5,093 research outputs found
Is Our Model for Contention Resolution Wrong?
Randomized binary exponential backoff (BEB) is a popular algorithm for
coordinating access to a shared channel. With an operational history exceeding
four decades, BEB is currently an important component of several wireless
standards. Despite this track record, prior theoretical results indicate that
under bursty traffic (1) BEB yields poor makespan and (2) superior algorithms
are possible. To date, the degree to which these findings manifest in practice
has not been resolved.
To address this issue, we examine one of the strongest cases against BEB:
packets that simultaneously begin contending for the wireless channel. Using
Network Simulator 3, we compare against more recent algorithms that are
inspired by BEB, but whose makespan guarantees are superior. Surprisingly, we
discover that these newer algorithms significantly underperform. Through
further investigation, we identify as the culprit a flawed but common
abstraction regarding the cost of collisions. Our experimental results are
complemented by analytical arguments that the number of collisions -- and not
solely makespan -- is an important metric to optimize. We believe that these
findings have implications for the design of contention-resolution algorithms.Comment: Accepted to the 29th ACM Symposium on Parallelism in Algorithms and
Architectures (SPAA 2017
Random Access Protocol for Massive MIMO: Strongest-User Collision Resolution (SUCR)
Wireless networks with many antennas at the base stations and multiplexing of
many users, known as Massive MIMO systems, are key to handle the rapid growth
of data traffic. As the number of users increases, the random access in
contemporary networks will be flooded by user collisions. In this paper, we
propose a reengineered random access protocol, coined strongest-user collision
resolution (SUCR). It exploits the channel hardening feature of Massive MIMO
channels to enable each user to detect collisions, determine how strong the
contenders' channels are, and only keep transmitting if it has the strongest
channel gain. The proposed SUCR protocol can quickly and distributively resolve
the vast majority of all pilot collisions.Comment: Published at the IEEE International Conference on Communications
(ICC), 2016, 6 pages, 6 figures. (c) 2016 IEEE. Personal use of this material
is permitte
A Random Access Protocol for Pilot Allocation in Crowded Massive MIMO Systems
The Massive MIMO (multiple-input multiple-output) technology has great
potential to manage the rapid growth of wireless data traffic. Massive MIMO
achieves tremendous spectral efficiency by spatial multiplexing of many tens of
user equipments (UEs). These gains are only achieved in practice if many more
UEs can connect efficiently to the network than today. As the number of UEs
increases, while each UE intermittently accesses the network, the random access
functionality becomes essential to share the limited number of pilots among the
UEs. In this paper, we revisit the random access problem in the Massive MIMO
context and develop a reengineered protocol, termed strongest-user collision
resolution (SUCRe). An accessing UE asks for a dedicated pilot by sending an
uncoordinated random access pilot, with a risk that other UEs send the same
pilot. The favorable propagation of Massive MIMO channels is utilized to enable
distributed collision detection at each UE, thereby determining the strength of
the contenders' signals and deciding to repeat the pilot if the UE judges that
its signal at the receiver is the strongest. The SUCRe protocol resolves the
vast majority of all pilot collisions in crowded urban scenarios and continues
to admit UEs efficiently in overloaded networks.Comment: To appear in IEEE Transactions on Wireless Communications, 16 pages,
10 figures. This is reproducible research with simulation code available at
https://github.com/emilbjornson/sucre-protoco
Characterization of Coded Random Access with Compressive Sensing based Multi-User Detection
The emergence of Machine-to-Machine (M2M) communication requires new Medium
Access Control (MAC) schemes and physical (PHY) layer concepts to support a
massive number of access requests. The concept of coded random access,
introduced recently, greatly outperforms other random access methods and is
inherently capable to take advantage of the capture effect from the PHY layer.
Furthermore, at the PHY layer, compressive sensing based multi-user detection
(CS-MUD) is a novel technique that exploits sparsity in multi-user detection to
achieve a joint activity and data detection. In this paper, we combine coded
random access with CS-MUD on the PHY layer and show very promising results for
the resulting protocol.Comment: Submitted to Globecom 201
The complexity of resolving conflicts on MAC
We consider the fundamental problem of multiple stations competing to
transmit on a multiple access channel (MAC). We are given stations out of
which at most are active and intend to transmit a message to other stations
using MAC. All stations are assumed to be synchronized according to a time
clock. If stations node transmit in the same round, then the MAC provides
the feedback whether , (collision occurred) or . When ,
then a single station is indeed able to successfully transmit a message, which
is received by all other nodes. For the above problem the active stations have
to schedule their transmissions so that they can singly, transmit their
messages on MAC, based only on the feedback received from the MAC in previous
round.
For the above problem it was shown in [Greenberg, Winograd, {\em A Lower
bound on the Time Needed in the Worst Case to Resolve Conflicts
Deterministically in Multiple Access Channels}, Journal of ACM 1985] that every
deterministic adaptive algorithm should take rounds
in the worst case. The fastest known deterministic adaptive algorithm requires
rounds. The gap between the upper and lower bound is
round. It is substantial for most values of : When constant and (for any constant , the lower bound is
respectively and O(n), which is trivial in both cases. Nevertheless,
the above lower bound is interesting indeed when poly(). In this
work, we present a novel counting argument to prove a tight lower bound of
rounds for all deterministic, adaptive algorithms, closing
this long standing open question.}Comment: Xerox internal report 27th July; 7 page
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