Research Article On Normal -Ary Codes in Rosenbloom...

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Research Article On Normal -Ary Codes in Rosenbloom-Tsfasman Metric R. S. Selvaraj and Venkatrajam Marka Department of Mathematics, National Institute of Technology Warangal, Andhra Pradesh 506004, India Correspondence should be addressed to R. S. Selvaraj; [email protected] Received 10 February 2014; Accepted 17 March 2014; Published 2 April 2014 Academic Editors: A. Cossidente, E. Manstavicius, and S. Richter Copyright Β© 2014 R. S. Selvaraj and V. Marka. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. e notion of normality of codes in Hamming metric is extended to the codes in Rosenbloom-Tsfasman metric (RT-metric, in short). Using concepts of partition number and -cell of codes in RT-metric, we establish results on covering radius and normality of -ary codes in this metric. We also examine the acceptability of various coordinate positions of -ary codes in this metric. And thus, by exploring the feasibility of applying amalgamated direct sum method for construction of codes, we analyze the significance of normality in RT-metric. 1. Introduction Covering properties of codes have unique significance in coding theory, and covering radius, one of the four funda- mental parameters, of a code is important in several respects [1]. Considering the fact that it is a geometric property of codes that characterizes maximal error correcting capability in the case of minimum distance decoding, covering radius had been extensively studied by many researchers (see, e.g., [2, 3] and the literature therein) especially with respect to the conventional Hamming metric. In fact, it has evolved into a subject in its own right mainly because of its practical applicability in areas such as data compression, testing, and write-once memories and also because of the mathematical beauty that it possesses. More on covering radius can be found in the monograph compiled by Cohen et al. [4]. In order to improve upon the bounds on covering radius, various construction techniques that use two or more known codes to construct a new code were proposed over the last few decades. One such method is direct sum construction which is a basic yet useful construction method. To improve upon the bounds related to covering radius of codes obtained using this method, the notion of normality which facilitates a construction technique known as amalgamated direct sum (ADS) was introduced for binary linear codes by Graham and Sloane in [5]. e same concepts were extended to binary nonlinear codes by Cohen et al. in [6]. Later, Lobstein and van Wee generalized these results to -ary codes [7]. In the present paper, we extend the notion of normality to codes in Rosenbloom-Tsfasman metric (RT-metric, in short). e present work is a generalization of our work on binary codes [8] to -ary case (though the discussed results hold good for codes over any alphabet of size , for simplicity, we have taken it to be the finite field F ). RT- metric was introduced by Rosenbloom and Tsfasman in [9] and independently by Skriganov in [10] and is more adequate than Hamming metric in dealing with channels in which errors have a tendency to occur with a periodic spikewise perturbation of period ∈ N. As a generalization of the classical Hamming metric with rich mathematical beauty and being advantageous over Hamming metric in dealing with certain channels [9, 10], this metric attracted the attention of coding theorists over the last two decades [11–13]. e covering problem in RT-metric was first dealt with by Yildiz et al. for RT-spaces over Galois Rings [14]. e organization of the present paper is as follows. In Section 2, some basic definitions and notations that are used in this paper are presented. In Section 3, we have studied the covering radius of -ary codes in this metric by introducing two new tools, namely, partition number and -cell which greatly reduce the difficulty in determining the covering radius. In Section 4, we investigate the normality of -ary Hindawi Publishing Corporation ISRN Combinatorics Volume 2014, Article ID 237915, 5 pages http://dx.doi.org/10.1155/2014/237915

Transcript of Research Article On Normal -Ary Codes in Rosenbloom...

  • Research ArticleOn Normal π‘ž-Ary Codes in Rosenbloom-Tsfasman Metric

    R. S. Selvaraj and Venkatrajam Marka

    Department of Mathematics, National Institute of Technology Warangal, Andhra Pradesh 506004, India

    Correspondence should be addressed to R. S. Selvaraj; [email protected]

    Received 10 February 2014; Accepted 17 March 2014; Published 2 April 2014

    Academic Editors: A. Cossidente, E. Manstavicius, and S. Richter

    Copyright Β© 2014 R. S. Selvaraj and V. Marka. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

    The notion of normality of codes in Hamming metric is extended to the codes in Rosenbloom-Tsfasman metric (RT-metric, inshort). Using concepts of partition number and 𝑙-cell of codes in RT-metric, we establish results on covering radius and normalityof π‘ž-ary codes in this metric. We also examine the acceptability of various coordinate positions of π‘ž-ary codes in this metric. Andthus, by exploring the feasibility of applying amalgamated direct summethod for construction of codes, we analyze the significanceof normality in RT-metric.

