple access (SS-MC-MA) technique in uplink multicellular systems. In a first step, a statistical characterization of the intercell interference is carried on to model it for BER performance simulations. Then, the impact of the intercell interference on such a scheme is evaluated and the robustness of SS-MC-MA system by mitigating those interferences thanks to frequency allocation, channel coding and spreading gain is optimized

Intercell interference mitigation for uplink OFDM code division multiplexing

International audienceIn this paper, we investigate the robustness of the spread spectrum multi-carrier multiple access (SS-MC-MA) technique in uplink multicellular systems. In a first step, a statistical characterization of the intercell interference is carried on to model it for BER performance simulations. Then, the impact of the intercell interference on such a scheme is evaluated and the robustness of SS-MC-MA system by mitigating those interferences thanks to frequency allocation, channel coding and spreading gain is optimized

Joint collision resolution and transmit‐power adjustment for Aloha‐type random access

We consider uplink random access for which slotted Aloha has usually been employed with unknown channel conditions. Upon failure of a transmission attempt, a user cannot tell whether the failure was caused by collision with other simultaneously transmitting users or by his use of insufficient transmit power. If a transmission attempt failed due to collision which could have been resolved by retransmission, increasing transmit power would just waste power and, moreover, reduce the other users' chance of successful access. To handle this lack of information on the cause of failure, we propose a novel Cause‐of‐Failure resolution, where the transmit power is increased after a given number of consecutive unsuccessful access attempts when the probability that a given failure is caused by collision becomes sufficiently low. To exploit the thus‐obtained transmit power for the next random access attempt, we also determine the Cause‐of‐Success based on the number of consecutive successful attempts, i.e., whether to (probabilistically) decrease or maintain the current transmit power. This way, users can adjust their transmit power for random access, which we call Auto Power Fallback (APF), considered as an advanced version of the power ramping algorithm. We evaluate APF by modeling analysis and numerical computation based on the slotted Aloha, showing that APF determines a suitable transmit power for uplink random accesses while achieving good performance. Copyright © 2011 John Wiley & Sons, Ltd. We consider uplink random access for which slotted Aloha has usually been employed with unknown channel conditions. To handle this lack of information on the cause of failure , we propose a novel Cause‐of‐Failure resolution, where the transmit power is increased after a given number of consecutive unsuccessful access attempts when the probability that a given failure is caused by collision becomes sufficiently low. Users can adjust their transmit power for random access, which we call Auto Power Fallback (APF), considered as an advanced version of the power ramping algorithm.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/96361/1/wcm1105.pd