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Uplink (UL) dominated sporadic transmission and stringent latency requirement of massive machine type communication (mMTC) forces researchers to abandon complicated grant-acknowledgment based legacy networks. UL grant-free non-orthogonal multiple access (NOMA) provides an array of features which can be harnessed to efficiently solve the problem of massive random connectivity and latency. Because of the inherent sparsity in user activity pattern in mMTC, the trend of existing literature specifically revolves around compressive sensing based multi user detection (CS-MUD) and Bayesian framework paradigm which employs either random or Zadoff-Chu spreading sequences for non-orthogonal multiple access. In this work, we propose sinusoidal code as candidate spreading sequences. We show that, sinusoidal codes allow some non-iterative algorithms to be employed in context of active user detection, channel estimation and data detection in a UL grant-free mMTC system. This relaxes the requirement of several impractical assumptions considered in the state-of-art algorithms with added advantages of performance guarantees and lower computational cost. Extensive simulation results validate the performance potential of sinusoidal codes in realistic mMTC environments., Comment: 10 pages, 7 figures

The autocorrelation of a Zadoff-Chu (ZC) sequence with a non-zero cyclically shifted version of itself is zero. Due to the interesting property, ZC sequences are widely used in the LTE air interface in the primary synchronization signal (PSS), random access preamble (PRACH), uplink control channel (PUCCH) etc. However, this interesting property of ZC sequence is not useful in the random access initial uplink synchronization problem due to some specific structures of the underlying problem. In particular, the state of the art uplink synchronization algorithms do not perform equally for all ZC sequences. In this work, we show a systematic procedure to choose the ZC sequences that yield the optimum performance of the uplink synchronization algorithms. At first, we show that the uplink synchronization is a sparse signal recovery problem on an overcomplete basis. Next, we use the theory of sparse recovery algorithms and identify a factor that controls performance of the algorithms. We then suggest a ZC sequence design procedure to optimally choose this factor. The simulation results show that the performance of most of the state of the art uplink synchronization algorithms improve significantly when the ZC sequences are chosen by using the proposed technique., Comment: 13 pages, 7 figures

Random access is a multiple access communication protocol where the users simultaneously communicate with a base station (BS) in an uncoordinated fashion. In this work, we consider the problem of multiuser detection in a random access bandwidth request context. We propose an enhanced random access scheme where the fixed/low-mobility M2M devices pre-equalize their random access codes using the estimated frequency response of the slowly-varying wireless channel. Consequently, we have developed two different multiuser detection algorithms. The first algorithm works in a greedy fashion where it performs cross-correlation of the received signal with a set of decoder sequences and detects active users based on the correlation output. We derive the condition under which the algorithm can detect a given number of active users with high probability. Subsequently, we demonstrate an efficient decoder design procedure which enhances the user detection performance. A basis mismatched sparse recovery technique has been applied in the second algorithm which exploit an inherent structure of the random access protocol. The performance of the proposed schemes is demonstrated in a WiMAX network environment., Comment: 12 pages, 7 figures

Initial ranging constitutes a part of the synchronization procedure employed by the wireless communication standards. This allows the base station (BS) to detect the subscriber stations (SS) that are willing to commence communication. In addition, the ranging process allows the BS to estimate the uplink channel parameters of these SSs. Accurate estimation of these parameters are crucial as they ensure that the uplink signals from all the SSs arrive at the BS synchronously and approximately at the same power level. However, this detection and estimation problem turns out to be very challenging when multiple users initiate the ranging procedure at the same time. We address this issue by exploiting the underlying sparsity of the estimation problem. We propose a fast sparse signal recovery approach to improve the ranging performance in multi-user environment. Compared to the standard correlation based techniques, our method shows a clear improvement in ranging code detection, timing offset and channel power estimation. Although this method has been developed around the WiMAX standard, the underlying principles apply to other OFDM based standards as well., Comment: 11 pages, 4 figures