    1. Introduction

    Covering properties of codes have unique significance incoding theory, and covering radius, one of the four funda-mental parameters, of a code is important in several respects[1]. Considering the fact that it is a geometric property ofcodes that characterizes maximal error correcting capabilityin the case of minimum distance decoding, covering radiushad been extensively studied by many researchers (see, e.g.,[2, 3] and the literature therein) especially with respect tothe conventional Hamming metric. In fact, it has evolvedinto a subject in its own right mainly because of its practicalapplicability in areas such as data compression, testing, andwrite-once memories and also because of the mathematicalbeauty that it possesses. More on covering radius can befound in the monograph compiled by Cohen et al. [4].In order to improve upon the bounds on covering radius,various construction techniques that use two or more knowncodes to construct a new code were proposed over the lastfew decades. One such method is direct sum constructionwhich is a basic yet useful construction method. To improveupon the bounds related to covering radius of codes obtainedusing this method, the notion of normality which facilitatesa construction technique known as amalgamated direct sum(ADS)was introduced for binary linear codes byGraham andSloane in [5]. The same concepts were extended to binary

    nonlinear codes by Cohen et al. in [6]. Later, Lobstein andvan Wee generalized these results to π‘ž-ary codes [7].

    In the present paper, we extend the notion of normalityto codes in Rosenbloom-Tsfasman metric (RT-metric, inshort). The present work is a generalization of our workon binary codes [8] to π‘ž-ary case (though the discussedresults hold good for codes over any alphabet of size π‘ž, forsimplicity, we have taken it to be the finite field Fπ‘ž). RT-metric was introduced by Rosenbloom and Tsfasman in [9]and independently by Skriganov in [10] and is more adequatethan Hamming metric in dealing with channels in whicherrors have a tendency to occur with a periodic spikewiseperturbation of period 𝑠 ∈ N. As a generalization of theclassical Hammingmetric with richmathematical beauty andbeing advantageous over Hamming metric in dealing withcertain channels [9, 10], this metric attracted the attentionof coding theorists over the last two decades [11–13]. Thecovering problem in RT-metric was first dealt with by Yildizet al. for RT-spaces over Galois Rings [14].

    The organization of the present paper is as follows. InSection 2, some basic definitions and notations that are usedin this paper are presented. In Section 3, we have studied thecovering radius of π‘ž-ary codes in this metric by introducingtwo new tools, namely, partition number and 𝑙-cell whichgreatly reduce the difficulty in determining the coveringradius. In Section 4, we investigate the normality of π‘ž-ary

    Hindawi Publishing CorporationISRN CombinatoricsVolume 2014, Article ID 237915, 5 pageshttp://dx.doi.org/10.1155/2014/237915

  • 2 ISRN Combinatorics

    codes in RT-metric. In this section, we also discuss thepossibilities of extending the direct sum and amalgamateddirect sum (ADS) constructions from Hamming metric toRT-metric. And, finally, Section 5 provides the conclusions ofthis paper.

    2. Definitions and Notations

    For π‘₯ = (π‘₯1, π‘₯2, . . . , π‘₯𝑠) ∈ F𝑠

    π‘ž, where Fπ‘ž = GF(π‘ž) is a finite field

    of π‘ž elements, we define the 𝜌-weight (RT-weight) of π‘₯ to be

    π‘€π‘‘πœŒ (π‘₯) = max {𝑖 | π‘₯𝑖 ΜΈ= 0, 1 ≀ 𝑖 ≀ 𝑠} . (1)

    The RT-distance or 𝜌-distance between π‘₯ = (π‘₯1, π‘₯2, . . . , π‘₯𝑠)and 𝑦 = (𝑦1, 𝑦2, . . . , 𝑦𝑠) ∈ F

    𝑠

    π‘žcan be defined by π‘‘πœŒ(π‘₯, 𝑦) =

    π‘€π‘‘πœŒ(π‘₯βˆ’π‘¦).The subsets of the space equippedwith thismetricare called RT-metric codes over Fπ‘ž (or π‘ž-ary RT-metric codes)and the subspaces are called linear RT-metric codes over Fπ‘ž.The value 𝑑min = min{π‘‘πœŒ(π‘₯, 𝑦) : π‘₯, 𝑦 ∈ 𝐢} is called theminimum 𝜌-distance of the code 𝐢. The maximum distanceof any word in the ambient space from an RT-metric code iscalled the covering radius of the code. A code in which eachnonzero codeword is of the same weight π‘€πœŒ is said to be aconstant weight code. A π‘ž-ary code of length 𝑠, cardinality 𝐾,andminimum𝜌-distanceπ‘‘πœŒ is said to be amaximumdistanceseparable code (an MDS code, in short) if𝐾 = π‘ž(π‘ βˆ’π‘‘πœŒ+1).

    Throughout this paper, unless otherwise specified, by acode we mean a π‘ž-ary RT-metric code and by distance wemean RT-distance. Moreover, [𝑠, π‘˜, π‘‘πœŒ]π‘žπ‘… denotes a π‘ž-arylinear code of length 𝑠, dimension π‘˜, minimum distance π‘‘πœŒ,and covering radius 𝑅, (𝑠, 𝐾, π‘‘πœŒ)π‘žπ‘… denotes a π‘ž-ary code withcardinality 𝐾, and π‘‘π‘ž[𝑠, π‘˜] denotes the minimum coveringradius that a π‘ž-ary linear code of length 𝑠 and dimension π‘˜can possess.

    Definition 1 (direct sumof two codes). Let𝐢1 and𝐢2 be codeswith parameters (𝑠1, 𝐾1)π‘ž and (𝑠2, 𝐾2)π‘ž, respectively. Then,the direct sum of 𝐢1 and 𝐢2, denoted by 𝐢1⨁𝐢2, is definedas

    𝐢1⨁𝐢2 = {(𝑐1, 𝑐2) | 𝑐1 ∈ 𝐢1, 𝑐2 ∈ 𝐢2} , (2)

    and is a code of length 𝑠1 + 𝑠2 and cardinality𝐾1𝐾2.

    Definition 2 (π‘ž-ary normal codes). Let𝐢be a π‘ž-aryRT-metriccode of length 𝑠, cardinality 𝐾, and covering radius 𝑅, and,also, for each π‘Ž ∈ Fπ‘ž, let 𝐢

    (𝑖)

    π‘Ždenote the set of codewords in

    which the 𝑖th coordinate is π‘Ž.Then, thenorm of𝐢with respectto the 𝑖th coordinate is defined as

    𝑁(𝑖)

    = maxπ‘₯∈F π‘ π‘ž

    {

    {

    {

    βˆ‘

    π‘ŽβˆˆFπ‘ž

    π‘‘πœŒ (π‘₯, 𝐢(𝑖)

    π‘Ž)}

    }

    }

    , (3)

    where

    π‘‘πœŒ (π‘₯, 𝐢(𝑖)

    π‘Ž) = {

    min {π‘‘πœŒ (π‘₯, 𝑦) | 𝑦 ∈ 𝐢(𝑖)

    π‘Ž} if 𝐢(𝑖)

    π‘ŽΜΈ= 0

    𝑠 if 𝐢(𝑖)π‘Ž

    = 0.(4)

    Now, 𝑁 = min𝑖𝑁(𝑖) is called the norm of 𝐢 and the

    coordinates 𝑖 for which 𝑁(𝑖) = 𝑁 are said to be acceptable.

    Finally, a code is said to be normal if its norm satisfies 𝑁 β‰€π‘žπ‘… + π‘ž βˆ’ 1. If the code 𝐢 is not clear from the context, we usethe notations𝑁(𝑖)(𝐢) and𝑁(𝐢).

    3. Covering Radius of RT-Metric Codes over Fπ‘ž

    Definition 3 (partition number of a π‘ž-ary RT-metric code).Let 𝐢 be an (𝑠, 𝐾, π‘‘πœŒ)π‘ž code in RT-metric. The largestnonnegative integer 𝑙, for which each π‘ž-ary 𝑙-tuple can beassigned to at least one codeword whose last 𝑙 coordinates areactually that 𝑙-tuple, is called the partition number of the code𝐢. The code with partition number 𝑙 can be partitioned intoπ‘žπ‘™ parts, each of which has the property that all its membershave the same π‘ž-ary 𝑙-tuple as their last 𝑙 coordinates. A partobtained in the above fashion is called an 𝑙-cell of the code,if at least one field element is not present in the (𝑠 βˆ’ 𝑙)thcoordinate of its member codewords. As the definition ofpartition number suggests, a code with partition number 𝑙contains at least π‘žπ‘™ codewords.

    If 𝐢 is an [𝑠, π‘˜, π‘‘πœŒ]π‘ž linear code, then each of the π‘žπ‘™ parts

    does have π‘žπ‘˜βˆ’π‘™ codewords in it and so does each 𝑙-cell by itsdefinition. If𝐢1 is an 𝑙-cell of the linear code𝐢, then π‘₯+𝐢1 forπ‘₯ ∈ 𝐢\𝐢1 will also be an 𝑙-cell different from𝐢1.Thus, for lin-ear codes, if there is one 𝑙-cell, then therewill be π‘žπ‘™ such 𝑙-cells.

    Now, we will observe that covering radius of a code canbe determined using the concepts of partition number and𝑙-cell. The definition of partition number serves as a tool indetermining the covering radius of an RT-metric code, asshown by the following theorem.

    Theorem 4. Let 𝐢 be an (𝑠, 𝐾, π‘‘πœŒ)π‘žπ‘… code in RT-metric. Then,the partition number of 𝐢 is 𝑙 if and only if its covering radiusis 𝑠 βˆ’ 𝑙.

    Proof. First, let the partition number of the code be 𝑙.Partition the code such that codewords in each part containa unique π‘ž-ary (𝑙 + 1)-tuple as their last 𝑙 + 1 coordinates.Associate each part with the respective (𝑙+1)-tuple. Since thepartition number of the code is 𝑙, the number of such partswill be less than π‘žπ‘™+1. Choose an π‘₯ ∈ F 𝑠

    π‘ž, whose last 𝑙 + 1

    coordinates constitute the (𝑙 + 1)-tuple that does not have apart associated with it. Such an π‘₯ will be at distance 𝑠 βˆ’ 𝑙from the code, which is the maximum distance that a wordcan actually be from the code 𝐢. Hence, the covering radiusis 𝑠 βˆ’ 𝑙.

    Conversely, let the covering radius be 𝑅 = 𝑠 βˆ’ 𝑙. By thedefinition of covering radius, any word must be at distance atmost 𝑠 βˆ’ 𝑙 from the code, which means that, for each word,there is at least one codeword which agrees with the word inthe last 𝑠 βˆ’ (𝑠 βˆ’ 𝑙) = 𝑙 coordinate positions. This implies thatthe partition number of the code is greater than or equal to 𝑙.Let us assume that the partition number of the code is π‘š >𝑙. Then, to each π‘ž-ary π‘š-tuple, we can associate a codewordwhose last π‘š coordinates coincide with that π‘š-tuple. Thus,eachword in F 𝑠

    π‘žwill be at distance atmost π‘ βˆ’π‘š, contradicting

    the fact that covering radius of 𝐢 is 𝑠 βˆ’ 𝑙. Hence, the partitionnumber of the code 𝐢 is 𝑙.

  • ISRN Combinatorics 3

    Now, the above theorem can be restated in terms of 𝑙-cell in the following manner, as the definition of the 𝑙-cellsuggests.

    Corollary 5. Let 𝐢 be an RT-metric code of length 𝑠 over Fπ‘ž.Then, the covering radius of 𝐢 is 𝑠 βˆ’ 𝑙 if and only if βˆƒ an 𝑙-cellof the code 𝐢.

    Proposition 6. Let 𝐢1 and 𝐢2 be any two RT-metric codesover Fπ‘ž with parameters (𝑠1, 𝐾1, 𝑑1)π‘žπ‘…1 and (𝑠2, 𝐾2, 𝑑2)π‘žπ‘…2,respectively. Then, their direct sum 𝐢 = 𝐢1⨁𝐢2 is an (𝑠1 +𝑠2, 𝐾1𝐾2, 𝑑)π‘žπ‘… code with minimum distance 𝑑 = 𝑑1 andcovering radius 𝑅 = 𝑠1 + 𝑅2, provided 𝐢2 ΜΈ= F 𝑠2π‘ž .

    Proof. The direct sum of 𝐢1 and 𝐢2 is given by

    𝐢1⨁𝐢2 = {(𝑐1, 𝑐2) | 𝑐1 ∈ 𝐢1, 𝑐2 ∈ 𝐢2} . (5)

    Clearly, this is a code of length 𝑠1 + 𝑠2 and cardinality 𝐾1𝐾2.Now, since the minimum distance of 𝐢1 is 𝑑1, there exist twocodewords 𝑐1 and 𝑐

    1in 𝐢1 such that π‘‘πœŒ(𝑐1, 𝑐

    1) = 𝑑1. Then,

    the codewords 𝑐 = (𝑐1, 𝑐2) and 𝑐= (𝑐

    1, 𝑐2) for some 𝑐2 ∈ 𝐢2

    will also be at distance 𝑑1 which is minimum among all thecodewords of 𝐢. FromTheorem 4 and Definition 3, it is clearthat the covering radius of a code in RT-metric depends onthe partition number of the code and that the process ofpartitioning starts with the right most coordinate. Therefore,byTheorem 4, unless𝐢2 is the space F

    𝑠2π‘ž, the partition number

    of 𝐢 must be equal to that of 𝐢2 which is 𝑠2 βˆ’ 𝑅2 and, hence,the covering radius of 𝐢 is 𝑠1 + 𝑠2 βˆ’ (𝑠2 βˆ’ 𝑅2) = 𝑠1 + 𝑅2.

    Remark 7. If 𝐢2 = F 𝑠2π‘ž , then the covering radius of the code𝐢 = 𝐢1⨁𝐢2 is 𝑅 = 𝑅1.

    4. Normality of Codes in RT-Metric

    Proposition 8. If 𝐢 is an (𝑠, 𝐾, π‘‘πœŒ)π‘žπ‘… RT-metric code over Fπ‘ž,then𝑁(𝐢) β‰₯ π‘žπ‘….

    Proof. The proof follows directly from the definition ofcovering radius and that of norm of a code.

    Theorem9. Any π‘ž-ary RT-metric code of length 𝑠 and coveringradius 𝑠 is normal and all the coordinates are acceptable.

    Proof. As 𝑅 = 𝑠, the partition number is 0 which meansthat there exists an 𝛼 ∈ Fπ‘ž which is not present as the lastcoordinate of any codeword in 𝐢. If π‘₯ = (π‘₯1, π‘₯2, . . . , π‘₯𝑠) ∈ F

    𝑠

    π‘ž

    is such that π‘₯𝑠 = 𝛼, then π‘‘πœŒ(π‘₯, 𝐢(𝑖)

    π‘Ž) = 𝑠 for each π‘Ž ∈ Fπ‘ž

    and for any 𝑖 ∈ {1, 2, . . . , 𝑠}. Thus, 𝑁(𝑖) = π‘žπ‘  < π‘žπ‘  + π‘ž βˆ’ 1 =π‘žπ‘…+(π‘žβˆ’1). Hence, the code is normal and all the coordinatesare acceptable.

    Lemma 10. Let 𝐢 be any RT-metric code with length 𝑠 andcovering radius 𝑅 < 𝑠; then

    𝑁(𝑖)

    = (π‘ž βˆ’ 1) 𝑖 + 𝑅, (6)

    for each 𝑖 ∈ {𝑅 + 1, 𝑅 + 2, . . . , 𝑠}.

    Proof. For a coordinate position 𝑖 ∈ {𝑅 + 1, 𝑅 + 2, . . . , 𝑠}, thenorm is given by

    𝑁(𝑖)

    = maxπ‘₯∈F π‘ π‘ž

    {

    {

    {

    βˆ‘

    π‘ŽβˆˆFπ‘ž

    π‘‘πœŒ (π‘₯, 𝐢(𝑖)

    π‘Ž)}

    }

    }

    . (7)

    As the covering radius of 𝐢 is 𝑅, it has partition number𝑠 βˆ’ 𝑅. So, the definition of partition number implies thateach codeword can be associated with a unique (𝑠 βˆ’ 𝑅)-tuplewhich actually consists of the last (𝑠 βˆ’ 𝑅) coordinates of thatcodeword and, also, that there exists at least one (𝑠 βˆ’ 𝑅 + 1)-tuple which is not the same as the last 𝑠 βˆ’ 𝑅 + 1 coordinatesof any of the codewords. Now, when we partition the codeinto π‘ž parts 𝐢(𝑖)

    π‘Ž, for π‘Ž ∈ Fπ‘ž, we can also partition the set of

    all (𝑠 βˆ’ 𝑅)-tuples into π‘ž parts corresponding to the associatedcodewords in 𝐢(𝑖)

    π‘Ž. If we choose a word π‘₯ ∈ F 𝑠

    π‘žwhose last

    𝑠 βˆ’ 𝑅 + 1 coordinates do not match with the last 𝑠 βˆ’ 𝑅 + 1coordinates of any of the codewords, then, for this word,βˆ‘π‘ŽβˆˆFπ‘ž

    π‘‘πœŒ(π‘₯, 𝐢(𝑖)

    π‘Ž) = (π‘ž βˆ’ 1)𝑖 + 𝑅 which is the maximum value

    that a word can give. Hence, the proof holds.

    Theorem 11. Let 𝐢 be any RT-metric code of length 𝑠 withcovering radius 𝑅 < 𝑠. Then, the coordinates 𝑖 ∈ {𝑅 + 2, 𝑅 +3, . . . , 𝑠} are not acceptable.

    Proof. Theminimum norm is

    𝑁 ≀ 𝑁(𝑖), βˆ€π‘– ∈ {1, 2, . . . , 𝑠} . (8)

    By Lemma 10, 𝑁(𝑖) = (π‘ž βˆ’ 1)𝑖 + 𝑅, for all 𝑖 β‰₯ 𝑅 + 1, whichimplies

    𝑁(𝑅+1)

    < 𝑁(𝑅+2)

    < 𝑁(𝑅+3)

    < β‹… β‹… β‹… < 𝑁(𝑠). (9)

    From (8) and (9), one can conclude that

    𝑁 < 𝑁(𝑖), βˆ€π‘– ∈ {𝑅 + 2, 𝑅 + 3, . . . , 𝑠} . (10)

    This completes the proof.

    The above theorem is not sufficient to arrive at a decisionon the acceptability of the 𝑠th coordinate, when the codehas covering radius 𝑅 = 𝑠 βˆ’ 1. This can be settled by thefollowing theorem which says that no π‘ž-ary linear RT-metriccode with dimension more than 1 and covering radius 𝑠 βˆ’ 1has acceptable last coordinate.

    Theorem 12. Let 𝐢 be an [𝑠, π‘˜, π‘‘πœŒ]π‘žπ‘… linear RT-metric codeover Fπ‘ž with π‘˜ > 1 and 𝑅 = 𝑠 βˆ’ 1. Then, the last coordinate isnot acceptable.

    Proof. By Lemma 10,

    𝑁(𝑠)

    = (π‘ž βˆ’ 1) 𝑠 + 𝑅

    = (π‘ž βˆ’ 1) 𝑠 + 𝑠 βˆ’ 1 = π‘žπ‘  βˆ’ 1

    = π‘ž (𝑠 βˆ’ 1) + π‘ž βˆ’ 1 = π‘žπ‘… + (π‘ž βˆ’ 1)

    (since 𝑅 = 𝑠 βˆ’ 1) .

    (11)

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    In order to prove this theorem, we must show that thereexists at least one coordinate 𝑗 for which 𝑁(𝑗) < 𝑁(𝑠). Asthe dimension of 𝐢 is π‘˜, there will be π‘˜ coordinate positions𝑖1, 𝑖2, . . . , π‘–π‘˜ such that 𝐢

    (𝑖𝑑)

    π‘ŽΜΈ= 0 for all π‘Ž ∈ Fπ‘ž and for each

    𝑑 = 1, 2, . . . , π‘˜. One such coordinate position is 𝑠 (but not π‘ βˆ’1,as the partition number is 1). As π‘˜ > 1, there exists at leastonemore such coordinate position 𝑗 ∈ {𝑖1, 𝑖2, . . . , π‘–π‘˜} and 𝑗 ΜΈ= 𝑠wherein 𝐢(𝑗)

    π‘ŽΜΈ= 0 for all π‘Ž ∈ Fπ‘ž, and so 𝑁

    (𝑗)≀ π‘ž(𝑠 βˆ’ 1) < 𝑁

    (𝑠).This completes the proof.

    But, when the code is either of dimension 1 or of constantweight, all the coordinates become acceptable as the followingresults suggest.

    Proposition 13. Let 𝐢 be an [𝑠, 1]π‘ž linear RT-metric code.Then, 𝐢 is normal and all the coordinates are acceptable.

    Proof. It can easily be seen that the covering radius of 𝐢 iseither 𝑠 or π‘ βˆ’1. If it is 𝑠, the result follows byTheorem 9. If it isπ‘ βˆ’1, there exists a 1-cell. Since𝐢 is of dimension 1, there existπ‘ž such 1-cells. By Lemma 10, 𝑁(𝑠) = π‘žπ‘  βˆ’ 1. Now for each 𝑖 ∈{1, 2, . . . , π‘ βˆ’1}, either𝐢(𝑖)

    0= 𝐢 or |𝐢(𝑖)

    0| = 1. In the former case,

    𝐢(𝑖)

    π‘Ž= 0 for all π‘Ž ΜΈ= 0 and, in the latter case, |𝐢(𝑖)

    π‘Ž| = 1 for all π‘Ž ∈

    Fπ‘ž. In any case,𝑁(𝑖)

    = π‘žπ‘ βˆ’1.This proves the result stated.

    Proposition 14. Let 𝐢 be a constant weight code of length𝑠 over Fπ‘ž. Then, 𝐢 is normal and all the coordinates areacceptable.

    Proof. It is easy to see that the covering radius 𝑅 of theconstant weight code 𝐢 is either 𝑠 or 𝑠 βˆ’ 1, as it can havepartition number of either 0 or 1. If𝑅 = 𝑠, then, by Lemma 10,it is done. If 𝑅 = 𝑠 βˆ’ 1, then 𝐢(𝑠)

    π‘ŽΜΈ= 0 for any π‘Ž ∈ Fπ‘ž. Then, for

    any 𝑖, 0 ∈ 𝐢(𝑖)0

    and |𝐢(𝑖)0| β‰₯ 1. For an π‘₯ ∈ F 𝑠

    π‘žwith π‘₯𝑠 = 0 and

    π‘₯π‘ βˆ’1 ΜΈ= 0,𝑁(𝑖) equals π‘žπ‘  βˆ’ 1. Hence, the result follows.

    Remark 15. If 𝐢 = F π‘ π‘ž, then its partition number is 𝑠 and so its

    covering radius 𝑅 is 0. By (3), for any 𝑖, 𝑁(𝑖) = (π‘ž βˆ’ 1)𝑖 + 0 =(π‘ž βˆ’ 1)𝑖. And so,𝑁(1) < 𝑁(2) < β‹… β‹… β‹… < 𝑁(𝑠) and𝑁(1) = π‘ž βˆ’ 1 =π‘žπ‘…+π‘žβˆ’1. Thus, the ambient space F 𝑠

    π‘žis normal with the first

    coordinate being the only acceptable coordinate.

    4.1. Normality and Direct Sum Construction

    Proposition 16. Let 𝐢1 and 𝐢2 be (𝑠1, 𝐾1, 𝑑1)π‘žπ‘…1 and(𝑠2, 𝐾2, 𝑑2)π‘žπ‘…2 RT-metric codes, respectively, such that 𝑅2 ΜΈ= 0.Then,

    (i) the direct sum 𝐢 = 𝐢1⨁𝐢2 is normal;(ii) all the coordinates corresponding to 𝐢1 are acceptable

    for 𝐢;(iii) the coordinate 𝑖 for 𝑠1 + 1 ≀ 𝑖 ≀ 𝑠2 is accept-

    able for 𝐢 only if the norm of 𝐢2 with respect to thecoordinate 𝑖 βˆ’ 𝑠1 is equal to π‘žπ‘…2.

    Proof. Let 𝐢1 and 𝐢2 be any (𝑠1, 𝐾1, 𝑑1)π‘žπ‘…1 and (𝑠2,𝐾2, 𝑑2)π‘žπ‘…2 π‘ž-ary RT-metric codes, respectively. Then, by

    Proposition 6, their direct sum 𝐢 = 𝐢1⨁𝐢2 is an (𝑠, 𝐾1𝐾2,𝑑1)π‘žπ‘… code with length 𝑠 = 𝑠1 + 𝑠2 and covering radius𝑅 = 𝑠1 + 𝑅2. Now, for 𝑖 ∈ {1, 2, . . . , 𝑠1}, by (3), we have

    𝑁(𝑖)

    (𝐢) = π‘ž (𝑠1 + 𝑅2) . (12)

    Now, in order to determine the norm 𝑁(𝐢), we have to find𝑁(𝑗)(𝐢) for each 𝑗 ∈ {𝑠1 +1, 𝑠1 +2, . . . , 𝑠1 + 𝑠2}, the coordinate

    positions corresponding to𝐢2. But, we know by Proposition 8that𝑁(𝐢2) β‰₯ π‘žπ‘…2 which implies𝑁

    (𝑗)(𝐢) β‰₯ π‘ž(𝑠1+𝑅2). Hence,

    𝑁(𝐢) = π‘ž(𝑠1+𝑅2) = π‘žπ‘… < π‘žπ‘…+π‘žβˆ’1.Thus,𝐢 is normal and allthe coordinate positions corresponding to 𝐢1 are acceptableand the coordinate position 𝑗 ∈ {𝑠1 + 1, 𝑠1 + 2, . . . , 𝑠1 + 𝑠2}corresponding to 𝐢2 is acceptable if𝑁

    (π‘—βˆ’π‘ 1)(𝐢2) = π‘žπ‘…2.

    4.2. Normality and Amalgamated Direct Sum Construction.The amalgamated direct sum of two codes is defined asfollows.

    Definition 17. Let 𝐢1 be an [𝑠1, π‘˜1]π‘žπ‘…1 normal code with thelast coordinate being acceptable and let 𝐢2 be an [𝑠2, π‘˜2]π‘žπ‘…2normal code with the first coordinate being acceptable.Then,their amalgamated direct sum (or shortly ADS), denoted by𝐢1⨁̇𝐢2, is an [𝑠1 + 𝑠2 βˆ’ 1, π‘˜1 + π‘˜2 βˆ’ 1]π‘ž(𝑠1 + 𝑅2 βˆ’ 1) code andis given by

    𝐢1Μ‡

    ⨁𝐢2 = {(𝑐1 | 𝑒 | 𝑐2) : (𝑐1 | 𝑒) ∈ 𝐢1, (𝑒 | 𝑐2) ∈ 𝐢2} .

    (13)

    Here, in this definition, we consider those codes 𝐢1 and 𝐢2which are normal, respectively, with the last coordinate andfirst coordinate being acceptable such that the parts 𝐢(𝑠)

    1π‘Žand

    𝐢(1)

    2π‘Žare nonempty for all π‘Ž ∈ Fπ‘ž.

    As Theorem 12 shows the nonexistence of linear codes ofdimension more than 1 whose last coordinate is acceptable,the significance of amalgamated direct sum and hence thatof normality in RT-metric are less as far as the resultingcovering radius is concerned. But, since the one-dimensionalcodes are normal and all the coordinates are acceptable, onecan only use this ADS construction method to combine a1-dimensional code with any other linear code, which maybe helpful in the construction of MDS codes as seen in thefollowing result.

    Theorem 18. Let 𝐢1 be an [𝑠1, 1]π‘ž MDS code with coveringradius π‘‘π‘ž[𝑠1, 1] (which is normal with last coordinate beingacceptable) and let 𝐢2 be an [𝑠2, π‘˜2]π‘ž MDS code with coveringradius π‘‘π‘ž[𝑠2, π‘˜2]. Then, their amalgamated direct sum 𝐢1⨁̇𝐢2is an [𝑠1 + 𝑠2 βˆ’ 1, π‘˜2]π‘ž MDS code with covering radius π‘‘π‘ž[𝑠1 +𝑠2 βˆ’ 1, π‘˜2].

    Proof. From the definition of partition number and fromTheorem 4, it is easy to see that π‘‘π‘ž[𝑠, π‘˜] = 𝑠 βˆ’ π‘˜. So, π‘‘π‘ž[𝑠1, 1] =𝑠1 βˆ’ 1 and π‘‘π‘ž[𝑠2, π‘˜2] = 𝑠2 βˆ’ π‘˜2. Now, as the dimension of𝐢1⨁̇𝐢2 is π‘˜2 (which is less than or equal to 𝑠2), the coveringradius of𝐢1⨁̇𝐢2 depends only on the coordinates pertainingto the code 𝐢2. But 𝐢2 has covering radius 𝑠2 βˆ’ π‘˜2 and hence

  • ISRN Combinatorics 5

    has partition number π‘˜2. So, 𝐢1⨁̇𝐢2 also will have partitionnumber π‘˜2 and hence will have covering radius 𝑠1+𝑠2βˆ’1βˆ’π‘˜2which is equal to π‘‘π‘ž[𝑠1+𝑠2βˆ’1, π‘˜2], which implies that𝐢1⨁̇𝐢2is MDS. This completes the proof.

    5. Conclusion

    We discussed the normality of codes over Fπ‘ž in RT-metricand determined its norm with respect to various coordinatepositions. We also established that the last coordinate is notacceptable for any nontrivial code in this metric whichmakesthe ADS construction less significant as far as the higherdimensional RT-metric codes are concerned.

    Conflict of Interests

    The authors declare that there is no conflict of interestsregarding the publication of this paper.

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    [2] G. D. Cohen, M. G. Karpovsky, H. F. Mattson, and J. R. Schatz,β€œCovering radiusβ€”survey and recent results,” IEEE Transac-tions on Information Theory, vol. 31, no. 3, pp. 328–343, 1985.

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    [7] A.C. Lobstein andG. J.M. vanWee, β€œOnnormal and subnormalq-ary codes,” IEEE Transactions on Information Theory, vol. 35,no. 6, pp. 1291–1295, 1989.

    [8] R. S. Selvaraj and V. Marka, β€œNormality of binary codes inRosenbloom-Tsfasman metric,” in Proceedings of the Interna-tional Conference on Advances in Computing, Communicationsand Informatics (ICACCI ’13), pp. 1370–1373, August 2013.

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    [11] I. Siap and M. Ozen, β€œThe complete weight enumerator forcodes over 𝑀

    𝑛×𝑠 (𝑅) with respect to the Rosenbloom-Tsfasmanmetric,” Applied Mathematics Letters, vol. 17, no. 1, pp. 65–69,2004.

    [12] S. T.Dougherty andK. Shiromoto, β€œMaximumdistance codes inπ‘€π‘Žπ‘‘π‘›Γ—π‘ 

    (Zπ‘˜)with a non-hammingmetric and uniformdistribu-

    tions,” Designs, Codes, and Cryptography, vol. 33, no. 1, pp. 45–61, 2004.

    [13] S. Jain, β€œCT burstsβ€”from classical to array coding,” DiscreteMathematics, vol. 308, no. 9, pp. 1489–1499, 2008.

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